diff --git a/adonisrc.ts b/adonisrc.ts index 97e4528..19e946c 100644 --- a/adonisrc.ts +++ b/adonisrc.ts @@ -35,6 +35,7 @@ export default defineConfig({ () => import('#start/rules/dependent_array_min_length'), () => import('#start/rules/referenceValidation'), () => import('#start/rules/valid_mimetype'), + () => import('#start/rules/array_contains_types'), ], /* |-------------------------------------------------------------------------- diff --git a/app/Controllers/Http/Admin/AdminuserController.ts b/app/Controllers/Http/Admin/AdminuserController.ts index ce99724..2962cbd 100644 --- a/app/Controllers/Http/Admin/AdminuserController.ts +++ b/app/Controllers/Http/Admin/AdminuserController.ts @@ -85,7 +85,9 @@ export default class AdminuserController { // return response.badRequest(error.messages); throw error; } - const input = request.only(['login', 'email', 'password', 'first_name', 'last_name']); + + const input: Record = request.only(['login', 'email','first_name', 'last_name']); + input.password = request.input('new_password'); const user = await User.create(input); if (request.input('roles')) { const roles: Array = request.input('roles'); @@ -95,7 +97,6 @@ export default class AdminuserController { session.flash('message', 'User has been created successfully'); return response.redirect().toRoute('settings.user.index'); } - public async show({ request, inertia }: HttpContext) { const id = request.param('id'); const user = await User.query().where('id', id).firstOrFail(); @@ -139,9 +140,11 @@ export default class AdminuserController { }); // password is optional - let input; - if (request.input('password')) { - input = request.only(['login', 'email', 'password', 'first_name', 'last_name']); + let input: Record; + + if (request.input('new_password')) { + input = request.only(['login', 'email', 'first_name', 'last_name']); + input.password = request.input('new_password'); } else { input = request.only(['login', 'email', 'first_name', 'last_name']); } @@ -156,7 +159,6 @@ export default class AdminuserController { session.flash('message', 'User has been updated successfully'); return response.redirect().toRoute('settings.user.index'); } - public async destroy({ request, response, session }: HttpContext) { const id = request.param('id'); const user = await User.findOrFail(id); diff --git a/app/Controllers/Http/Admin/MimetypeController.ts b/app/Controllers/Http/Admin/MimetypeController.ts index 1d9d2a7..561c0ad 100644 --- a/app/Controllers/Http/Admin/MimetypeController.ts +++ b/app/Controllers/Http/Admin/MimetypeController.ts @@ -64,7 +64,7 @@ export default class MimetypeController { 'maxLength': '{{ field }} must be less then {{ max }} characters long', 'isUnique': '{{ field }} must be unique, and this value is already taken', 'required': '{{ field }} is required', - 'file_extension.minLength': 'at least {{ min }} mimetypes must be defined', + 'file_extension.array.minLength': 'at least {{ min }} mimetypes must be defined', 'file_extension.*.string': 'Each file extension must be a valid string', // Adjusted to match the type }; diff --git a/app/Controllers/Http/Api/AuthorsController.ts b/app/Controllers/Http/Api/AuthorsController.ts index bc964a9..7209699 100644 --- a/app/Controllers/Http/Api/AuthorsController.ts +++ b/app/Controllers/Http/Api/AuthorsController.ts @@ -9,6 +9,7 @@ export default class AuthorsController { // where exists (select * from gba.documents inner join gba.link_documents_persons on "documents"."id" = "link_documents_persons"."document_id" // where ("link_documents_persons"."role" = 'author') and ("persons"."id" = "link_documents_persons"."person_id")); const authors = await Person.query() + .preload('datasets') .where('name_type', 'Personal') .whereHas('datasets', (dQuery) => { dQuery.wherePivot('role', 'author'); @@ -27,7 +28,10 @@ export default class AuthorsController { if (request.input('filter')) { // users = users.whereRaw('name like %?%', [request.input('search')]) const searchTerm = request.input('filter'); - authors.whereILike('first_name', `%${searchTerm}%`).orWhereILike('last_name', `%${searchTerm}%`); + authors.andWhere((query) => { + query.whereILike('first_name', `%${searchTerm}%`) + .orWhereILike('last_name', `%${searchTerm}%`); + }); // .orWhere('email', 'like', `%${searchTerm}%`); } diff --git a/app/Controllers/Http/Api/HomeController.ts b/app/Controllers/Http/Api/HomeController.ts index 020f651..fdec7f9 100644 --- a/app/Controllers/Http/Api/HomeController.ts +++ b/app/Controllers/Http/Api/HomeController.ts @@ -17,7 +17,8 @@ export default class HomeController { // .preload('authors') // .orderBy('server_date_published'); - const datasets = await db.from('documents as doc') + const datasets = await db + .from('documents as doc') .select(['publish_id', 'server_date_published', db.raw(`date_part('year', server_date_published) as pub_year`)]) .where('server_state', serverState) .innerJoin('link_documents_persons as ba', 'doc.id', 'ba.document_id') @@ -59,7 +60,6 @@ export default class HomeController { // const year = params.year; // const from = parseInt(year); try { - // const datasets = await Database.from('documents as doc') // .select([Database.raw(`date_part('month', server_date_published) as pub_month`), Database.raw('COUNT(*) as count')]) // .where('server_state', serverState) @@ -68,9 +68,12 @@ export default class HomeController { // .groupBy('pub_month'); // // .orderBy('server_date_published'); - const years = [2021, 2022, 2023]; // Add the second year + // Calculate the last 4 years including the current year + const currentYear = new Date().getFullYear(); + const years = Array.from({ length: 4 }, (_, i) => currentYear - (i + 1)).reverse(); - const result = await db.from('documents as doc') + const result = await db + .from('documents as doc') .select([ db.raw(`date_part('year', server_date_published) as pub_year`), db.raw(`date_part('month', server_date_published) as pub_month`), @@ -83,7 +86,7 @@ export default class HomeController { .groupBy('pub_year', 'pub_month') .orderBy('pub_year', 'asc') .orderBy('pub_month', 'asc'); - + const labels = Array.from({ length: 12 }, (_, i) => i + 1); // Assuming 12 months const inputDatasets: Map = result.reduce((acc, item) => { @@ -100,15 +103,15 @@ export default class HomeController { acc[pub_year].data[pub_month - 1] = parseInt(count); - return acc ; + return acc; }, {}); const outputDatasets = Object.entries(inputDatasets).map(([year, data]) => ({ data: data.data, label: year, borderColor: data.borderColor, - fill: data.fill - })); + fill: data.fill, + })); const data = { labels: labels, @@ -126,11 +129,11 @@ export default class HomeController { private getRandomHexColor() { const letters = '0123456789ABCDEF'; let color = '#'; - + for (let i = 0; i < 6; i++) { color += letters[Math.floor(Math.random() * 16)]; } - + return color; } } @@ -139,5 +142,4 @@ interface ChartDataset { label: string; borderColor: string; fill: boolean; - } diff --git a/app/Controllers/Http/Auth/AuthController.ts b/app/Controllers/Http/Auth/AuthController.ts index 71256f2..08b1c05 100644 --- a/app/Controllers/Http/Auth/AuthController.ts +++ b/app/Controllers/Http/Auth/AuthController.ts @@ -5,7 +5,7 @@ import BackupCode from '#models/backup_code'; // import InvalidCredentialException from 'App/Exceptions/InvalidCredentialException'; import { authValidator } from '#validators/auth'; import hash from '@adonisjs/core/services/hash'; - +import db from '@adonisjs/lucid/services/db'; import TwoFactorAuthProvider from '#app/services/TwoFactorAuthProvider'; // import { Authenticator } from '@adonisjs/auth'; // import { LoginState } from 'Contracts/enums'; @@ -29,6 +29,10 @@ export default class AuthController { const { email, password } = request.only(['email', 'password']); try { + + await db.connection().rawQuery('SELECT 1') + + // // attempt to verify credential and login user // await auth.use('web').attempt(email, plainPassword); @@ -51,6 +55,9 @@ export default class AuthController { await auth.use('web').login(user); } catch (error) { + if (error.code === 'ECONNREFUSED') { + throw error + } // if login fails, return vague form message and redirect back session.flash('message', 'Your username, email, or password is incorrect'); return response.redirect().back(); diff --git a/app/Controllers/Http/Editor/DatasetController.ts b/app/Controllers/Http/Editor/DatasetController.ts index acaf505..5ec3910 100644 --- a/app/Controllers/Http/Editor/DatasetController.ts +++ b/app/Controllers/Http/Editor/DatasetController.ts @@ -18,9 +18,33 @@ import { HttpException } from 'node-exceptions'; import { ModelQueryBuilderContract } from '@adonisjs/lucid/types/model'; import vine, { SimpleMessagesProvider } from '@vinejs/vine'; import mail from '@adonisjs/mail/services/main'; -// import { resolveMx } from 'dns/promises'; -// import * as net from 'net'; import { validate } from 'deep-email-validator'; +import { + TitleTypes, + DescriptionTypes, + ContributorTypes, + PersonNameTypes, + ReferenceIdentifierTypes, + RelationTypes, + SubjectTypes, + DatasetTypes, +} from '#contracts/enums'; +import { TransactionClientContract } from '@adonisjs/lucid/types/database'; +import db from '@adonisjs/lucid/services/db'; +import Project from '#models/project'; +import License from '#models/license'; +import Language from '#models/language'; +import File from '#models/file'; +import Coverage from '#models/coverage'; +import Title from '#models/title'; +import Description from '#models/description'; +import Subject from '#models/subject'; +import DatasetReference from '#models/dataset_reference'; +import Collection from '#models/collection'; +import CollectionRole from '#models/collection_role'; +import { updateEditorDatasetValidator } from '#validators/dataset'; +import { savePersons } from '#app/utils/utility-functions'; + // Create a new instance of the client const client = new Client({ node: 'http://localhost:9200' }); // replace with your OpenSearch endpoint @@ -63,8 +87,15 @@ export default class DatasetsController { } datasets.orderBy(attribute, sortOrder); } else { - // users.orderBy('created_at', 'desc'); - datasets.orderBy('id', 'asc'); + // datasets.orderBy('id', 'asc'); + // Custom ordering to prioritize rejected_editor state + datasets.orderByRaw(` + CASE + WHEN server_state = 'rejected_reviewer' THEN 0 + ELSE 1 + END ASC, + id ASC + `); } // const users = await User.query().orderBy('login').paginate(page, limit); @@ -217,6 +248,10 @@ export default class DatasetsController { if (dataset.reject_reviewer_note != null) { dataset.reject_reviewer_note = null; } + if (dataset.reject_editor_note != null) { + dataset.reject_editor_note = null; + } + //save main and additional titles const reviewer_id = request.input('reviewer_id', null); @@ -255,70 +290,7 @@ export default class DatasetsController { }); } - // private async checkEmailDomain(email: string): Promise { - // const domain = email.split('@')[1]; - // try { - // // Step 1: Check MX records for the domain - // const mxRecords = await resolveMx(domain); - // if (mxRecords.length === 0) { - // return false; // No MX records, can't send email - // } - - // // Sort MX records by priority - // mxRecords.sort((a, b) => a.priority - b.priority); - - // // Step 2: Attempt SMTP connection to the first available mail server - // const smtpServer = mxRecords[0].exchange; - - // return await this.checkMailboxExists(smtpServer, email); - // } catch (error) { - // console.error('Error during MX lookup or SMTP validation:', error); - // return false; - // } - // } - - //// Helper function to check if the mailbox exists using SMTP - // private async checkMailboxExists(smtpServer: string, email: string): Promise { - // return new Promise((resolve, reject) => { - // const socket = net.createConnection(25, smtpServer); - - // socket.on('connect', () => { - // socket.write(`HELO ${smtpServer}\r\n`); - // socket.write(`MAIL FROM: \r\n`); - // socket.write(`RCPT TO: <${email}>\r\n`); - // }); - - // socket.on('data', (data) => { - // const response = data.toString(); - // if (response.includes('250')) { - // // 250 is an SMTP success code - // socket.end(); - // resolve(true); // Email exists - // } else if (response.includes('550')) { - // // 550 means the mailbox doesn't exist - // socket.end(); - // resolve(false); // Email doesn't exist - // } - // }); - - // socket.on('error', (error) => { - // console.error('SMTP connection error:', error); - // socket.end(); - // resolve(false); - // }); - - // socket.on('end', () => { - // // SMTP connection closed - // }); - - // socket.setTimeout(5000, () => { - // // Timeout after 5 seconds - // socket.end(); - // resolve(false); // Assume email doesn't exist if no response - // }); - // }); - // } public async rejectUpdate({ request, response, auth }: HttpContext) { const authUser = auth.user!; @@ -353,7 +325,7 @@ export default class DatasetsController { return response .flash( `Invalid server state. Dataset with id ${id} cannot be rejected. Datset has server state ${dataset.server_state}.`, - 'warning' + 'warning', ) .redirect() .toRoute('editor.dataset.list'); @@ -388,7 +360,9 @@ export default class DatasetsController { emailStatusMessage = ` A rejection email was successfully sent to ${dataset.user.email}.`; } catch (error) { logger.error(error); - return response.flash('Dataset has not been rejected due to an email error: ' + error.message, 'error').toRoute('editor.dataset.list'); + return response + .flash('Dataset has not been rejected due to an email error: ' + error.message, 'error') + .toRoute('editor.dataset.list'); } } else { emailStatusMessage = ` However, the email could not be sent because the submitter's email address (${dataset.user.email}) is not valid.`; @@ -404,7 +378,7 @@ export default class DatasetsController { .toRoute('editor.dataset.list'); } - public async publish({ request, inertia, response }: HttpContext) { + public async publish({ request, inertia, response, auth }: HttpContext) { const id = request.param('id'); const dataset = await Dataset.query() @@ -428,8 +402,14 @@ export default class DatasetsController { .back(); } + + return inertia.render('Editor/Dataset/Publish', { dataset, + can: { + reject: await auth.user?.can(['dataset-editor-reject']), + publish: await auth.user?.can(['dataset-publish']), + }, }); } @@ -471,6 +451,119 @@ export default class DatasetsController { } } + public async rejectToReviewer({ request, inertia, response }: HttpContext) { + const id = request.param('id'); + const dataset = await Dataset.query() + .where('id', id) + .preload('reviewer', (builder) => { + builder.select('id', 'login', 'email'); + }) + .firstOrFail(); + + const validStates = ['reviewed']; + if (!validStates.includes(dataset.server_state)) { + // session.flash('errors', 'Invalid server state!'); + return response + .flash( + 'warning', + `Invalid server state. Dataset with id ${id} cannot be rejected to the reviewer. Datset has server state ${dataset.server_state}.`, + ) + .redirect() + .toRoute('editor.dataset.list'); + } + + return inertia.render('Editor/Dataset/RejectToReviewer', { + dataset, + }); + } + + public async rejectToReviewerUpdate({ request, response, auth }: HttpContext) { + const authUser = auth.user!; + + const id = request.param('id'); + const dataset = await Dataset.query() + .where('id', id) + .preload('reviewer', (builder) => { + builder.select('id', 'login', 'email'); + }) + .firstOrFail(); + + const newSchema = vine.object({ + server_state: vine.string().trim(), + reject_editor_note: vine.string().trim().minLength(10).maxLength(500), + send_mail: vine.boolean().optional(), + }); + + try { + // await request.validate({ schema: newSchema }); + const validator = vine.compile(newSchema); + await request.validateUsing(validator); + } catch (error) { + // return response.badRequest(error.messages); + throw error; + } + + const validStates = ['reviewed']; + if (!validStates.includes(dataset.server_state)) { + // throw new Error('Invalid server state!'); + // return response.flash('warning', 'Invalid server state. Dataset cannot be released to editor').redirect().back(); + return response + .flash( + `Invalid server state. Dataset with id ${id} cannot be rejected to reviewer. Datset has server state ${dataset.server_state}.`, + 'warning', + ) + .redirect() + .toRoute('editor.dataset.list'); + } + + dataset.server_state = 'rejected_to_reviewer'; + const rejectEditorNote = request.input('reject_editor_note', ''); + dataset.reject_editor_note = rejectEditorNote; + + // add logic for sending reject message + const sendMail = request.input('send_email', false); + // const validRecipientEmail = await this.checkEmailDomain('arno.kaimbacher@outlook.at'); + const validationResult = await validate({ + email: dataset.reviewer.email, + validateSMTP: false, + }); + const validRecipientEmail: boolean = validationResult.valid; + + await dataset.save(); + + let emailStatusMessage = ''; + if (sendMail == true) { + if (dataset.reviewer.email && validRecipientEmail) { + try { + await mail.send((message) => { + message.to(dataset.reviewer.email).subject('Dataset Rejection Notification').html(` +

Dear ${dataset.reviewer.login},

+

Your dataset with ID ${dataset.id} has been rejected.

+

Reason for rejection: ${rejectEditorNote}

+

Best regards,
Your Tethys editor: ${authUser.login}

+ `); + }); + emailStatusMessage = ` A rejection email was successfully sent to ${dataset.reviewer.email}.`; + } catch (error) { + logger.error(error); + return response + .flash('Dataset has not been rejected due to an email error: ' + error.message, 'error') + .toRoute('editor.dataset.list'); + } + } else { + emailStatusMessage = ` However, the email could not be sent because the submitter's email address (${dataset.reviewer.email}) is not valid.`; + } + } + + + return response + .flash( + `You have successfully rejected dataset ${dataset.id} reviewed by ${dataset.reviewer.login}.${emailStatusMessage}`, + 'message', + ) + .toRoute('editor.dataset.list'); + } + public async doiCreate({ request, inertia }: HttpContext) { const id = request.param('id'); const dataset = await Dataset.query() @@ -536,10 +629,376 @@ export default class DatasetsController { public async show({}: HttpContext) {} - public async edit({}: HttpContext) {} + public async edit({ request, inertia, response }: HttpContext) { + const id = request.param('id'); + const datasetQuery = Dataset.query().where('id', id); + datasetQuery + .preload('titles', (query) => query.orderBy('id', 'asc')) + .preload('descriptions', (query) => query.orderBy('id', 'asc')) + .preload('coverage') + .preload('licenses') + .preload('authors', (query) => query.orderBy('pivot_sort_order', 'asc')) + .preload('contributors', (query) => query.orderBy('pivot_sort_order', 'asc')) + // .preload('subjects') + .preload('subjects', (builder) => { + builder.orderBy('id', 'asc').withCount('datasets'); + }) + .preload('references') + .preload('files', (query) => { + query.orderBy('sort_order', 'asc'); // Sort by sort_order column + }); + + const dataset = await datasetQuery.firstOrFail(); + const validStates = ['editor_accepted', 'rejected_reviewer']; + if (!validStates.includes(dataset.server_state)) { + // session.flash('errors', 'Invalid server state!'); + return response + .flash( + `Invalid server state. Dataset with id ${id} cannot be edited. Datset has server state ${dataset.server_state}.`, + 'warning', + ) + .toRoute('editor.dataset.list'); + } + + const titleTypes = Object.entries(TitleTypes) + .filter(([value]) => value !== 'Main') + .map(([key, value]) => ({ value: key, label: value })); + + const descriptionTypes = Object.entries(DescriptionTypes) + .filter(([value]) => value !== 'Abstract') + .map(([key, value]) => ({ value: key, label: value })); + + const languages = await Language.query().where('active', true).pluck('part1', 'part1'); + + // const contributorTypes = Config.get('enums.contributor_types'); + const contributorTypes = Object.entries(ContributorTypes).map(([key, value]) => ({ value: key, label: value })); + + // const nameTypes = Config.get('enums.name_types'); + const nameTypes = Object.entries(PersonNameTypes).map(([key, value]) => ({ value: key, label: value })); + + // const messages = await Database.table('messages') + // .pluck('help_text', 'metadata_element'); + + const projects = await Project.query().pluck('label', 'id'); + + const currentDate = new Date(); + const currentYear = currentDate.getFullYear(); + const years = Array.from({ length: currentYear - 1990 + 1 }, (_, index) => 1990 + index); + + const licenses = await License.query().select('id', 'name_long').where('active', 'true').pluck('name_long', 'id'); + // const userHasRoles = user.roles; + // const datasetHasLicenses = await dataset.related('licenses').query().pluck('id'); + // const checkeds = dataset.licenses.first().id; + + // const doctypes = { + // analysisdata: { label: 'Analysis', value: 'analysisdata' }, + // measurementdata: { label: 'Measurements', value: 'measurementdata' }, + // monitoring: 'Monitoring', + // remotesensing: 'Remote Sensing', + // gis: 'GIS', + // models: 'Models', + // mixedtype: 'Mixed Type', + // }; + + return inertia.render('Editor/Dataset/Edit', { + dataset, + titletypes: titleTypes, + descriptiontypes: descriptionTypes, + contributorTypes, + nameTypes, + languages, + // messages, + projects, + licenses, + // datasetHasLicenses: Object.keys(datasetHasLicenses).map((key) => datasetHasLicenses[key]), //convert object to array with license ids + // checkeds, + years, + // languages, + subjectTypes: SubjectTypes, + referenceIdentifierTypes: Object.entries(ReferenceIdentifierTypes).map(([key, value]) => ({ value: key, label: value })), + relationTypes: Object.entries(RelationTypes).map(([key, value]) => ({ value: key, label: value })), + doctypes: DatasetTypes, + }); + } + + public async update({ request, response, session }: HttpContext) { + // Get the dataset id from the route parameter + const datasetId = request.param('id'); + // Retrieve the dataset and load its existing files + const dataset = await Dataset.findOrFail(datasetId); + await dataset.load('files'); + + let trx: TransactionClientContract | null = null; + try { + await request.validateUsing(updateEditorDatasetValidator); + trx = await db.transaction(); + // const user = (await User.find(auth.user?.id)) as User; + // await this.createDatasetAndAssociations(user, request, trx); + const dataset = await Dataset.findOrFail(datasetId); + + // save the licenses + const licenses: number[] = request.input('licenses', []); + // await dataset.useTransaction(trx).related('licenses').sync(licenses); + await dataset.useTransaction(trx).related('licenses').sync(licenses); + + // save authors and contributors + await dataset.useTransaction(trx).related('authors').sync([]); + await dataset.useTransaction(trx).related('contributors').sync([]); + await savePersons(dataset, request.input('authors', []), 'author', trx); + await savePersons(dataset, request.input('contributors', []), 'contributor', trx); + + //save the titles: + const titles = request.input('titles', []); + // const savedTitles:Array = []; + for (const titleData of titles) { + if (titleData.id) { + const title = await Title.findOrFail(titleData.id); + title.value = titleData.value; + title.language = titleData.language; + title.type = titleData.type; + if (title.$isDirty) { + await title.useTransaction(trx).save(); + // await dataset.useTransaction(trx).related('titles').save(title); + // savedTitles.push(title); + } + } else { + const title = new Title(); + title.fill(titleData); + // savedTitles.push(title); + await dataset.useTransaction(trx).related('titles').save(title); + } + } + + // save the abstracts + const descriptions = request.input('descriptions', []); + // const savedTitles:Array<Title> = []; + for (const descriptionData of descriptions) { + if (descriptionData.id) { + const description = await Description.findOrFail(descriptionData.id); + description.value = descriptionData.value; + description.language = descriptionData.language; + description.type = descriptionData.type; + if (description.$isDirty) { + await description.useTransaction(trx).save(); + // await dataset.useTransaction(trx).related('titles').save(title); + // savedTitles.push(title); + } + } else { + const description = new Description(); + description.fill(descriptionData); + // savedTitles.push(title); + await dataset.useTransaction(trx).related('descriptions').save(description); + } + } + + // Process all subjects/keywords from the request + const subjects = request.input('subjects'); + for (const subjectData of subjects) { + // Case 1: Subject already exists in the database (has an ID) + if (subjectData.id) { + // Retrieve the existing subject + const existingSubject = await Subject.findOrFail(subjectData.id); + + // Update subject properties from the request data + existingSubject.value = subjectData.value; + existingSubject.type = subjectData.type; + existingSubject.external_key = subjectData.external_key; + + // Only save if there are actual changes + if (existingSubject.$isDirty) { + await existingSubject.save(); + } + + // Note: The relationship between dataset and subject is already established, + // so we don't need to attach it again + } + // Case 2: New subject being added (no ID) + else { + // Check if a subject with the same value and type already exists in the database + const subject = await Subject.firstOrNew({ value: subjectData.value, type: subjectData.type }, subjectData); + + if (subject.$isNew === true) { + // If it's a completely new subject, create and associate it with the dataset + await dataset.useTransaction(trx).related('subjects').save(subject); + } else { + // If the subject already exists, just create the relationship + await dataset.useTransaction(trx).related('subjects').attach([subject.id]); + } + } + } + + const subjectsToDelete = request.input('subjectsToDelete', []); + for (const subjectData of subjectsToDelete) { + if (subjectData.id) { + // const subject = await Subject.findOrFail(subjectData.id); + const subject = await Subject.query() + .where('id', subjectData.id) + .preload('datasets', (builder) => { + builder.orderBy('id', 'asc'); + }) + .withCount('datasets') + .firstOrFail(); + + // Check if the subject is used by multiple datasets + if (subject.$extras.datasets_count > 1) { + // If used by multiple datasets, just detach it from the current dataset + await dataset.useTransaction(trx).related('subjects').detach([subject.id]); + } else { + // If only used by this dataset, delete the subject completely + + await dataset.useTransaction(trx).related('subjects').detach([subject.id]); + await subject.useTransaction(trx).delete(); + } + } + } + + // Process references + const references = request.input('references', []); + // First, get existing references to determine which ones to update vs. create + const existingReferences = await dataset.related('references').query(); + const existingReferencesMap: Map<number, DatasetReference> = new Map(existingReferences.map((ref) => [ref.id, ref])); + + for (const referenceData of references) { + if (existingReferencesMap.has(referenceData.id) && referenceData.id) { + // Update existing reference + const reference = existingReferencesMap.get(referenceData.id); + if (reference) { + reference.merge(referenceData); + if (reference.$isDirty) { + await reference.useTransaction(trx).save(); + } + } + } else { + // Create new reference + const dataReference = new DatasetReference(); + dataReference.fill(referenceData); + await dataset.useTransaction(trx).related('references').save(dataReference); + } + } + + // Handle references to delete if provided + const referencesToDelete = request.input('referencesToDelete', []); + for (const referenceData of referencesToDelete) { + if (referenceData.id) { + const reference = await DatasetReference.findOrFail(referenceData.id); + await reference.useTransaction(trx).delete(); + } + } + + // save coverage + const coverageData = request.input('coverage'); + if (coverageData) { + if (coverageData.id) { + const coverage = await Coverage.findOrFail(coverageData.id); + coverage.merge(coverageData); + if (coverage.$isDirty) { + await coverage.useTransaction(trx).save(); + } + } + } + + const input = request.only(['project_id', 'embargo_date', 'language', 'type', 'creating_corporation']); + // dataset.type = request.input('type'); + dataset.merge(input); + // let test: boolean = dataset.$isDirty; + await dataset.useTransaction(trx).save(); + + await trx.commit(); + // console.log('Dataset has been updated successfully'); + + session.flash('message', 'Dataset has been updated successfully'); + // return response.redirect().toRoute('user.index'); + return response.redirect().toRoute('editor.dataset.edit', [dataset.id]); + } catch (error) { + if (trx !== null) { + await trx.rollback(); + } + console.error('Failed to update dataset and related models:', error); + // throw new ValidationException(true, { 'upload error': `failed to create dataset and related models. ${error}` }); + throw error; + } + } + + public async categorize({ inertia, request, response }: HttpContext) { + const id = request.param('id'); + // Preload dataset and its "collections" relation + const dataset = await Dataset.query().where('id', id).preload('collections').firstOrFail(); + const validStates = ['editor_accepted', 'rejected_reviewer']; + if (!validStates.includes(dataset.server_state)) { + // session.flash('errors', 'Invalid server state!'); + return response + .flash( + 'warning', + `Invalid server state. Dataset with id ${id} cannot be edited. Datset has server state ${dataset.server_state}.`, + ) + .redirect() + .toRoute('editor.dataset.list'); + } + + const collectionRoles = await CollectionRole.query() + .whereIn('name', ['ddc', 'ccs']) + .preload('collections', (coll: Collection) => { + // preloa only top level collection with noparent_id + coll.whereNull('parent_id').orderBy('number', 'asc'); + }) + .exec(); + + return inertia.render('Editor/Dataset/Category', { + collectionRoles: collectionRoles, + dataset: dataset, + relatedCollections: dataset.collections, + }); + } + + public async categorizeUpdate({ request, response, session }: HttpContext) { + // Get the dataset id from the route parameter + const id = request.param('id'); + const dataset = await Dataset.query().preload('files').where('id', id).firstOrFail(); + + const validStates = ['editor_accepted', 'rejected_reviewer']; + if (!validStates.includes(dataset.server_state)) { + return response + .flash( + 'warning', + `Invalid server state. Dataset with id ${id} cannot be categorized. Dataset has server state ${dataset.server_state}.`, + ) + .redirect() + .toRoute('editor.dataset.list'); + } + + let trx: TransactionClientContract | null = null; + try { + trx = await db.transaction(); + // const user = (await User.find(auth.user?.id)) as User; + // await this.createDatasetAndAssociations(user, request, trx); + + // Retrieve the selected collections from the request. + // This should be an array of collection ids. + const collections: number[] = request.input('collections', []); + + // Synchronize the dataset collections using the transaction. + await dataset.useTransaction(trx).related('collections').sync(collections); + + // Commit the transaction.await trx.commit() + await trx.commit(); + + // Redirect with a success flash message. + // return response.flash('success', 'Dataset collections updated successfully!').redirect().toRoute('dataset.list'); + + session.flash('message', 'Dataset collections updated successfully!'); + return response.redirect().toRoute('editor.dataset.list'); + } catch (error) { + if (trx !== null) { + await trx.rollback(); + } + console.error('Failed tocatgorize dataset collections:', error); + // throw new ValidationException(true, { 'upload error': `failed to create dataset and related models. ${error}` }); + throw error; + } + } // public async update({}: HttpContextContract) {} - public async update({ response }: HttpContext) { + public async updateOpensearch({ response }: HttpContext) { const id = 273; //request.param('id'); const dataset = await Dataset.query().preload('xmlCache').where('id', id).firstOrFail(); // add xml elements @@ -655,6 +1114,19 @@ export default class DatasetsController { } } + public async download({ params, response }: HttpContext) { + const id = params.id; + // Find the file by ID + const file = await File.findOrFail(id); + // const filePath = await drive.use('local').getUrl('/'+ file.filePath) + const filePath = file.filePath; + const fileExt = file.filePath.split('.').pop() || ''; + // Set the response headers and download the file + response.header('Content-Type', file.mime_type || 'application/octet-stream'); + response.attachment(`${file.label}.${fileExt}`); + return response.download(filePath); + } + public async destroy({}: HttpContext) {} private async createXmlRecord(dataset: Dataset, datasetNode: XMLBuilder) { diff --git a/app/Controllers/Http/Reviewer/DatasetController.ts b/app/Controllers/Http/Reviewer/DatasetController.ts index 76ad4d8..6b54772 100644 --- a/app/Controllers/Http/Reviewer/DatasetController.ts +++ b/app/Controllers/Http/Reviewer/DatasetController.ts @@ -9,6 +9,7 @@ import vine from '@vinejs/vine'; import mail from '@adonisjs/mail/services/main'; import logger from '@adonisjs/core/services/logger'; import { validate } from 'deep-email-validator'; +import File from '#models/file'; interface Dictionary { [index: string]: string; @@ -38,13 +39,21 @@ export default class DatasetsController { } datasets.orderBy(attribute, sortOrder); } else { - // users.orderBy('created_at', 'desc'); - datasets.orderBy('id', 'asc'); + // datasets.orderBy('id', 'asc'); + // Custom ordering to prioritize rejected_editor state + datasets.orderByRaw(` + CASE + WHEN server_state = 'rejected_to_reviewer' THEN 0 + ELSE 1 + END ASC, + id ASC + `); } // const users = await User.query().orderBy('login').paginate(page, limit); const myDatasets = await datasets - .where('server_state', 'approved') + // .where('server_state', 'approved') + .whereIn('server_state', ['approved', 'rejected_to_reviewer']) .where('reviewer_id', user.id) .preload('titles') @@ -62,7 +71,52 @@ export default class DatasetsController { }); } - public async review({ request, inertia, response }: HttpContext) { + public async review({ request, inertia, response, auth }: HttpContext) { + const id = request.param('id'); + const datasetQuery = Dataset.query().where('id', id); + + datasetQuery + .preload('titles', (query) => query.orderBy('id', 'asc')) + .preload('descriptions', (query) => query.orderBy('id', 'asc')) + .preload('coverage') + .preload('licenses') + .preload('authors', (query) => query.orderBy('pivot_sort_order', 'asc')) + .preload('contributors', (query) => query.orderBy('pivot_sort_order', 'asc')) + // .preload('subjects') + .preload('subjects', (builder) => { + builder.orderBy('id', 'asc').withCount('datasets'); + }) + .preload('references') + .preload('project') + .preload('files', (query) => { + query.orderBy('sort_order', 'asc'); // Sort by sort_order column + }); + + const dataset = await datasetQuery.firstOrFail(); + + const validStates = ['approved', 'rejected_to_reviewer']; + if (!validStates.includes(dataset.server_state)) { + // session.flash('errors', 'Invalid server state!'); + return response + .flash( + 'warning', + `Invalid server state. Dataset with id ${id} cannot be reviewed. Datset has server state ${dataset.server_state}.`, + ) + .redirect() + .toRoute('reviewer.dataset.list'); + } + + return inertia.render('Reviewer/Dataset/Review', { + dataset, + can: { + review: await auth.user?.can(['dataset-review']), + reject: await auth.user?.can(['dataset-review-reject']), + }, + }); + + } + + public async review_old({ request, inertia, response, auth }: HttpContext) { const id = request.param('id'); const dataset = await Dataset.query() .where('id', id) @@ -158,6 +212,10 @@ export default class DatasetsController { return inertia.render('Reviewer/Dataset/Review', { dataset, fields: fields, + can: { + review: await auth.user?.can(['dataset-review']), + reject: await auth.user?.can(['dataset-review-reject']), + }, }); } @@ -166,7 +224,7 @@ export default class DatasetsController { // const { id } = params; const dataset = await Dataset.findOrFail(id); - const validStates = ['approved']; + const validStates = ['approved', 'rejected_to_reviewer']; if (!validStates.includes(dataset.server_state)) { // throw new Error('Invalid server state!'); // return response.flash('warning', 'Invalid server state. Dataset cannot be released to editor').redirect().back(); @@ -180,6 +238,10 @@ export default class DatasetsController { } dataset.server_state = 'reviewed'; + // if editor has rejected to reviewer: + if (dataset.reject_editor_note != null) { + dataset.reject_editor_note = null; + } try { // await dataset.related('editor').associate(user); // speichert schon ab @@ -203,7 +265,7 @@ export default class DatasetsController { }) .firstOrFail(); - const validStates = ['approved']; + const validStates = ['approved', 'rejected_to_reviewer']; if (!validStates.includes(dataset.server_state)) { // session.flash('errors', 'Invalid server state!'); return response @@ -250,12 +312,12 @@ export default class DatasetsController { throw error; } - const validStates = ['approved']; + const validStates = ['approved', 'rejected_to_reviewer']; if (!validStates.includes(dataset.server_state)) { // throw new Error('Invalid server state!'); // return response.flash('warning', 'Invalid server state. Dataset cannot be released to editor').redirect().back(); return response - .flash( + .flash( `Invalid server state. Dataset with id ${id} cannot be rejected. Datset has server state ${dataset.server_state}.`, 'warning', ) @@ -307,4 +369,17 @@ export default class DatasetsController { .toRoute('reviewer.dataset.list') .flash(`You have rejected dataset ${dataset.id}! to editor ${dataset.editor.login}`, 'message'); } + + public async download({ params, response }: HttpContext) { + const id = params.id; + // Find the file by ID + const file = await File.findOrFail(id); + // const filePath = await drive.use('local').getUrl('/'+ file.filePath) + const filePath = file.filePath; + const fileExt = file.filePath.split('.').pop() || ''; + // Set the response headers and download the file + response.header('Content-Type', file.mime_type || 'application/octet-stream'); + response.attachment(`${file.label}.${fileExt}`); + return response.download(filePath); + } } diff --git a/app/Controllers/Http/Submitter/DatasetController.ts b/app/Controllers/Http/Submitter/DatasetController.ts index a1a6643..245b5d9 100644 --- a/app/Controllers/Http/Submitter/DatasetController.ts +++ b/app/Controllers/Http/Submitter/DatasetController.ts @@ -29,23 +29,30 @@ import { } from '#contracts/enums'; import { ModelQueryBuilderContract } from '@adonisjs/lucid/types/model'; import DatasetReference from '#models/dataset_reference'; -import { cuid } from '@adonisjs/core/helpers'; import File from '#models/file'; import ClamScan from 'clamscan'; -// import { ValidationException } from '@adonisjs/validator'; -// import Drive from '@ioc:Adonis/Core/Drive'; -// import drive from '#services/drive'; import drive from '@adonisjs/drive/services/main'; import path from 'path'; import { Exception } from '@adonisjs/core/exceptions'; import { MultipartFile } from '@adonisjs/core/types/bodyparser'; import * as crypto from 'crypto'; +import { pipeline } from 'node:stream/promises'; +import { createWriteStream } from 'node:fs'; +import type { Multipart } from '@adonisjs/bodyparser'; +import * as fs from 'fs'; +import { parseBytesSize, getConfigFor, getTmpPath, formatBytes } from '#app/utils/utility-functions'; + interface Dictionary { [index: string]: string; } import vine, { SimpleMessagesProvider, errors } from '@vinejs/vine'; export default class DatasetController { + /** + * Bodyparser config + */ + // config: BodyParserConfig = config.get('bodyparser'); + public async index({ auth, request, inertia }: HttpContext) { const user = (await User.find(auth.user?.id)) as User; const page = request.input('page', 1); @@ -69,8 +76,16 @@ export default class DatasetController { } datasets.orderBy(attribute, sortOrder); } else { - // users.orderBy('created_at', 'desc'); - datasets.orderBy('id', 'asc'); + // datasets.orderBy('id', 'asc'); + // Custom ordering to prioritize rejected_editor state + datasets.orderByRaw(` + CASE + WHEN server_state = 'rejected_editor' THEN 0 + WHEN server_state = 'rejected_reviewer' THEN 1 + ELSE 2 + END ASC, + id ASC + `); } // const results = await Database @@ -191,7 +206,8 @@ export default class DatasetController { .translatedLanguage({ mainLanguageField: 'language', typeField: 'type' }), }), ) - .minLength(1), + // .minLength(2) + .arrayContainsTypes({ typeA: 'main', typeB: 'translated' }), descriptions: vine .array( vine.object({ @@ -205,7 +221,8 @@ export default class DatasetController { .translatedLanguage({ mainLanguageField: 'language', typeField: 'type' }), }), ) - .minLength(1), + // .minLength(1), + .arrayContainsTypes({ typeA: 'abstract', typeB: 'translated' }), authors: vine .array( vine.object({ @@ -280,7 +297,8 @@ export default class DatasetController { .translatedLanguage({ mainLanguageField: 'language', typeField: 'type' }), }), ) - .minLength(1), + // .minLength(2) + .arrayContainsTypes({ typeA: 'main', typeB: 'translated' }), descriptions: vine .array( vine.object({ @@ -294,7 +312,8 @@ export default class DatasetController { .translatedLanguage({ mainLanguageField: 'language', typeField: 'type' }), }), ) - .minLength(1), + // .minLength(1), + .arrayContainsTypes({ typeA: 'abstract', typeB: 'translated' }), authors: vine .array( vine.object({ @@ -402,21 +421,99 @@ export default class DatasetController { } public async store({ auth, request, response, session }: HttpContext) { - // node ace make:validator CreateDataset + // At the top of the store() method, declare an array to hold temporary file paths + const uploadedTmpFiles: string[] = []; + // Aggregated limit example (adjust as needed) + const multipartConfig = getConfigFor('multipart'); + const aggregatedLimit = multipartConfig.limit ? parseBytesSize(multipartConfig.limit) : 100 * 1024 * 1024; + // const aggregatedLimit = 200 * 1024 * 1024; + let totalUploadedSize = 0; + + // // Helper function to format bytes as human-readable text + // function formatBytes(bytes: number): string { + // if (bytes === 0) return '0 Bytes'; + // const k = 1024; + // const sizes = ['Bytes', 'KB', 'MB', 'GB', 'TB']; + // const i = Math.floor(Math.log(bytes) / Math.log(k)); + // return parseFloat((bytes / Math.pow(k, i)).toFixed(2)) + ' ' + sizes[i]; + // } + // const enabledExtensions = await this.getEnabledExtensions(); + const multipart: Multipart = request.multipart; + + multipart.onFile('files', { deferValidations: true }, async (part) => { + // Attach an individual file size accumulator if needed + let fileUploadedSize = 0; + + // Simply accumulate the size in on('data') without performing the expensive check per chunk + part.on('data', (chunk) => { + // reporter(chunk); + // Increase counters using the chunk length + fileUploadedSize += chunk.length; + }); + + // After the file is completely read, update the global counter and check aggregated limit + part.on('end', () => { + totalUploadedSize += fileUploadedSize; + part.file.size = fileUploadedSize; + // Record the temporary file path + if (part.file.tmpPath) { + uploadedTmpFiles.push(part.file.tmpPath); + } + + if (totalUploadedSize > aggregatedLimit) { + // Clean up all temporary files if aggregate limit is exceeded + uploadedTmpFiles.forEach((tmpPath) => { + try { + fs.unlinkSync(tmpPath); + } catch (cleanupError) { + console.error('Error cleaning up temporary file:', cleanupError); + } + }); + const error = new errors.E_VALIDATION_ERROR({ + 'upload error': `Aggregated upload limit of ${formatBytes(aggregatedLimit)} exceeded. The total size of files being uploaded would exceed the limit.`, + }); + request.multipart.abort(error); + } + }); + + part.on('error', (error) => { + // fileUploadError = error; + request.multipart.abort(error); + }); + + // await pipeline(part, createWriteStream(filePath)); + // return { filePath }; + // Process file with error handling + try { + // Extract extension from the client file name, e.g. "Tethys 5 - Ampflwang_dataset.zip" + const ext = path.extname(part.file.clientName).replace('.', ''); + // Attach the extracted extension to the file object for later use + part.file.extname = ext; + + // part.file.sortOrder = part.file.sortOrder; + + const tmpPath = getTmpPath(multipartConfig); + (part.file as any).tmpPath = tmpPath; + + const writeStream = createWriteStream(tmpPath); + await pipeline(part, writeStream); + } catch (error) { + request.multipart.abort(new errors.E_VALIDATION_ERROR({ 'upload error': error.message })); + } + }); + try { - // Step 2 - Validate request body against the schema - // await request.validate({ schema: newDatasetSchema, messages: this.messages }); - // await request.validate(CreateDatasetValidator); - await request.validateUsing(createDatasetValidator); - // console.log({ payload }); + await multipart.process(); + // // Instead of letting an error abort the controller, check if any error occurred } catch (error) { - // Step 3 - Handle errors - // return response.badRequest(error.messages); - throw error; + // This is where you'd expect to catch any errors. + session.flash('errors', error.messages); + return response.redirect().back(); } let trx: TransactionClientContract | null = null; try { + await request.validateUsing(createDatasetValidator); trx = await db.transaction(); const user = (await User.find(auth.user?.id)) as User; @@ -425,6 +522,14 @@ export default class DatasetController { await trx.commit(); console.log('Dataset and related models created successfully'); } catch (error) { + // Clean up temporary files if validation or later steps fail + uploadedTmpFiles.forEach((tmpPath) => { + try { + fs.unlinkSync(tmpPath); + } catch (cleanupError) { + console.error('Error cleaning up temporary file:', cleanupError); + } + }); if (trx !== null) { await trx.rollback(); } @@ -437,14 +542,19 @@ export default class DatasetController { return response.redirect().toRoute('dataset.list'); // return response.redirect().back(); } - - private async createDatasetAndAssociations(user: User, request: HttpContext['request'], trx: TransactionClientContract) { + private async createDatasetAndAssociations( + user: User, + request: HttpContext['request'], + trx: TransactionClientContract, + // uploadedFiles: Array<MultipartFile>, + ) { // Create a new instance of the Dataset model: const dataset = new Dataset(); dataset.type = request.input('type'); dataset.creating_corporation = request.input('creating_corporation'); dataset.language = request.input('language'); dataset.embargo_date = request.input('embargo_date'); + dataset.project_id = request.input('project_id'); //await dataset.related('user').associate(user); // speichert schon ab // Dataset.$getRelation('user').boot(); // Dataset.$getRelation('user').setRelated(dataset, user); @@ -553,7 +663,7 @@ export default class DatasetController { newFile.fileSize = file.size; newFile.mimeType = mimeType; newFile.label = file.clientName; - newFile.sortOrder = index; + newFile.sortOrder = index + 1; newFile.visibleInFrontdoor = true; newFile.visibleInOai = true; // let path = coverImage.filePath; @@ -704,6 +814,8 @@ export default class DatasetController { 'files.array.minLength': 'At least {{ min }} file upload is required.', 'files.*.size': 'file size is to big', 'files.*.extnames': 'file extension is not supported', + + 'embargo_date.date.afterOrEqual': `Embargo date must be on or after ${dayjs().add(10, 'day').format('DD.MM.YYYY')}`, }; // public async release({ params, view }) { @@ -814,7 +926,7 @@ export default class DatasetController { // throw new GeneralException(trans('exceptions.publish.release.update_error')); } - public async edit({ request, inertia, response }: HttpContext) { + public async edit({ request, inertia, response, auth }: HttpContext) { const id = request.param('id'); const datasetQuery = Dataset.query().where('id', id); datasetQuery @@ -822,8 +934,8 @@ export default class DatasetController { .preload('descriptions', (query) => query.orderBy('id', 'asc')) .preload('coverage') .preload('licenses') - .preload('authors') - .preload('contributors') + .preload('authors', (query) => query.orderBy('pivot_sort_order', 'asc')) + .preload('contributors', (query) => query.orderBy('pivot_sort_order', 'asc')) // .preload('subjects') .preload('subjects', (builder) => { builder.orderBy('id', 'asc').withCount('datasets'); @@ -839,10 +951,9 @@ export default class DatasetController { // session.flash('errors', 'Invalid server state!'); return response .flash( - 'warning', `Invalid server state. Dataset with id ${id} cannot be edited. Datset has server state ${dataset.server_state}.`, + 'warning', ) - .redirect() .toRoute('dataset.list'); } @@ -876,15 +987,15 @@ export default class DatasetController { // const datasetHasLicenses = await dataset.related('licenses').query().pluck('id'); // const checkeds = dataset.licenses.first().id; - const doctypes = { - analysisdata: { label: 'Analysis', value: 'analysisdata' }, - measurementdata: { label: 'Measurements', value: 'measurementdata' }, - monitoring: 'Monitoring', - remotesensing: 'Remote Sensing', - gis: 'GIS', - models: 'Models', - mixedtype: 'Mixed Type', - }; + // const doctypes = { + // analysisdata: { label: 'Analysis', value: 'analysisdata' }, + // measurementdata: { label: 'Measurements', value: 'measurementdata' }, + // monitoring: 'Monitoring', + // remotesensing: 'Remote Sensing', + // gis: 'GIS', + // models: 'Models', + // mixedtype: 'Mixed Type', + // }; return inertia.render('Submitter/Dataset/Edit', { dataset, @@ -903,25 +1014,95 @@ export default class DatasetController { subjectTypes: SubjectTypes, referenceIdentifierTypes: Object.entries(ReferenceIdentifierTypes).map(([key, value]) => ({ value: key, label: value })), relationTypes: Object.entries(RelationTypes).map(([key, value]) => ({ value: key, label: value })), - doctypes, + doctypes: DatasetTypes, + can: { + edit: await auth.user?.can(['dataset-edit']), + delete: await auth.user?.can(['dataset-delete']), + }, }); } public async update({ request, response, session }: HttpContext) { - try { - // await request.validate(UpdateDatasetValidator); - await request.validateUsing(updateDatasetValidator); - } catch (error) { - // - Handle errors - // return response.badRequest(error.messages); - throw error; - // return response.badRequest(error.messages); + // Get the dataset id from the route parameter + const datasetId = request.param('id'); + // Retrieve the dataset and load its existing files + const dataset = await Dataset.findOrFail(datasetId); + await dataset.load('files'); + // Accumulate the size of the already related files + // const preExistingFileSize = dataset.files.reduce((acc, file) => acc + file.fileSize, 0); + let preExistingFileSize = 0; + for (const file of dataset.files) { + preExistingFileSize += Number(file.fileSize); } - // await request.validate(UpdateDatasetValidator); - const id = request.param('id'); + const uploadedTmpFiles: string[] = []; + // Only process multipart if the request has a multipart content type + const contentType = request.request.headers['content-type'] || ''; + if (contentType.includes('multipart/form-data')) { + const multipart: Multipart = request.multipart; + // Aggregated limit example (adjust as needed) + const multipartConfig = getConfigFor('multipart'); + const aggregatedLimit = multipartConfig.limit ? parseBytesSize(multipartConfig.limit) : 100 * 1024 * 1024; + // Initialize totalUploadedSize with the size of existing files + let totalUploadedSize = preExistingFileSize; + + multipart.onFile('files', { deferValidations: true }, async (part) => { + let fileUploadedSize = 0; + + part.on('data', (chunk) => { + fileUploadedSize += chunk.length; + }); + + part.on('end', () => { + totalUploadedSize += fileUploadedSize; + part.file.size = fileUploadedSize; + if (part.file.tmpPath) { + uploadedTmpFiles.push(part.file.tmpPath); + } + if (totalUploadedSize > aggregatedLimit) { + uploadedTmpFiles.forEach((tmpPath) => { + try { + fs.unlinkSync(tmpPath); + } catch (cleanupError) { + console.error('Error cleaning up temporary file:', cleanupError); + } + }); + const error = new errors.E_VALIDATION_ERROR({ + 'upload error': `Aggregated upload limit of ${formatBytes(aggregatedLimit)} exceeded. The total size of files being uploaded would exceed the limit.`, + }); + request.multipart.abort(error); + } + }); + + part.on('error', (error) => { + request.multipart.abort(error); + }); + + try { + const fileNameWithoutParams = part.file.clientName.split('?')[0]; + const ext = path.extname(fileNameWithoutParams).replace('.', ''); + part.file.extname = ext; + const tmpPath = getTmpPath(multipartConfig); + (part.file as any).tmpPath = tmpPath; + const writeStream = createWriteStream(tmpPath); + await pipeline(part, writeStream); + } catch (error) { + request.multipart.abort(new errors.E_VALIDATION_ERROR({ 'upload error': error.message })); + } + }); + + try { + await multipart.process(); + } catch (error) { + session.flash('errors', error.messages); + return response.redirect().back(); + } + } + + const id = request.param('id'); let trx: TransactionClientContract | null = null; try { + await request.validateUsing(updateDatasetValidator); trx = await db.transaction(); // const user = (await User.find(auth.user?.id)) as User; // await this.createDatasetAndAssociations(user, request, trx); @@ -982,22 +1163,97 @@ export default class DatasetController { } } - // await dataset.useTransaction(trx).related('subjects').sync([]); - const keywords = request.input('subjects'); - for (const keywordData of keywords) { - if (keywordData.id) { - const subject = await Subject.findOrFail(keywordData.id); - // await dataset.useTransaction(trx).related('subjects').attach([keywordData.id]); - subject.value = keywordData.value; - subject.type = keywordData.type; - subject.external_key = keywordData.external_key; - if (subject.$isDirty) { - await subject.save(); + // Process all subjects/keywords from the request + const subjects = request.input('subjects'); + for (const subjectData of subjects) { + // Case 1: Subject already exists in the database (has an ID) + if (subjectData.id) { + // Retrieve the existing subject + const existingSubject = await Subject.findOrFail(subjectData.id); + + // Update subject properties from the request data + existingSubject.value = subjectData.value; + existingSubject.type = subjectData.type; + existingSubject.external_key = subjectData.external_key; + + // Only save if there are actual changes + if (existingSubject.$isDirty) { + await existingSubject.save(); + } + + // Note: The relationship between dataset and subject is already established, + // so we don't need to attach it again + } + // Case 2: New subject being added (no ID) + else { + // Check if a subject with the same value and type already exists in the database + const subject = await Subject.firstOrNew({ value: subjectData.value, type: subjectData.type }, subjectData); + + if (subject.$isNew === true) { + // If it's a completely new subject, create and associate it with the dataset + await dataset.useTransaction(trx).related('subjects').save(subject); + } else { + // If the subject already exists, just create the relationship + await dataset.useTransaction(trx).related('subjects').attach([subject.id]); + } + } + } + + const subjectsToDelete = request.input('subjectsToDelete', []); + for (const subjectData of subjectsToDelete) { + if (subjectData.id) { + // const subject = await Subject.findOrFail(subjectData.id); + const subject = await Subject.query() + .where('id', subjectData.id) + .preload('datasets', (builder) => { + builder.orderBy('id', 'asc'); + }) + .withCount('datasets') + .firstOrFail(); + + // Check if the subject is used by multiple datasets + if (subject.$extras.datasets_count > 1) { + // If used by multiple datasets, just detach it from the current dataset + await dataset.useTransaction(trx).related('subjects').detach([subject.id]); + } else { + // If only used by this dataset, delete the subject completely + + await dataset.useTransaction(trx).related('subjects').detach([subject.id]); + await subject.useTransaction(trx).delete(); + } + } + } + + // Process references + const references = request.input('references', []); + // First, get existing references to determine which ones to update vs. create + const existingReferences = await dataset.related('references').query(); + const existingReferencesMap: Map<number, DatasetReference> = new Map(existingReferences.map((ref) => [ref.id, ref])); + + for (const referenceData of references) { + if (existingReferencesMap.has(referenceData.id) && referenceData.id) { + // Update existing reference + const reference = existingReferencesMap.get(referenceData.id); + if (reference) { + reference.merge(referenceData); + if (reference.$isDirty) { + await reference.useTransaction(trx).save(); + } } } else { - const keyword = new Subject(); - keyword.fill(keywordData); - await dataset.useTransaction(trx).related('subjects').save(keyword, false); + // Create new reference + const dataReference = new DatasetReference(); + dataReference.fill(referenceData); + await dataset.useTransaction(trx).related('references').save(dataReference); + } + } + + // Handle references to delete if provided + const referencesToDelete = request.input('referencesToDelete', []); + for (const referenceData of referencesToDelete) { + if (referenceData.id) { + const reference = await DatasetReference.findOrFail(referenceData.id); + await reference.useTransaction(trx).delete(); } } @@ -1029,9 +1285,9 @@ export default class DatasetController { // handle new uploaded files: const uploadedFiles: MultipartFile[] = request.files('files'); if (Array.isArray(uploadedFiles) && uploadedFiles.length > 0) { - for (const [index, fileData] of uploadedFiles.entries()) { + for (const [index, file] of uploadedFiles.entries()) { try { - await this.scanFileForViruses(fileData.tmpPath); //, 'gitea.lan', 3310); + await this.scanFileForViruses(file.tmpPath); //, 'gitea.lan', 3310); // await this.scanFileForViruses("/tmp/testfile.txt"); } catch (error) { // If the file is infected or there's an error scanning the file, throw a validation exception @@ -1039,29 +1295,29 @@ export default class DatasetController { } // move to disk: - const fileName = `file-${cuid()}.${fileData.extname}`; //'file-ls0jyb8xbzqtrclufu2z2e0c.pdf' + const fileName = this.generateFilename(file.extname as string); const datasetFolder = `files/${dataset.id}`; // 'files/307' const datasetFullPath = path.join(`${datasetFolder}`, fileName); - // await fileData.moveToDisk(datasetFolder, { name: fileName, overwrite: true }, 'local'); - // await fileData.move(drive.makePath(datasetFolder), { + // await file.moveToDisk(datasetFolder, { name: fileName, overwrite: true }, 'local'); + // await file.move(drive.makePath(datasetFolder), { // name: fileName, // overwrite: true, // overwrite in case of conflict // }); - await fileData.moveToDisk(datasetFullPath, 'local', { + await file.moveToDisk(datasetFullPath, 'local', { name: fileName, overwrite: true, // overwrite in case of conflict disk: 'local', }); //save to db: - const { clientFileName, sortOrder } = this.extractVariableNameAndSortOrder(fileData.clientName); - const mimeType = fileData.headers['content-type'] || 'application/octet-stream'; // Fallback to a default MIME type + const { clientFileName, sortOrder } = this.extractVariableNameAndSortOrder(file.clientName); + const mimeType = file.headers['content-type'] || 'application/octet-stream'; // Fallback to a default MIME type const newFile = await dataset .useTransaction(trx) .related('files') .create({ pathName: `${datasetFolder}/${fileName}`, - fileSize: fileData.size, + fileSize: file.size, mimeType, label: clientFileName, sortOrder: sortOrder || index, @@ -1101,16 +1357,24 @@ export default class DatasetController { await dataset.useTransaction(trx).save(); await trx.commit(); - console.log('Dataset and related models created successfully'); + console.log('Dataset has been updated successfully'); session.flash('message', 'Dataset has been updated successfully'); // return response.redirect().toRoute('user.index'); return response.redirect().toRoute('dataset.edit', [dataset.id]); } catch (error) { + // Clean up temporary files if validation or later steps fail + uploadedTmpFiles.forEach((tmpPath) => { + try { + fs.unlinkSync(tmpPath); + } catch (cleanupError) { + console.error('Error cleaning up temporary file:', cleanupError); + } + }); if (trx !== null) { await trx.rollback(); } - console.error('Failed to create dataset and related models:', error); + console.error('Failed to update dataset and related models:', error); // throw new ValidationException(true, { 'upload error': `failed to create dataset and related models. ${error}` }); throw error; } @@ -1236,6 +1500,7 @@ export default class DatasetController { } const collectionRoles = await CollectionRole.query() + .whereIn('name', ['ddc', 'ccs']) .preload('collections', (coll: Collection) => { // preloa only top level collection with noparent_id coll.whereNull('parent_id').orderBy('number', 'asc'); @@ -1275,7 +1540,7 @@ export default class DatasetController { // This should be an array of collection ids. const collections: number[] = request.input('collections', []); - // Synchronize the dataset collections using the transaction. + // Synchronize the dataset collections using the transaction. await dataset.useTransaction(trx).related('collections').sync(collections); // Commit the transaction.await trx.commit() diff --git a/app/exceptions/db_handler.ts b/app/exceptions/db_handler.ts new file mode 100644 index 0000000..868fec9 --- /dev/null +++ b/app/exceptions/db_handler.ts @@ -0,0 +1,43 @@ +// import { Exception } from '@adonisjs/core/exceptions' +import { HttpContext, ExceptionHandler } from '@adonisjs/core/http'; + +export default class DbHandlerException extends ExceptionHandler { + // constructor() { + // super(Logger) + // } + + async handle(error: any, ctx: HttpContext) { + // Check for AggregateError type + if (error.type === 'AggregateError' && error.aggregateErrors) { + const dbErrors = error.aggregateErrors.some((err: any) => err.code === 'ECONNREFUSED' && err.port === 5432); + + if (dbErrors) { + return ctx.response.status(503).json({ + status: 'error', + message: 'PostgreSQL database connection failed. Please ensure the database service is running.', + details: { + code: error.code, + type: error.type, + ports: error.aggregateErrors.map((err: any) => ({ + port: err.port, + address: err.address, + })), + }, + }); + } + } + + // Handle simple ECONNREFUSED errors + if (error.code === 'ECONNREFUSED') { + return ctx.response.status(503).json({ + status: 'error', + message: 'Database connection failed. Please ensure PostgreSQL is running.', + code: error.code, + }); + } + + return super.handle(error, ctx); + } + + static status = 500; +} diff --git a/app/exceptions/handler.ts b/app/exceptions/handler.ts index d8f1c63..a460c3d 100644 --- a/app/exceptions/handler.ts +++ b/app/exceptions/handler.ts @@ -46,6 +46,7 @@ export default class HttpExceptionHandler extends ExceptionHandler { // return view.render('./errors/server-error', { error }); // }, // }; + protected statusPages: Record<StatusPageRange, StatusPageRenderer> = { '404': (error, { inertia }) => { return inertia.render('Errors/ServerError', { @@ -58,9 +59,47 @@ export default class HttpExceptionHandler extends ExceptionHandler { return inertia.render('Errors/ServerError', { error: error.message, code: error.status, - }); + }); + }, + // '500': (error, { inertia }) => { + // return inertia.render('Errors/postgres_error', { + // status: 'error', + // message: 'PostgreSQL database connection failed. Please ensure the database service is running.', + // details: { + // code: error.code, + // type: error.status, + // ports: error.errors.map((err: any) => ({ + // port: err.port, + // address: err.address, + // })), + // }, + // }); + // }, + '500..599': (error, { inertia }) => { + if (error.code === 'ECONNREFUSED') { + const dbErrors = error.errors.some((err: any) => err.code === 'ECONNREFUSED' && err.port === 5432); + + if (dbErrors) { + return inertia.render('Errors/postgres_error', { + status: 'error', + message: 'PostgreSQL database connection failed. Please ensure the database service is running.', + details: { + code: error.code, + type: error.status, + ports: error.errors.map((err: any) => ({ + port: err.port, + address: err.address, + })), + }, + }); + } + } else { + return inertia.render('Errors/ServerError', { + error: error.message, + code: error.status, + }); + } }, - '500..599': (error, { inertia }) => inertia.render('Errors/ServerError', { error: error.message, code: error.status }), }; // constructor() { @@ -68,7 +107,7 @@ export default class HttpExceptionHandler extends ExceptionHandler { // } public async handle(error: any, ctx: HttpContext) { - const { response, request, session } = ctx; + const { response, request, session, inertia } = ctx; /** * Handle failed authentication attempt @@ -82,6 +121,47 @@ export default class HttpExceptionHandler extends ExceptionHandler { // return response.redirect('/dashboard'); // } + // Handle Axios errors + if (error.code === 'ECONNREFUSED') { + const dbErrors = error.errors.some((err: any) => err.code === 'ECONNREFUSED' && err.port === 5432); + + if (dbErrors) { + // return ctx.response.status(503).json({ + // status: 'error', + // message: 'PostgreSQL database connection failed. Please ensure the database service is running.', + // details: { + // code: error.code, + // type: error.status, + // ports: error.errors.map((err: any) => ({ + // port: err.port, + // address: err.address, + // })), + // }, + // }); + // return inertia.render('Errors/postgres_error', { + // status: 'error', + // message: 'PostgreSQL database connection failed. Please ensure the database service is running.', + // details: { + // code: error.code, + // type: error.status, + // ports: error.errors.map((err: any) => ({ + // port: err.port, + // address: err.address, + // })), + // }, + // }); + } + } + + // Handle simple ECONNREFUSED errors + // if (error.code === 'ECONNREFUSED') { + // return ctx.response.status(503).json({ + // status: 'error', + // message: 'Database connection failed. Please ensure PostgreSQL is running.', + // code: error.code, + // }); + // } + // https://github.com/inertiajs/inertia-laravel/issues/56 // let test = response.getStatus(); //200 // let header = request.header('X-Inertia'); // true @@ -98,12 +178,21 @@ export default class HttpExceptionHandler extends ExceptionHandler { // ->toResponse($request) // ->setStatusCode($response->status()); } + + // Handle simple ECONNREFUSED errors + // if (error.code === 'ECONNREFUSED') { + // return ctx.response.status(503).json({ + // status: 'error', + // message: 'Database connection failed. Please ensure PostgreSQL is running.', + // code: error.code, + // }); + // } // Dynamically change the error templates based on the absence of X-Inertia header // if (!ctx.request.header('X-Inertia')) { // this.statusPages = { - // '401..403': (error, { view }) => view.render('./errors/unauthorized', { error }), - // '404': (error, { view }) => view.render('./errors/not-found', { error }), - // '500..599': (error, { view }) => view.render('./errors/server-error', { error }), + // '401..403': (error, { inertia }) => inertia.render('Errors/ServerError', { error: error.message, code: error.status }), + // '404': (error, { inertia }) => inertia.render('Errors/ServerError', { error: error.message, code: error.status }), + // '500..599': (error, { inertia }) => inertia.render('Errors/ServerError', { error: error.message, code: error.status }), // }; // } diff --git a/app/models/person.ts b/app/models/person.ts index 4e6b60b..cdc612d 100644 --- a/app/models/person.ts +++ b/app/models/person.ts @@ -3,7 +3,7 @@ import { DateTime } from 'luxon'; import dayjs from 'dayjs'; import Dataset from './dataset.js'; import BaseModel from './base_model.js'; -import type { ManyToMany } from "@adonisjs/lucid/types/relations"; +import type { ManyToMany } from '@adonisjs/lucid/types/relations'; export default class Person extends BaseModel { public static namingStrategy = new SnakeCaseNamingStrategy(); @@ -64,9 +64,8 @@ export default class Person extends BaseModel { // return '2023-03-21 08:45:00'; // } - @computed({ - serializeAs: 'dataset_count', + serializeAs: 'dataset_count', }) public get datasetCount() { const stock = this.$extras.datasets_count; //my pivot column name was "stock" @@ -79,6 +78,16 @@ export default class Person extends BaseModel { return contributor_type; } + @computed({ serializeAs: 'allow_email_contact' }) + public get allowEmailContact() { + // If the datasets relation is missing or empty, return false instead of null. + if (!this.datasets || this.datasets.length === 0) { + return false; + } + // Otherwise return the pivot attribute from the first related dataset. + return this.datasets[0].$extras?.pivot_allow_email_contact; + } + @manyToMany(() => Dataset, { pivotForeignKey: 'person_id', pivotRelatedForeignKey: 'document_id', diff --git a/app/models/types.ts b/app/models/types.ts new file mode 100644 index 0000000..1fda1e1 --- /dev/null +++ b/app/models/types.ts @@ -0,0 +1,57 @@ +/** + * Qs module config + */ +type QueryStringConfig = { + depth?: number + allowPrototypes?: boolean + plainObjects?: boolean + parameterLimit?: number + arrayLimit?: number + ignoreQueryPrefix?: boolean + delimiter?: RegExp | string + allowDots?: boolean + charset?: 'utf-8' | 'iso-8859-1' | undefined + charsetSentinel?: boolean + interpretNumericEntities?: boolean + parseArrays?: boolean + comma?: boolean + } +/** + * Base config used by all types + */ +type BodyParserBaseConfig = { + encoding: string + limit: string | number + types: string[] + } + + /** + * Body parser config for parsing JSON requests + */ + export type BodyParserJSONConfig = BodyParserBaseConfig & { + strict: boolean + convertEmptyStringsToNull: boolean + } + + /** + * Parser config for parsing form data + */ + export type BodyParserFormConfig = BodyParserBaseConfig & { + queryString: QueryStringConfig + convertEmptyStringsToNull: boolean + } + + /** + * Parser config for parsing raw body (untouched) + */ + export type BodyParserRawConfig = BodyParserBaseConfig +/** + * Body parser config for all supported form types + */ +export type BodyParserConfig = { + allowedMethods: string[] + json: BodyParserJSONConfig + form: BodyParserFormConfig + raw: BodyParserRawConfig + multipart: BodyParserMultipartConfig + } \ No newline at end of file diff --git a/app/utils/utility-functions.ts b/app/utils/utility-functions.ts index 6afb2a0..a281f59 100644 --- a/app/utils/utility-functions.ts +++ b/app/utils/utility-functions.ts @@ -1,3 +1,16 @@ +import { join, isAbsolute } from 'node:path'; +import type { BodyParserConfig } from '#models/types'; +import { createId } from '@paralleldrive/cuid2'; +import { tmpdir } from 'node:os'; +import config from '@adonisjs/core/services/config'; +import Dataset from '#models/dataset'; +import { TransactionClientContract } from '@adonisjs/lucid/types/database'; +import Person from '#models/person'; + +interface Dictionary { + [index: string]: string; +} + export function sum(a: number, b: number): number { return a + b; } @@ -24,3 +37,88 @@ export function preg_match(regex: RegExp, str: string) { const result: boolean = regex.test(str); return result; } + +/** + * Returns the tmp path for storing the files temporarly + */ +export function getTmpPath(config: BodyParserConfig['multipart']): string { + if (typeof config.tmpFileName === 'function') { + const tmpPath = config.tmpFileName(); + return isAbsolute(tmpPath) ? tmpPath : join(tmpdir(), tmpPath); + } + + return join(tmpdir(), createId()); +} +/** + * Returns config for a given type + */ +export function getConfigFor<K extends keyof BodyParserConfig>(type: K): BodyParserConfig[K] { + const bodyParserConfig: BodyParserConfig = config.get('bodyparser'); + const configType = bodyParserConfig[type]; + return configType; +} + +export function parseBytesSize(size: string): number { + const units: Record<string, number> = { + kb: 1024, + mb: 1024 * 1024, + gb: 1024 * 1024 * 1024, + tb: 1024 * 1024 * 1024 * 1024, + }; + + const match = size.match(/^(\d+)(kb|mb|gb|tb)$/i); // Regex to match size format + + if (!match) { + throw new Error('Invalid size format'); + } + + const [, value, unit] = match; + return parseInt(value) * units[unit.toLowerCase()]; +} + +// Helper function to format bytes as human-readable text + +export function formatBytes(bytes: number): string { + if (bytes === 0) return '0 Bytes'; + const k = 1024; + const sizes = ['Bytes', 'KB', 'MB', 'GB', 'TB']; + const i = Math.floor(Math.log(bytes) / Math.log(k)); + return parseFloat((bytes / Math.pow(k, i)).toFixed(2)) + ' ' + sizes[i]; +} + +export async function savePersons(dataset: Dataset, persons: any[], role: string, trx: TransactionClientContract) { + for (const [key, person] of persons.entries()) { + const pivotData = { + role: role, + sort_order: key + 1, + allow_email_contact: false, + ...extractPivotAttributes(person), // Merge pivot attributes here + }; + + if (person.id !== undefined) { + await dataset + .useTransaction(trx) + .related('persons') + .attach({ + [person.id]: pivotData, + }); + } else { + const dataPerson = new Person(); + dataPerson.fill(person); + await dataset.useTransaction(trx).related('persons').save(dataPerson, false, pivotData); + } + } +} + +// Helper function to extract pivot attributes from a person object +function extractPivotAttributes(person: any) { + const pivotAttributes: Dictionary = {}; + for (const key in person) { + if (key.startsWith('pivot_')) { + // pivotAttributes[key] = person[key]; + const cleanKey = key.replace('pivot_', ''); // Remove 'pivot_' prefix + pivotAttributes[cleanKey] = person[key]; + } + } + return pivotAttributes; +} diff --git a/app/validators/dataset.ts b/app/validators/dataset.ts index cdd1fbf..5417463 100644 --- a/app/validators/dataset.ts +++ b/app/validators/dataset.ts @@ -40,7 +40,8 @@ export const createDatasetValidator = vine.compile( .translatedLanguage({ mainLanguageField: 'language', typeField: 'type' }), }), ) - .minLength(1), + // .minLength(2) + .arrayContainsTypes({ typeA: 'main', typeB: 'translated' }), descriptions: vine .array( vine.object({ @@ -54,7 +55,8 @@ export const createDatasetValidator = vine.compile( .translatedLanguage({ mainLanguageField: 'language', typeField: 'type' }), }), ) - .minLength(1), + // .minLength(1), + .arrayContainsTypes({ typeA: 'abstract', typeB: 'translated' }), authors: vine .array( vine.object({ @@ -156,8 +158,7 @@ export const createDatasetValidator = vine.compile( .fileScan({ removeInfected: true }), ) .minLength(1), - }), -); + }),); /** * Validates the dataset's update action @@ -187,7 +188,8 @@ export const updateDatasetValidator = vine.compile( .translatedLanguage({ mainLanguageField: 'language', typeField: 'type' }), }), ) - .minLength(1), + // .minLength(2) + .arrayContainsTypes({ typeA: 'main', typeB: 'translated' }), descriptions: vine .array( vine.object({ @@ -201,7 +203,7 @@ export const updateDatasetValidator = vine.compile( .translatedLanguage({ mainLanguageField: 'language', typeField: 'type' }), }), ) - .minLength(1), + .arrayContainsTypes({ typeA: 'abstract', typeB: 'translated' }), authors: vine .array( vine.object({ @@ -312,12 +314,137 @@ export const updateDatasetValidator = vine.compile( }), ); -// files: schema.array([rules.minLength(1)]).members( -// schema.file({ -// size: '512mb', -// extnames: ['jpg', 'gif', 'png', 'tif', 'pdf', 'zip', 'fgb', 'nc', 'qml', 'ovr', 'gpkg', 'gml', 'gpx', 'kml', 'kmz', 'json'], -// }), -// ), +export const updateEditorDatasetValidator = vine.compile( + vine.object({ + // first step + language: vine + .string() + .trim() + .regex(/^[a-zA-Z0-9]+$/), + licenses: vine.array(vine.number()).minLength(1), // define at least one license for the new dataset + rights: vine.string().in(['true']), + // second step + type: vine.string().trim().minLength(3).maxLength(255), + creating_corporation: vine.string().trim().minLength(3).maxLength(255), + titles: vine + .array( + vine.object({ + value: vine.string().trim().minLength(3).maxLength(255), + type: vine.enum(Object.values(TitleTypes)), + language: vine + .string() + .trim() + .minLength(2) + .maxLength(255) + .translatedLanguage({ mainLanguageField: 'language', typeField: 'type' }), + }), + ) + // .minLength(2) + .arrayContainsTypes({ typeA: 'main', typeB: 'translated' }), + descriptions: vine + .array( + vine.object({ + value: vine.string().trim().minLength(3).maxLength(2500), + type: vine.enum(Object.values(DescriptionTypes)), + language: vine + .string() + .trim() + .minLength(2) + .maxLength(255) + .translatedLanguage({ mainLanguageField: 'language', typeField: 'type' }), + }), + ) + .arrayContainsTypes({ typeA: 'abstract', typeB: 'translated' }), + authors: vine + .array( + vine.object({ + email: vine + .string() + .trim() + .maxLength(255) + .email() + .normalizeEmail() + .isUniquePerson({ table: 'persons', column: 'email', idField: 'id' }), + first_name: vine.string().trim().minLength(3).maxLength(255), + last_name: vine.string().trim().minLength(3).maxLength(255), + }), + ) + .minLength(1) + .distinct('email'), + contributors: vine + .array( + vine.object({ + email: vine + .string() + .trim() + .maxLength(255) + .email() + .normalizeEmail() + .isUniquePerson({ table: 'persons', column: 'email', idField: 'id' }), + first_name: vine.string().trim().minLength(3).maxLength(255), + last_name: vine.string().trim().minLength(3).maxLength(255), + pivot_contributor_type: vine.enum(Object.keys(ContributorTypes)), + }), + ) + .distinct('email') + .optional(), + // third step + project_id: vine.number().optional(), + // embargo_date: schema.date.optional({ format: 'yyyy-MM-dd' }, [rules.after(10, 'days')]), + embargo_date: vine + .date({ + formats: ['YYYY-MM-DD'], + }) + .afterOrEqual((_field) => { + return dayjs().add(10, 'day').format('YYYY-MM-DD'); + }) + .optional(), + coverage: vine.object({ + x_min: vine.number(), + x_max: vine.number(), + y_min: vine.number(), + y_max: vine.number(), + elevation_absolut: vine.number().positive().optional(), + elevation_min: vine.number().positive().optional().requiredIfExists('elevation_max'), + elevation_max: vine.number().positive().optional().requiredIfExists('elevation_min'), + // type: vine.enum(Object.values(DescriptionTypes)), + depth_absolut: vine.number().negative().optional(), + depth_min: vine.number().negative().optional().requiredIfExists('depth_max'), + depth_max: vine.number().negative().optional().requiredIfExists('depth_min'), + time_abolute: vine.date({ formats: { utc: true } }).optional(), + time_min: vine + .date({ formats: { utc: true } }) + .beforeField('time_max') + .optional() + .requiredIfExists('time_max'), + time_max: vine + .date({ formats: { utc: true } }) + .afterField('time_min') + .optional() + .requiredIfExists('time_min'), + }), + references: vine + .array( + vine.object({ + value: vine.string().trim().minLength(3).maxLength(255).validateReference({ typeField: 'type' }), + type: vine.enum(Object.values(ReferenceIdentifierTypes)), + relation: vine.enum(Object.values(RelationTypes)), + label: vine.string().trim().minLength(2).maxLength(255), + }), + ) + .optional(), + subjects: vine + .array( + vine.object({ + value: vine.string().trim().minLength(3).maxLength(255), + // pivot_contributor_type: vine.enum(Object.keys(ContributorTypes)), + language: vine.string().trim().minLength(2).maxLength(255), + }), + ) + .minLength(3) + .distinct('value'), + }), +); let messagesProvider = new SimpleMessagesProvider({ 'minLength': '{{ field }} must be at least {{ min }} characters long', @@ -369,8 +496,10 @@ let messagesProvider = new SimpleMessagesProvider({ 'files.array.minLength': 'At least {{ min }} file upload is required.', 'files.*.size': 'file size is to big', 'files.*.extnames': 'file extension is not supported', + 'embargo_date.date.afterOrEqual': `Embargo date must be on or after ${dayjs().add(10, 'day').format('DD.MM.YYYY')}`, }); createDatasetValidator.messagesProvider = messagesProvider; updateDatasetValidator.messagesProvider = messagesProvider; +updateEditorDatasetValidator.messagesProvider = messagesProvider; // export default createDatasetValidator; diff --git a/app/validators/user.ts b/app/validators/user.ts index c87d467..b7bbd70 100644 --- a/app/validators/user.ts +++ b/app/validators/user.ts @@ -16,7 +16,7 @@ export const createUserValidator = vine.compile( first_name: vine.string().trim().minLength(3).maxLength(255), last_name: vine.string().trim().minLength(3).maxLength(255), email: vine.string().maxLength(255).email().normalizeEmail().isUnique({ table: 'accounts', column: 'email' }), - password: vine.string().confirmed().trim().minLength(3).maxLength(60), + new_password: vine.string().confirmed({ confirmationField: 'password_confirmation' }).trim().minLength(3).maxLength(60), roles: vine.array(vine.number()).minLength(1), // define at least one role for the new user }), ); @@ -42,7 +42,7 @@ export const updateUserValidator = vine.withMetaData<{ objId: number }>().compil .email() .normalizeEmail() .isUnique({ table: 'accounts', column: 'email', whereNot: (field) => field.meta.objId }), - password: vine.string().confirmed().trim().minLength(3).maxLength(60).optional(), + new_password: vine.string().confirmed({ confirmationField: 'password_confirmation' }).trim().minLength(3).maxLength(60).optional(), roles: vine.array(vine.number()).minLength(1), // define at least one role for the new user }), ); diff --git a/config/bodyparser.ts b/config/bodyparser.ts index efc7dbb..b7c7d35 100644 --- a/config/bodyparser.ts +++ b/config/bodyparser.ts @@ -128,7 +128,7 @@ allowedMethods: ['POST', 'PUT', 'PATCH', 'DELETE'], | projects/:id/file | ``` */ - processManually: [], + processManually: ['/submitter/dataset/submit', '/submitter/dataset/:id/update'], /* |-------------------------------------------------------------------------- @@ -185,8 +185,8 @@ allowedMethods: ['POST', 'PUT', 'PATCH', 'DELETE'], | and fields data. | */ - // limit: '20mb', - limit: env.get('UPLOAD_LIMIT', '513mb'), + limit: '513mb', + //limit: env.get('UPLOAD_LIMIT', '513mb'), /* |-------------------------------------------------------------------------- diff --git a/contracts/enums.ts b/contracts/enums.ts index 68ec4d9..5772570 100644 --- a/contracts/enums.ts +++ b/contracts/enums.ts @@ -21,6 +21,7 @@ export enum ServerStates { rejected_reviewer = 'rejected_reviewer', rejected_editor = 'rejected_editor', reviewed = 'reviewed', + rejected_to_reviewer = 'rejected_to_reviewer', } // for table dataset_titles diff --git a/database/factories/create_collections_data_ccs.sql b/database/factories/create_collections_data_ccs.sql new file mode 100644 index 0000000..e6b14df --- /dev/null +++ b/database/factories/create_collections_data_ccs.sql @@ -0,0 +1,1472 @@ +-- ACM Computing Classification System (CCS) — a widely used system for classifying academic literature in computer science and related disciplines. +/* The main classes are: see number at db +A. General Literature +B. Hardware +C. Computer Systems Organization +D. Software +E. Data +F. Theory of Computation +G. Mathematics of Computing +H. Information Systems +I. Computing Methodologies +J. Computer Applications +K. Computing Milieux + +These classes help in organizing research papers, indexing databases, and guiding publication categorization +*/ +INSERT INTO collections (id, role_id, number, name, oai_subset, left_id, right_id, parent_id, visible, visible_publish) VALUES +(1030,3,'A.','General Literature','A.',2,17,NULL,1,1), +(1031,3,'B.','Hardware','B.',18,379,NULL,1,1), +(1032,3,'C.','Computer Systems Organization','C.',380,567,NULL,1,1), +(1033,3,'D.','Software','D.',568,1035,NULL,1,1), +(1034,3,'E.','Data','E.',1036,1101,NULL,1,1), +(1035,3,'F.','Theory of Computation','F.',1102,1291,NULL,1,1), +(1036,3,'G.','Mathematics of Computing','G.',1292,1587,NULL,1,1), +(1037,3,'H.','Information Systems','H.',1588,1919,NULL,1,1), +(1038,3,'I.','Computing Methodologies','I.',1920,2537,NULL,1,1), +(1039,3,'J.','Computer Applications','J.',2538,2637,NULL,1,1), +(1040,3,'K.','Computing Milieux','K.',2638,2911,NULL,1,1), +(1041,3,'A.0','GENERAL','A.0',3,10,1030,1,1), +(1042,3,'A.1','INTRODUCTORY AND SURVEY','A.1',11,12,1030,1,1), +(1043,3,'A.2','REFERENCE (e.g., dictionaries, encyclopedias, glossaries)','A.2',13,14,1030,1,1), +(1044,3,'A.m','MISCELLANEOUS','A.m',15,16,1030,1,1), +(1045,3,'B.0','GENERAL','B.0',19,20,1031,1,1), +(1046,3,'B.1','CONTROL STRUCTURES AND MICROPROGRAMMING (D.3.2)','B.1',21,76,1031,1,1), +(1047,3,'B.2','ARITHMETIC AND LOGIC STRUCTURES','B.2',77,114,1031,1,1), +(1048,3,'B.3','MEMORY STRUCTURES','B.3',115,164,1031,1,1), +(1049,3,'B.4','INPUT/OUTPUT AND DATA COMMUNICATIONS','B.4',165,226,1031,1,1), +(1050,3,'B.5','REGISTER-TRANSFER-LEVEL IMPLEMENTATION','B.5',227,268,1031,1,1), +(1051,3,'B.6','LOGIC DESIGN','B.6',269,316,1031,1,1), +(1052,3,'B.7','INTEGRATED CIRCUITS','B.7',317,364,1031,1,1), +(1053,3,'B.8','PERFORMANCE AND RELIABILITY (C.4) (NEW)','B.8',365,374,1031,1,1), +(1054,3,'B.m','MISCELLANEOUS','B.m',375,378,1031,1,1), +(1055,3,'C.0','GENERAL','C.0',381,382,1032,1,1), +(1056,3,'C.1','PROCESSOR ARCHITECTURES','C.1',383,450,1032,1,1), +(1057,3,'C.2','COMPUTER-COMMUNICATION NETWORKS','C.2',451,534,1032,1,1), +(1058,3,'C.3','SPECIAL-PURPOSE AND APPLICATION-BASED SYSTEMS (J.7)','C.3',535,536,1032,1,1), +(1059,3,'C.4','PERFORMANCE OF SYSTEMS','C.4',537,538,1032,1,1), +(1060,3,'C.5','COMPUTER SYSTEM IMPLEMENTATION','C.5',539,564,1032,1,1), +(1061,3,'C.m','MISCELLANEOUS','C.m',565,566,1032,1,1), +(1062,3,'D.0','GENERAL','D.0',569,570,1033,1,1), +(1063,3,'D.1','PROGRAMMING TECHNIQUES (E)','D.1',571,594,1033,1,1), +(1064,3,'D.2','SOFTWARE ENGINEERING (K.6.3)','D.2',595,796,1033,1,1), +(1065,3,'D.3','PROGRAMMING LANGUAGES','D.3',797,900,1033,1,1), +(1066,3,'D.4','OPERATING SYSTEMS (C)','D.4',901,1030,1033,1,1), +(1067,3,'D.m','MISCELLANEOUS','D.m',1031,1034,1033,1,1), +(1068,3,'E.0','GENERAL','E.0',1037,1038,1034,1,1), +(1069,3,'E.1','DATA STRUCTURES','E.1',1039,1054,1034,1,1), +(1070,3,'E.2','DATA STORAGE REPRESENTATIONS','E.2',1055,1068,1034,1,1), +(1071,3,'E.3','DATA ENCRYPTION','E.3',1069,1078,1034,1,1), +(1072,3,'E.4','CODING AND INFORMATION THEORY (H.1.1)','E.4',1079,1088,1034,1,1), +(1073,3,'E.5','FILES (D.4.3, F.2.2, H.2)','E.5',1089,1098,1034,1,1), +(1074,3,'E.m','MISCELLANEOUS','E.m',1099,1100,1034,1,1), +(1075,3,'F.0','GENERAL','F.0',1103,1104,1035,1,1), +(1076,3,'F.1','COMPUTATION BY ABSTRACT DEVICES','F.1',1105,1152,1035,1,1), +(1077,3,'F.2','ANALYSIS OF ALGORITHMS AND PROBLEM COMPLEXITY (B.6-7, F.1.3)','F.2',1153,1188,1035,1,1), +(1078,3,'F.3','LOGICS AND MEANINGS OF PROGRAMS','F.3',1189,1234,1035,1,1), +(1079,3,'F.4','MATHEMATICAL LOGIC AND FORMAL LANGUAGES','F.4',1235,1288,1035,1,1), +(1080,3,'F.m','MISCELLANEOUS','F.m',1289,1290,1035,1,1), +(1081,3,'G.0','GENERAL','G.0',1293,1294,1036,1,1), +(1082,3,'G.1','NUMERICAL ANALYSIS','G.1',1295,1490,1036,1,1), +(1083,3,'G.2','DISCRETE MATHEMATICS','G.2',1491,1524,1036,1,1), +(1084,3,'G.3','PROBABILITY AND STATISTICS','G.3',1525,1562,1036,1,1), +(1085,3,'G.4','MATHEMATICAL SOFTWARE','G.4',1563,1582,1036,1,1), +(1086,3,'G.m','MISCELLANEOUS','G.m',1583,1586,1036,1,1), +(1087,3,'H.0','GENERAL','H.0',1589,1590,1037,1,1), +(1088,3,'H.1','MODELS AND PRINCIPLES','H.1',1591,1612,1037,1,1), +(1089,3,'H.2','DATABASE MANAGEMENT (E.5)','H.2',1613,1700,1037,1,1), +(1090,3,'H.3','INFORMATION STORAGE AND RETRIEVAL','H.3',1701,1778,1037,1,1), +(1091,3,'H.4','INFORMATION SYSTEMS APPLICATIONS','H.4',1779,1818,1037,1,1), +(1092,3,'H.5','INFORMATION INTERFACES AND PRESENTATION (e.g., HCI) (I.7)','H.5',1819,1916,1037,1,1), +(1093,3,'H.m','MISCELLANEOUS','H.m',1917,1918,1037,1,1), +(1094,3,'I.0','GENERAL','I.0',1921,1922,1038,1,1), +(1095,3,'I.1','SYMBOLIC AND ALGEBRAIC MANIPULATION (REVISED)','I.1',1923,1956,1038,1,1), +(1096,3,'I.2','ARTIFICIAL INTELLIGENCE','I.2',1957,2132,1038,1,1), +(1097,3,'I.3','COMPUTER GRAPHICS','I.3',2133,2252,1038,1,1), +(1098,3,'I.4','IMAGE PROCESSING AND COMPUTER VISION (REVISED)','I.4',2253,2382,1038,1,1), +(1099,3,'I.5','PATTERN RECOGNITION','I.5',2383,2432,1038,1,1), +(1100,3,'I.6','SIMULATION AND MODELING (G.3)','I.6',2433,2482,1038,1,1), +(1101,3,'I.7','DOCUMENT AND TEXT PROCESSING (H.4-5) (REVISED)','I.7',2483,2534,1038,1,1), +(1102,3,'I.m','MISCELLANEOUS','I.m',2535,2536,1038,1,1), +(1103,3,'J.0','GENERAL','J.0',2539,2540,1039,1,1), +(1104,3,'J.1','ADMINISTRATIVE DATA PROCESSING','J.1',2541,2558,1039,1,1), +(1105,3,'J.2','PHYSICAL SCIENCES AND ENGINEERING','J.2',2559,2578,1039,1,1), +(1106,3,'J.3','LIFE AND MEDICAL SCIENCES','J.3',2579,2586,1039,1,1), +(1107,3,'J.4','SOCIAL AND BEHAVIORAL SCIENCES','J.4',2587,2594,1039,1,1), +(1108,3,'J.5','ARTS AND HUMANITIES','J.5',2595,2612,1039,1,1), +(1109,3,'J.6','COMPUTER-AIDED ENGINEERING','J.6',2613,2618,1039,1,1), +(1110,3,'J.7','COMPUTERS IN OTHER SYSTEMS (C.3)','J.7',2619,2634,1039,1,1), +(1111,3,'J.m','MISCELLANEOUS','J.m',2635,2636,1039,1,1), +(1112,3,'K.0','GENERAL','K.0',2639,2640,1040,1,1), +(1113,3,'K.1','THE COMPUTER INDUSTRY','K.1',2641,2650,1040,1,1), +(1114,3,'K.2','HISTORY OF COMPUTING','K.2',2651,2662,1040,1,1), +(1115,3,'K.3','COMPUTERS AND EDUCATION','K.3',2663,2696,1040,1,1), +(1116,3,'K.4','COMPUTERS AND SOCIETY','K.4',2697,2756,1040,1,1), +(1117,3,'K.5','LEGAL ASPECTS OF COMPUTING','K.5',2757,2786,1040,1,1), +(1118,3,'K.6','MANAGEMENT OF COMPUTING AND INFORMATION SYSTEMS','K.6',2787,2856,1040,1,1), +(1119,3,'K.7','THE COMPUTING PROFESSION','K.7',2857,2880,1040,1,1), +(1120,3,'K.8','PERSONAL COMPUTING','K.8',2881,2908,1040,1,1), +(1121,3,'K.m','MISCELLANEOUS','K.m',2909,2910,1040,1,1), +(1122,3,NULL,'Biographies/autobiographies',NULL,4,5,1041,1,1), +(1123,3,NULL,'Conference proceedings',NULL,6,7,1041,1,1), +(1124,3,NULL,'General literary works (e.g., fiction, plays)',NULL,8,9,1041,1,1), +(1125,3,'B.1.0','General','B.1.0',22,23,1046,1,1), +(1126,3,'B.1.1','Control Design Styles','B.1.1',24,31,1046,1,1), +(1127,3,NULL,'Hardwired control**',NULL,25,26,1126,1,1), +(1128,3,NULL,'Microprogrammed logic arrays**',NULL,27,28,1126,1,1), +(1129,3,NULL,'Writable control store**',NULL,29,30,1126,1,1), +(1130,3,'B.1.2','Control Structure Performance Analysis and Design Aids','B.1.2',32,39,1046,1,1), +(1131,3,NULL,'Automatic synthesis**',NULL,33,34,1130,1,1), +(1132,3,NULL,'Formal models**',NULL,35,36,1130,1,1), +(1133,3,NULL,'Simulation**',NULL,37,38,1130,1,1), +(1134,3,'B.1.3','Control Structure Reliability, Testing, and Fault-Tolerance** (B.8)','B.1.3',40,49,1046,1,1), +(1135,3,NULL,'Diagnostics**',NULL,41,42,1134,1,1), +(1136,3,NULL,'Error-checking**',NULL,43,44,1134,1,1), +(1137,3,NULL,'Redundant design**',NULL,45,46,1134,1,1), +(1138,3,NULL,'Test generation**',NULL,47,48,1134,1,1), +(1139,3,'B.1.4','Microprogram Design Aids (D.2.2, D.2.4, D.3.2, D.3.4)','B.1.4',50,61,1046,1,1), +(1140,3,NULL,'Firmware engineering**',NULL,51,52,1139,1,1), +(1141,3,NULL,'Languages and compilers',NULL,53,54,1139,1,1), +(1142,3,NULL,'Machine-independent microcode generation**',NULL,55,56,1139,1,1), +(1143,3,NULL,'Optimization',NULL,57,58,1139,1,1), +(1144,3,NULL,'Verification**',NULL,59,60,1139,1,1), +(1145,3,'B.1.5','Microcode Applications','B.1.5',62,73,1046,1,1), +(1146,3,NULL,'Direct data manipulation**',NULL,63,64,1145,1,1), +(1147,3,NULL,'Firmware support of operating systems/instruction sets**',NULL,65,66,1145,1,1), +(1148,3,NULL,'Instruction set interpretation',NULL,67,68,1145,1,1), +(1149,3,NULL,'Peripheral control**',NULL,69,70,1145,1,1), +(1150,3,NULL,'Special-purpose**',NULL,71,72,1145,1,1), +(1151,3,'B.1.m','Miscellaneous','B.1.m',74,75,1046,1,1), +(1152,3,'B.2.0','General','B.2.0',78,79,1047,1,1), +(1153,3,'B.2.1','Design Styles (C.1.1-2)','B.2.1',80,87,1047,1,1), +(1154,3,NULL,'Calculator**',NULL,81,82,1153,1,1), +(1155,3,NULL,'Parallel',NULL,83,84,1153,1,1), +(1156,3,NULL,'Pipeline',NULL,85,86,1153,1,1), +(1157,3,'B.2.2','Performance Analysis and Design Aids** (B.8)','B.2.2',88,95,1047,1,1), +(1158,3,NULL,'Simulation**',NULL,89,90,1157,1,1), +(1159,3,NULL,'Verification**',NULL,91,92,1157,1,1), +(1160,3,NULL,'Worst-case analysis**',NULL,93,94,1157,1,1), +(1161,3,'B.2.3','Reliability, Testing, and Fault-Tolerance** (B.8)','B.2.3',96,105,1047,1,1), +(1162,3,NULL,'Diagnostics**',NULL,97,98,1161,1,1), +(1163,3,NULL,'Error-checking**',NULL,99,100,1161,1,1), +(1164,3,NULL,'Redundant design**',NULL,101,102,1161,1,1), +(1165,3,NULL,'Test generation**',NULL,103,104,1161,1,1), +(1166,3,'B.2.4','High-Speed Arithmetic (NEW)','B.2.4',106,111,1047,1,1), +(1167,3,NULL,'Algorithms (NEW)',NULL,107,108,1166,1,1), +(1168,3,NULL,'Cost/performance (NEW)',NULL,109,110,1166,1,1), +(1169,3,'B.2.m','Miscellaneous','B.2.m',112,113,1047,1,1), +(1170,3,'B.3.0','General','B.3.0',116,117,1048,1,1), +(1171,3,'B.3.1','Semiconductor Memories (NEW) (B.7.1)','B.3.1',118,125,1048,1,1), +(1172,3,NULL,'Dynamic memory (DRAM) (NEW)',NULL,119,120,1171,1,1), +(1173,3,NULL,'Read-only memory (ROM) (NEW)',NULL,121,122,1171,1,1), +(1174,3,NULL,'Static memory (SRAM) (NEW)',NULL,123,124,1171,1,1), +(1175,3,'B.3.2','Design Styles (D.4.2)','B.3.2',126,143,1048,1,1), +(1176,3,NULL,'Associative memories',NULL,127,128,1175,1,1), +(1177,3,NULL,'Cache memories',NULL,129,130,1175,1,1), +(1178,3,NULL,'Interleaved memories**',NULL,131,132,1175,1,1), +(1179,3,NULL,'Mass storage (e.g., magnetic, optical, RAID) (REVISED)',NULL,133,134,1175,1,1), +(1180,3,NULL,'Primary memory',NULL,135,136,1175,1,1), +(1181,3,NULL,'Sequential-access memory**',NULL,137,138,1175,1,1), +(1182,3,NULL,'Shared memory',NULL,139,140,1175,1,1), +(1183,3,NULL,'Virtual memory',NULL,141,142,1175,1,1), +(1184,3,'B.3.3','Performance Analysis and Design Aids** (B.8, C.4)','B.3.3',144,151,1048,1,1), +(1185,3,NULL,'Formal models**',NULL,145,146,1184,1,1), +(1186,3,NULL,'Simulation**',NULL,147,148,1184,1,1), +(1187,3,NULL,'Worst-case analysis**',NULL,149,150,1184,1,1), +(1188,3,'B.3.4','Reliability, Testing, and Fault-Tolerance** (B.8)','B.3.4',152,161,1048,1,1), +(1189,3,NULL,'Diagnostics**',NULL,153,154,1188,1,1), +(1190,3,NULL,'Error-checking**',NULL,155,156,1188,1,1), +(1191,3,NULL,'Redundant design**',NULL,157,158,1188,1,1), +(1192,3,NULL,'Test generation**',NULL,159,160,1188,1,1), +(1193,3,'B.3.m','Miscellaneous','B.3.m',162,163,1048,1,1), +(1194,3,'B.4.0','General','B.4.0',166,167,1049,1,1), +(1195,3,'B.4.1','Data Communications Devices','B.4.1',168,175,1049,1,1), +(1196,3,NULL,'Processors**',NULL,169,170,1195,1,1), +(1197,3,NULL,'Receivers (e.g., voice, data, image)**',NULL,171,172,1195,1,1), +(1198,3,NULL,'Transmitters**',NULL,173,174,1195,1,1), +(1199,3,'B.4.2','Input/Output Devices','B.4.2',176,185,1049,1,1), +(1200,3,NULL,'Channels and controllers',NULL,177,178,1199,1,1), +(1201,3,NULL,'Data terminals and printers',NULL,179,180,1199,1,1), +(1202,3,NULL,'Image display',NULL,181,182,1199,1,1), +(1203,3,NULL,'Voice',NULL,183,184,1199,1,1), +(1204,3,'B.4.3','Interconnections (Subsystems)','B.4.3',186,199,1049,1,1), +(1205,3,NULL,'Asynchronous/synchronous operation',NULL,187,188,1204,1,1), +(1206,3,NULL,'Fiber optics',NULL,189,190,1204,1,1), +(1207,3,NULL,'Interfaces',NULL,191,192,1204,1,1), +(1208,3,NULL,'Parallel I/O (NEW)',NULL,193,194,1204,1,1), +(1209,3,NULL,'Physical structures (e.g., backplanes, cables, chip carriers)**',NULL,195,196,1204,1,1), +(1210,3,NULL,'Topology (e.g., bus, point-to-point)',NULL,197,198,1204,1,1), +(1211,3,'B.4.4','Performance Analysis and Design Aids** (B.8)','B.4.4',200,209,1049,1,1), +(1212,3,NULL,'Formal models**',NULL,201,202,1211,1,1), +(1213,3,NULL,'Simulation**',NULL,203,204,1211,1,1), +(1214,3,NULL,'Verification**',NULL,205,206,1211,1,1), +(1215,3,NULL,'Worst-case analysis**',NULL,207,208,1211,1,1), +(1216,3,'B.4.5','Reliability, Testing, and Fault-Tolerance** (B.8)','B.4.5',210,223,1049,1,1), +(1217,3,NULL,'Built-in tests**',NULL,211,212,1216,1,1), +(1218,3,NULL,'Diagnostics**',NULL,213,214,1216,1,1), +(1219,3,NULL,'Error-checking**',NULL,215,216,1216,1,1), +(1220,3,NULL,'Hardware reliability**',NULL,217,218,1216,1,1), +(1221,3,NULL,'Redundant design**',NULL,219,220,1216,1,1), +(1222,3,NULL,'Test generation**',NULL,221,222,1216,1,1), +(1223,3,'B.4.m','Miscellaneous','B.4.m',224,225,1049,1,1), +(1224,3,'B.5.0','General','B.5.0',228,229,1050,1,1), +(1225,3,'B.5.1','Design','B.5.1',230,241,1050,1,1), +(1226,3,NULL,'Arithmetic and logic units',NULL,231,232,1225,1,1), +(1227,3,NULL,'Control design',NULL,233,234,1225,1,1), +(1228,3,NULL,'Data-path design',NULL,235,236,1225,1,1), +(1229,3,NULL,'Memory design',NULL,237,238,1225,1,1), +(1230,3,NULL,'Styles (e.g., parallel, pipeline, special-purpose)',NULL,239,240,1225,1,1), +(1231,3,'B.5.2','Design Aids','B.5.2',242,253,1050,1,1), +(1232,3,NULL,'Automatic synthesis',NULL,243,244,1231,1,1), +(1233,3,NULL,'Hardware description languages',NULL,245,246,1231,1,1), +(1234,3,NULL,'Optimization',NULL,247,248,1231,1,1), +(1235,3,NULL,'Simulation',NULL,249,250,1231,1,1), +(1236,3,NULL,'Verification',NULL,251,252,1231,1,1), +(1237,3,'B.5.3','Reliability and Testing** (B.8)','B.5.3',254,265,1050,1,1), +(1238,3,NULL,'Built-in tests**',NULL,255,256,1237,1,1), +(1239,3,NULL,'Error-checking**',NULL,257,258,1237,1,1), +(1240,3,NULL,'Redundant design**',NULL,259,260,1237,1,1), +(1241,3,NULL,'Test generation**',NULL,261,262,1237,1,1), +(1242,3,NULL,'Testability**',NULL,263,264,1237,1,1), +(1243,3,'B.5.m','Miscellaneous','B.5.m',266,267,1050,1,1), +(1244,3,'B.6.0','General','B.6.0',270,271,1051,1,1), +(1245,3,'B.6.1','Design Styles','B.6.1',272,287,1051,1,1), +(1246,3,NULL,'Cellular arrays and automata',NULL,273,274,1245,1,1), +(1247,3,NULL,'Combinational logic',NULL,275,276,1245,1,1), +(1248,3,NULL,'Logic arrays',NULL,277,278,1245,1,1), +(1249,3,NULL,'Memory control and access**',NULL,279,280,1245,1,1), +(1250,3,NULL,'Memory used as logic**',NULL,281,282,1245,1,1), +(1251,3,NULL,'Parallel circuits',NULL,283,284,1245,1,1), +(1252,3,NULL,'Sequential circuits',NULL,285,286,1245,1,1), +(1253,3,'B.6.2','Reliability and Testing** (B.8)','B.6.2',288,299,1051,1,1), +(1254,3,NULL,'Built-in tests**',NULL,289,290,1253,1,1), +(1255,3,NULL,'Error-checking**',NULL,291,292,1253,1,1), +(1256,3,NULL,'Redundant design**',NULL,293,294,1253,1,1), +(1257,3,NULL,'Test generation**',NULL,295,296,1253,1,1), +(1258,3,NULL,'Testability**',NULL,297,298,1253,1,1), +(1259,3,'B.6.3','Design Aids','B.6.3',300,313,1051,1,1), +(1260,3,NULL,'Automatic synthesis',NULL,301,302,1259,1,1), +(1261,3,NULL,'Hardware description languages',NULL,303,304,1259,1,1), +(1262,3,NULL,'Optimization',NULL,305,306,1259,1,1), +(1263,3,NULL,'Simulation',NULL,307,308,1259,1,1), +(1264,3,NULL,'Switching theory',NULL,309,310,1259,1,1), +(1265,3,NULL,'Verification',NULL,311,312,1259,1,1), +(1266,3,'B.6.m','Miscellaneous','B.6.m',314,315,1051,1,1), +(1267,3,'B.7.0','General','B.7.0',318,319,1052,1,1), +(1268,3,'B.7.1','Types and Design Styles','B.7.1',320,337,1052,1,1), +(1269,3,NULL,'Advanced technologies',NULL,321,322,1268,1,1), +(1270,3,NULL,'Algorithms implemented in hardware',NULL,323,324,1268,1,1), +(1271,3,NULL,'Gate arrays',NULL,325,326,1268,1,1), +(1272,3,NULL,'Input/output circuits',NULL,327,328,1268,1,1), +(1273,3,NULL,'Memory technologies',NULL,329,330,1268,1,1), +(1274,3,NULL,'Microprocessors and microcomputers',NULL,331,332,1268,1,1), +(1275,3,NULL,'Standard cells**',NULL,333,334,1268,1,1), +(1276,3,NULL,'VLSI (very large scale integration)',NULL,335,336,1268,1,1), +(1277,3,'B.7.2','Design Aids','B.7.2',338,349,1052,1,1), +(1278,3,NULL,'Graphics',NULL,339,340,1277,1,1), +(1279,3,NULL,'Layout',NULL,341,342,1277,1,1), +(1280,3,NULL,'Placement and routing',NULL,343,344,1277,1,1), +(1281,3,NULL,'Simulation',NULL,345,346,1277,1,1), +(1282,3,NULL,'Verification',NULL,347,348,1277,1,1), +(1283,3,'B.7.3','Reliability and Testing** (B.8)','B.7.3',350,361,1052,1,1), +(1284,3,NULL,'Built-in tests**',NULL,351,352,1283,1,1), +(1285,3,NULL,'Error-checking**',NULL,353,354,1283,1,1), +(1286,3,NULL,'Redundant design**',NULL,355,356,1283,1,1), +(1287,3,NULL,'Test generation**',NULL,357,358,1283,1,1), +(1288,3,NULL,'Testability**',NULL,359,360,1283,1,1), +(1289,3,'B.7.m','Miscellaneous','B.7.m',362,363,1052,1,1), +(1290,3,'B.8.0','General (NEW)','B.8.0',366,367,1053,1,1), +(1291,3,'B.8.1','Reliability, Testing, and Fault-Tolerance (NEW)','B.8.1',368,369,1053,1,1), +(1292,3,'B.8.2','Performance Analysis and Design Aids (NEW)','B.8.2',370,371,1053,1,1), +(1293,3,'B.8.m','Miscellaneous (NEW)','B.8.m',372,373,1053,1,1), +(1294,3,NULL,'Design management',NULL,376,377,1054,1,1), +(1295,3,'C.1.0','General','C.1.0',384,385,1056,1,1), +(1296,3,'C.1.1','Single Data Stream Architectures','C.1.1',386,397,1056,1,1), +(1297,3,NULL,'Multiple-instruction-stream, single-data-stream processors (MISD)**',NULL,387,388,1296,1,1), +(1298,3,NULL,'Pipeline processors**',NULL,389,390,1296,1,1), +(1299,3,NULL,'RISC/CISC, VLIW architectures (NEW)',NULL,391,392,1296,1,1), +(1300,3,NULL,'Single-instruction-stream, single-data-stream processors (SISD)**',NULL,393,394,1296,1,1), +(1301,3,NULL,'Von Neumann architectures**',NULL,395,396,1296,1,1), +(1302,3,'C.1.2','Multiple Data Stream Architectures (Multiprocessors)','C.1.2',398,415,1056,1,1), +(1303,3,NULL,'Array and vector processors',NULL,399,400,1302,1,1), +(1304,3,NULL,'Associative processors',NULL,401,402,1302,1,1), +(1305,3,NULL,'Connection machines',NULL,403,404,1302,1,1), +(1306,3,NULL,'Interconnection architectures (e.g., common bus, multiport memory, crossbar switch)',NULL,405,406,1302,1,1), +(1307,3,NULL,'Multiple-instruction-stream, multiple-data-stream processors (MIMD)',NULL,407,408,1302,1,1), +(1308,3,NULL,'Parallel processors**',NULL,409,410,1302,1,1), +(1309,3,NULL,'Pipeline processors**',NULL,411,412,1302,1,1), +(1310,3,NULL,'Single-instruction-stream, multiple-data-stream processors (SIMD)',NULL,413,414,1302,1,1), +(1311,3,'C.1.3','Other Architecture Styles','C.1.3',416,437,1056,1,1), +(1312,3,NULL,'Adaptable architectures',NULL,417,418,1311,1,1), +(1313,3,NULL,'Analog computers (NEW)',NULL,419,420,1311,1,1), +(1314,3,NULL,'Capability architectures**',NULL,421,422,1311,1,1), +(1315,3,NULL,'Cellular architecture (e.g., mobile) (REVISED)',NULL,423,424,1311,1,1), +(1316,3,NULL,'Data-flow architectures',NULL,425,426,1311,1,1), +(1317,3,NULL,'Heterogeneous (hybrid) systems (NEW)',NULL,427,428,1311,1,1), +(1318,3,NULL,'High-level language architectures**',NULL,429,430,1311,1,1), +(1319,3,NULL,'Neural nets',NULL,431,432,1311,1,1), +(1320,3,NULL,'Pipeline processors (NEW)',NULL,433,434,1311,1,1), +(1321,3,NULL,'Stack-oriented processors**',NULL,435,436,1311,1,1), +(1322,3,'C.1.4','Parallel Architectures (NEW)','C.1.4',438,443,1056,1,1), +(1323,3,NULL,'Distributed architectures (NEW)',NULL,439,440,1322,1,1), +(1324,3,NULL,'Mobile processors (NEW)',NULL,441,442,1322,1,1), +(1325,3,'C.1.m','Miscellaneous','C.1.m',444,449,1056,1,1), +(1326,3,NULL,'Analog computers**',NULL,445,446,1325,1,1), +(1327,3,NULL,'Hybrid systems**',NULL,447,448,1325,1,1), +(1328,3,'C.2.0','General','C.2.0',452,459,1057,1,1), +(1329,3,NULL,'Data communications',NULL,453,454,1328,1,1), +(1330,3,NULL,'Open Systems Interconnection reference model (OSI)',NULL,455,456,1328,1,1), +(1331,3,NULL,'Security and protection (e.g., firewalls) (REVISED)',NULL,457,458,1328,1,1), +(1332,3,'C.2.1','Network Architecture and Design','C.2.1',460,483,1057,1,1), +(1333,3,NULL,'Asynchronous Transfer Mode (ATM) (NEW)',NULL,461,462,1332,1,1), +(1334,3,NULL,'Centralized networks**',NULL,463,464,1332,1,1), +(1335,3,NULL,'Circuit-switching networks',NULL,465,466,1332,1,1), +(1336,3,NULL,'Distributed networks',NULL,467,468,1332,1,1), +(1337,3,NULL,'Frame relay networks (NEW)',NULL,469,470,1332,1,1), +(1338,3,NULL,'ISDN (Integrated Services Digital Network)',NULL,471,472,1332,1,1), +(1339,3,NULL,'Network communications',NULL,473,474,1332,1,1), +(1340,3,NULL,'Network topology',NULL,475,476,1332,1,1), +(1341,3,NULL,'Packet-switching networks (REVISED)',NULL,477,478,1332,1,1), +(1342,3,NULL,'Store and forward networks',NULL,479,480,1332,1,1), +(1343,3,NULL,'Wireless communication (NEW)',NULL,481,482,1332,1,1), +(1344,3,'C.2.2','Network Protocols','C.2.2',484,493,1057,1,1), +(1345,3,NULL,'Applications (SMTP, FTP, etc.) (NEW)',NULL,485,486,1344,1,1), +(1346,3,NULL,'Protocol architecture (OSI model) (REVISED)',NULL,487,488,1344,1,1), +(1347,3,NULL,'Protocol verification',NULL,489,490,1344,1,1), +(1348,3,NULL,'Routing protocols (NEW)',NULL,491,492,1344,1,1), +(1349,3,'C.2.3','Network Operations','C.2.3',494,501,1057,1,1), +(1350,3,NULL,'Network management',NULL,495,496,1349,1,1), +(1351,3,NULL,'Network monitoring',NULL,497,498,1349,1,1), +(1352,3,NULL,'Public networks',NULL,499,500,1349,1,1), +(1353,3,'C.2.4','Distributed Systems','C.2.4',502,511,1057,1,1), +(1354,3,NULL,'Client/server (NEW)',NULL,503,504,1353,1,1), +(1355,3,NULL,'Distributed applications',NULL,505,506,1353,1,1), +(1356,3,NULL,'Distributed databases',NULL,507,508,1353,1,1), +(1357,3,NULL,'Network operating systems',NULL,509,510,1353,1,1), +(1358,3,'C.2.5','Local and Wide-Area Networks (REVISED)','C.2.5',512,525,1057,1,1), +(1359,3,NULL,'Access schemes',NULL,513,514,1358,1,1), +(1360,3,NULL,'Buses',NULL,515,516,1358,1,1), +(1361,3,NULL,'Ethernet (e.g., CSMA/CD) (NEW)',NULL,517,518,1358,1,1), +(1362,3,NULL,'High-speed (e.g., FDDI, fiber channel, ATM) (NEW)',NULL,519,520,1358,1,1), +(1363,3,NULL,'Internet (e.g., TCP/IP) (NEW)',NULL,521,522,1358,1,1), +(1364,3,NULL,'Token rings (REVISED)',NULL,523,524,1358,1,1), +(1365,3,'C.2.6','Internetworking (C.2.2) (NEW)','C.2.6',526,531,1057,1,1), +(1366,3,NULL,'Routers (NEW)',NULL,527,528,1365,1,1), +(1367,3,NULL,'Standards (e.g., TCP/IP) (NEW)',NULL,529,530,1365,1,1), +(1368,3,'C.2.m','Miscellaneous','C.2.m',532,533,1057,1,1), +(1369,3,'C.5.0','General','C.5.0',540,541,1060,1,1), +(1370,3,'C.5.1','Large and Medium Mainframe Computers','C.5.1',542,545,1060,1,1), +(1371,3,NULL,'Super (very large) computers',NULL,543,544,1370,1,1), +(1372,3,'C.5.2','Minicomputers**','C.5.2',546,547,1060,1,1), +(1373,3,'C.5.3','Microcomputers','C.5.3',548,557,1060,1,1), +(1374,3,NULL,'Microprocessors',NULL,549,550,1373,1,1), +(1375,3,NULL,'Personal computers',NULL,551,552,1373,1,1), +(1376,3,NULL,'Portable devices (e.g., laptops, personal digital assistants) (NEW)',NULL,553,554,1373,1,1), +(1377,3,NULL,'Workstations',NULL,555,556,1373,1,1), +(1378,3,'C.5.4','VLSI Systems','C.5.4',558,559,1060,1,1), +(1379,3,'C.5.5','Servers (NEW)','C.5.5',560,561,1060,1,1), +(1380,3,'C.5.m','Miscellaneous','C.5.m',562,563,1060,1,1), +(1381,3,'D.1.0','General','D.1.0',572,573,1063,1,1), +(1382,3,'D.1.1','Applicative (Functional) Programming','D.1.1',574,575,1063,1,1), +(1383,3,'D.1.2','Automatic Programming (I.2.2)','D.1.2',576,577,1063,1,1), +(1384,3,'D.1.3','Concurrent Programming','D.1.3',578,583,1063,1,1), +(1385,3,NULL,'Distributed programming',NULL,579,580,1384,1,1), +(1386,3,NULL,'Parallel programming',NULL,581,582,1384,1,1), +(1387,3,'D.1.4','Sequential Programming','D.1.4',584,585,1063,1,1), +(1388,3,'D.1.5','Object-oriented Programming','D.1.5',586,587,1063,1,1), +(1389,3,'D.1.6','Logic Programming','D.1.6',588,589,1063,1,1), +(1390,3,'D.1.7','Visual Programming','D.1.7',590,591,1063,1,1), +(1391,3,'D.1.m','Miscellaneous','D.1.m',592,593,1063,1,1), +(1392,3,'D.2.0','General (K.5.1)','D.2.0',596,601,1064,1,1), +(1393,3,NULL,'Protection mechanisms',NULL,597,598,1392,1,1), +(1394,3,NULL,'Standards',NULL,599,600,1392,1,1), +(1395,3,'D.2.1','Requirements/Specifications (D.3.1)','D.2.1',602,611,1064,1,1), +(1396,3,NULL,'Elicitation methods (e.g., rapid prototyping, interviews, JAD) (NEW)',NULL,603,604,1395,1,1), +(1397,3,NULL,'Languages',NULL,605,606,1395,1,1), +(1398,3,NULL,'Methodologies (e.g., object-oriented, structured) (REVISED)',NULL,607,608,1395,1,1), +(1399,3,NULL,'Tools',NULL,609,610,1395,1,1), +(1400,3,'D.2.2','Design Tools and Techniques (REVISED)','D.2.2',612,639,1064,1,1), +(1401,3,NULL,'Computer-aided software engineering (CASE)',NULL,613,614,1400,1,1), +(1402,3,NULL,'Decision tables',NULL,615,616,1400,1,1), +(1403,3,NULL,'Evolutionary prototyping (NEW)',NULL,617,618,1400,1,1), +(1404,3,NULL,'Flow charts',NULL,619,620,1400,1,1), +(1405,3,NULL,'Modules and interfaces',NULL,621,622,1400,1,1), +(1406,3,NULL,'Object-oriented design methods (NEW)',NULL,623,624,1400,1,1), +(1407,3,NULL,'Petri nets',NULL,625,626,1400,1,1), +(1408,3,NULL,'Programmer workbench**',NULL,627,628,1400,1,1), +(1409,3,NULL,'Software libraries',NULL,629,630,1400,1,1), +(1410,3,NULL,'State diagrams (NEW)',NULL,631,632,1400,1,1), +(1411,3,NULL,'Structured programming**',NULL,633,634,1400,1,1), +(1412,3,NULL,'Top-down programming**',NULL,635,636,1400,1,1), +(1413,3,NULL,'User interfaces',NULL,637,638,1400,1,1), +(1414,3,'D.2.3','Coding Tools and Techniques (REVISED)','D.2.3',640,655,1064,1,1), +(1415,3,NULL,'Object-oriented programming (NEW)',NULL,641,642,1414,1,1), +(1416,3,NULL,'Pretty printers',NULL,643,644,1414,1,1), +(1417,3,NULL,'Program editors',NULL,645,646,1414,1,1), +(1418,3,NULL,'Reentrant code**',NULL,647,648,1414,1,1), +(1419,3,NULL,'Standards',NULL,649,650,1414,1,1), +(1420,3,NULL,'Structured programming (NEW)',NULL,651,652,1414,1,1), +(1421,3,NULL,'Top-down programming (NEW)',NULL,653,654,1414,1,1), +(1422,3,'D.2.4','Software/Program Verification (F.3.1) (REVISED)','D.2.4',656,675,1064,1,1), +(1423,3,NULL,'Assertion checkers',NULL,657,658,1422,1,1), +(1424,3,NULL,'Class invariants (NEW)',NULL,659,660,1422,1,1), +(1425,3,NULL,'Correctness proofs',NULL,661,662,1422,1,1), +(1426,3,NULL,'Formal methods (NEW)',NULL,663,664,1422,1,1), +(1427,3,NULL,'Model checking (NEW)',NULL,665,666,1422,1,1), +(1428,3,NULL,'Programming by contract (NEW)',NULL,667,668,1422,1,1), +(1429,3,NULL,'Reliability',NULL,669,670,1422,1,1), +(1430,3,NULL,'Statistical methods (NEW)',NULL,671,672,1422,1,1), +(1431,3,NULL,'Validation',NULL,673,674,1422,1,1), +(1432,3,'D.2.5','Testing and Debugging','D.2.5',676,697,1064,1,1), +(1433,3,NULL,'Code inspections and walk-throughs',NULL,677,678,1432,1,1), +(1434,3,NULL,'Debugging aids',NULL,679,680,1432,1,1), +(1435,3,NULL,'Diagnostics',NULL,681,682,1432,1,1), +(1436,3,NULL,'Distributed debugging (NEW)',NULL,683,684,1432,1,1), +(1437,3,NULL,'Dumps**',NULL,685,686,1432,1,1), +(1438,3,NULL,'Error handling and recovery',NULL,687,688,1432,1,1), +(1439,3,NULL,'Monitors',NULL,689,690,1432,1,1), +(1440,3,NULL,'Symbolic execution',NULL,691,692,1432,1,1), +(1441,3,NULL,'Testing tools (e.g., data generators, coverage testing) (REVISED)',NULL,693,694,1432,1,1), +(1442,3,NULL,'Tracing',NULL,695,696,1432,1,1), +(1443,3,'D.2.6','Programming Environments','D.2.6',698,707,1064,1,1), +(1444,3,NULL,'Graphical environments (NEW)',NULL,699,700,1443,1,1), +(1445,3,NULL,'Integrated environments (NEW)',NULL,701,702,1443,1,1), +(1446,3,NULL,'Interactive environments (REVISED)',NULL,703,704,1443,1,1), +(1447,3,NULL,'Programmer workbench (NEW)',NULL,705,706,1443,1,1), +(1448,3,'D.2.7','Distribution, Maintenance, and Enhancement (REVISED)','D.2.7',708,723,1064,1,1), +(1449,3,NULL,'Corrections**',NULL,709,710,1448,1,1), +(1450,3,NULL,'Documentation',NULL,711,712,1448,1,1), +(1451,3,NULL,'Enhancement**',NULL,713,714,1448,1,1), +(1452,3,NULL,'Extensibility**',NULL,715,716,1448,1,1), +(1453,3,NULL,'Portability',NULL,717,718,1448,1,1), +(1454,3,NULL,'Restructuring, reverse engineering, and reengineering (REVISED)',NULL,719,720,1448,1,1), +(1455,3,NULL,'Version control',NULL,721,722,1448,1,1), +(1456,3,'D.2.8','Metrics (D.4.8)','D.2.8',724,735,1064,1,1), +(1457,3,NULL,'Complexity measures',NULL,725,726,1456,1,1), +(1458,3,NULL,'Performance measures',NULL,727,728,1456,1,1), +(1459,3,NULL,'Process metrics (NEW)',NULL,729,730,1456,1,1), +(1460,3,NULL,'Product metrics (NEW)',NULL,731,732,1456,1,1), +(1461,3,NULL,'Software science**',NULL,733,734,1456,1,1), +(1462,3,'D.2.9','Management (K.6.3, K.6.4)','D.2.9',736,755,1064,1,1), +(1463,3,NULL,'Copyrights**',NULL,737,738,1462,1,1), +(1464,3,NULL,'Cost estimation',NULL,739,740,1462,1,1), +(1465,3,NULL,'Life cycle',NULL,741,742,1462,1,1), +(1466,3,NULL,'Productivity',NULL,743,744,1462,1,1), +(1467,3,NULL,'Programming teams',NULL,745,746,1462,1,1), +(1468,3,NULL,'Software configuration management',NULL,747,748,1462,1,1), +(1469,3,NULL,'Software process models (e.g., CMM, ISO, PSP) (NEW)',NULL,749,750,1462,1,1), +(1470,3,NULL,'Software quality assurance (SQA)',NULL,751,752,1462,1,1), +(1471,3,NULL,'Time estimation',NULL,753,754,1462,1,1), +(1472,3,'D.2.10','Design** (D.2.2)','D.2.10',756,761,1064,1,1), +(1473,3,NULL,'Methodologies**',NULL,757,758,1472,1,1), +(1474,3,NULL,'Representation**',NULL,759,760,1472,1,1), +(1475,3,'D.2.11','Software Architectures (NEW)','D.2.11',762,773,1064,1,1), +(1476,3,NULL,'Data abstraction (NEW)',NULL,763,764,1475,1,1), +(1477,3,NULL,'Domain-specific architectures (NEW)',NULL,765,766,1475,1,1), +(1478,3,NULL,'Information hiding (NEW)',NULL,767,768,1475,1,1), +(1479,3,NULL,'Languages (e.g., description, interconnection, definition) (NEW)',NULL,769,770,1475,1,1), +(1480,3,NULL,'Patterns (e.g., client/server, pipeline, blackboard) (NEW)',NULL,771,772,1475,1,1), +(1481,3,'D.2.12','Interoperability (NEW)','D.2.12',774,781,1064,1,1), +(1482,3,NULL,'Data mapping (NEW)',NULL,775,776,1481,1,1), +(1483,3,NULL,'Distributed objects (NEW)',NULL,777,778,1481,1,1), +(1484,3,NULL,'Interface definition languages (NEW)',NULL,779,780,1481,1,1), +(1485,3,'D.2.13','Reusable Software (NEW)','D.2.13',782,789,1064,1,1), +(1486,3,NULL,'Domain engineering (NEW)',NULL,783,784,1485,1,1), +(1487,3,NULL,'Reusable libraries (NEW)',NULL,785,786,1485,1,1), +(1488,3,NULL,'Reuse models (NEW)',NULL,787,788,1485,1,1), +(1489,3,'D.2.m','Miscellaneous','D.2.m',790,795,1064,1,1), +(1490,3,NULL,'Rapid prototyping**',NULL,791,792,1489,1,1), +(1491,3,NULL,'Reusable software**',NULL,793,794,1489,1,1), +(1492,3,'D.3.0','General','D.3.0',798,801,1065,1,1), +(1493,3,NULL,'Standards',NULL,799,800,1492,1,1), +(1494,3,'D.3.1','Formal Definitions and Theory (D.2.1, F.3.1-2, F.4.2-3)','D.3.1',802,807,1065,1,1), +(1495,3,NULL,'Semantics',NULL,803,804,1494,1,1), +(1496,3,NULL,'Syntax',NULL,805,806,1494,1,1), +(1497,3,'D.3.2','Language Classifications','D.3.2',808,837,1065,1,1), +(1498,3,NULL,'Applicative (functional) languages (REVISED)',NULL,809,810,1497,1,1), +(1499,3,NULL,'Concurrent, distributed, and parallel languages',NULL,811,812,1497,1,1), +(1500,3,NULL,'Constraint and logic languages (NEW)',NULL,813,814,1497,1,1), +(1501,3,NULL,'Data-flow languages',NULL,815,816,1497,1,1), +(1502,3,NULL,'Design languages',NULL,817,818,1497,1,1), +(1503,3,NULL,'Extensible languages',NULL,819,820,1497,1,1), +(1504,3,NULL,'Macro and assembly languages',NULL,821,822,1497,1,1), +(1505,3,NULL,'Microprogramming languages**',NULL,823,824,1497,1,1), +(1506,3,NULL,'Multiparadigm languages (NEW)',NULL,825,826,1497,1,1), +(1507,3,NULL,'Nondeterministic languages**',NULL,827,828,1497,1,1), +(1508,3,NULL,'Nonprocedural languages**',NULL,829,830,1497,1,1), +(1509,3,NULL,'Object-oriented languages',NULL,831,832,1497,1,1), +(1510,3,NULL,'Specialized application languages',NULL,833,834,1497,1,1), +(1511,3,NULL,'Very high-level languages',NULL,835,836,1497,1,1), +(1512,3,'D.3.3','Language Constructs and Features (E.2)','D.3.3',838,871,1065,1,1), +(1513,3,NULL,'Abstract data types',NULL,839,840,1512,1,1), +(1514,3,NULL,'Classes and objects (NEW)',NULL,841,842,1512,1,1), +(1515,3,NULL,'Concurrent programming structures',NULL,843,844,1512,1,1), +(1516,3,NULL,'Constraints (NEW)',NULL,845,846,1512,1,1), +(1517,3,NULL,'Control structures',NULL,847,848,1512,1,1), +(1518,3,NULL,'Coroutines',NULL,849,850,1512,1,1), +(1519,3,NULL,'Data types and structures',NULL,851,852,1512,1,1), +(1520,3,NULL,'Dynamic storage management',NULL,853,854,1512,1,1), +(1521,3,NULL,'Frameworks (NEW)',NULL,855,856,1512,1,1), +(1522,3,NULL,'Inheritance (NEW)',NULL,857,858,1512,1,1), +(1523,3,NULL,'Input/output',NULL,859,860,1512,1,1), +(1524,3,NULL,'Modules, packages',NULL,861,862,1512,1,1), +(1525,3,NULL,'Patterns (NEW)',NULL,863,864,1512,1,1), +(1526,3,NULL,'Polymorphism (NEW)',NULL,865,866,1512,1,1), +(1527,3,NULL,'Procedures, functions, and subroutines',NULL,867,868,1512,1,1), +(1528,3,NULL,'Recursion',NULL,869,870,1512,1,1), +(1529,3,'D.3.4','Processors','D.3.4',872,897,1065,1,1), +(1530,3,NULL,'Code generation',NULL,873,874,1529,1,1), +(1531,3,NULL,'Compilers',NULL,875,876,1529,1,1), +(1532,3,NULL,'Debuggers (NEW)',NULL,877,878,1529,1,1), +(1533,3,NULL,'Incremental compilers (NEW)',NULL,879,880,1529,1,1), +(1534,3,NULL,'Interpreters',NULL,881,882,1529,1,1), +(1535,3,NULL,'Memory management (garbage collection) (NEW)',NULL,883,884,1529,1,1), +(1536,3,NULL,'Optimization',NULL,885,886,1529,1,1), +(1537,3,NULL,'Parsing',NULL,887,888,1529,1,1), +(1538,3,NULL,'Preprocessors',NULL,889,890,1529,1,1), +(1539,3,NULL,'Retargetable compilers (NEW)',NULL,891,892,1529,1,1), +(1540,3,NULL,'Run-time environments',NULL,893,894,1529,1,1), +(1541,3,NULL,'Translator writing systems and compiler generators',NULL,895,896,1529,1,1), +(1542,3,'D.3.m','Miscellaneous','D.3.m',898,899,1065,1,1), +(1543,3,'D.4.0','General','D.4.0',902,903,1066,1,1), +(1544,3,'D.4.1','Process Management','D.4.1',904,919,1066,1,1), +(1545,3,NULL,'Concurrency',NULL,905,906,1544,1,1), +(1546,3,NULL,'Deadlocks',NULL,907,908,1544,1,1), +(1547,3,NULL,'Multiprocessing/multiprogramming/multitasking (REVISED)',NULL,909,910,1544,1,1), +(1548,3,NULL,'Mutual exclusion',NULL,911,912,1544,1,1), +(1549,3,NULL,'Scheduling',NULL,913,914,1544,1,1), +(1550,3,NULL,'Synchronization',NULL,915,916,1544,1,1), +(1551,3,NULL,'Threads (NEW)',NULL,917,918,1544,1,1), +(1552,3,'D.4.2','Storage Management','D.4.2',920,939,1066,1,1), +(1553,3,NULL,'Allocation/deallocation strategies',NULL,921,922,1552,1,1), +(1554,3,NULL,'Distributed memories',NULL,923,924,1552,1,1), +(1555,3,NULL,'Garbage collection (NEW)',NULL,925,926,1552,1,1), +(1556,3,NULL,'Main memory',NULL,927,928,1552,1,1), +(1557,3,NULL,'Secondary storage',NULL,929,930,1552,1,1), +(1558,3,NULL,'Segmentation**',NULL,931,932,1552,1,1), +(1559,3,NULL,'Storage hierarchies',NULL,933,934,1552,1,1), +(1560,3,NULL,'Swapping**',NULL,935,936,1552,1,1), +(1561,3,NULL,'Virtual memory',NULL,937,938,1552,1,1), +(1562,3,'D.4.3','File Systems Management (E.5)','D.4.3',940,951,1066,1,1), +(1563,3,NULL,'Access methods',NULL,941,942,1562,1,1), +(1564,3,NULL,'Directory structures',NULL,943,944,1562,1,1), +(1565,3,NULL,'Distributed file systems',NULL,945,946,1562,1,1), +(1566,3,NULL,'File organization',NULL,947,948,1562,1,1), +(1567,3,NULL,'Maintenance**',NULL,949,950,1562,1,1), +(1568,3,'D.4.4','Communications Management (C.2)','D.4.4',952,963,1066,1,1), +(1569,3,NULL,'Buffering',NULL,953,954,1568,1,1), +(1570,3,NULL,'Input/output',NULL,955,956,1568,1,1), +(1571,3,NULL,'Message sending',NULL,957,958,1568,1,1), +(1572,3,NULL,'Network communication',NULL,959,960,1568,1,1), +(1573,3,NULL,'Terminal management**',NULL,961,962,1568,1,1), +(1574,3,'D.4.5','Reliability','D.4.5',964,973,1066,1,1), +(1575,3,NULL,'Backup procedures',NULL,965,966,1574,1,1), +(1576,3,NULL,'Checkpoint/restart',NULL,967,968,1574,1,1), +(1577,3,NULL,'Fault-tolerance',NULL,969,970,1574,1,1), +(1578,3,NULL,'Verification',NULL,971,972,1574,1,1), +(1579,3,'D.4.6','Security and Protection (K.6.5)','D.4.6',974,989,1066,1,1), +(1580,3,NULL,'Access controls',NULL,975,976,1579,1,1), +(1581,3,NULL,'Authentication',NULL,977,978,1579,1,1), +(1582,3,NULL,'Cryptographic controls',NULL,979,980,1579,1,1), +(1583,3,NULL,'Information flow controls',NULL,981,982,1579,1,1), +(1584,3,NULL,'Invasive software (e.g., viruses, worms, Trojan horses)',NULL,983,984,1579,1,1), +(1585,3,NULL,'Security kernels**',NULL,985,986,1579,1,1), +(1586,3,NULL,'Verification**',NULL,987,988,1579,1,1), +(1587,3,'D.4.7','Organization and Design','D.4.7',990,1001,1066,1,1), +(1588,3,NULL,'Batch processing systems**',NULL,991,992,1587,1,1), +(1589,3,NULL,'Distributed systems',NULL,993,994,1587,1,1), +(1590,3,NULL,'Hierarchical design**',NULL,995,996,1587,1,1), +(1591,3,NULL,'Interactive systems',NULL,997,998,1587,1,1), +(1592,3,NULL,'Real-time systems and embedded systems',NULL,999,1000,1587,1,1), +(1593,3,'D.4.8','Performance (C.4, D.2.8, I.6)','D.4.8',1002,1017,1066,1,1), +(1594,3,NULL,'Measurements',NULL,1003,1004,1593,1,1), +(1595,3,NULL,'Modeling and prediction',NULL,1005,1006,1593,1,1), +(1596,3,NULL,'Monitors',NULL,1007,1008,1593,1,1), +(1597,3,NULL,'Operational analysis',NULL,1009,1010,1593,1,1), +(1598,3,NULL,'Queueing theory',NULL,1011,1012,1593,1,1), +(1599,3,NULL,'Simulation',NULL,1013,1014,1593,1,1), +(1600,3,NULL,'Stochastic analysis',NULL,1015,1016,1593,1,1), +(1601,3,'D.4.9','Systems Programs and Utilities','D.4.9',1018,1027,1066,1,1), +(1602,3,NULL,'Command and control languages',NULL,1019,1020,1601,1,1), +(1603,3,NULL,'Linkers**',NULL,1021,1022,1601,1,1), +(1604,3,NULL,'Loaders**',NULL,1023,1024,1601,1,1), +(1605,3,NULL,'Window managers',NULL,1025,1026,1601,1,1), +(1606,3,'D.4.m','Miscellaneous','D.4.m',1028,1029,1066,1,1), +(1607,3,NULL,'Software psychology**',NULL,1032,1033,1067,1,1), +(1608,3,NULL,'Arrays',NULL,1040,1041,1069,1,1), +(1609,3,NULL,'Distributed data structures (NEW)',NULL,1042,1043,1069,1,1), +(1610,3,NULL,'Graphs and networks (REVISED)',NULL,1044,1045,1069,1,1), +(1611,3,NULL,'Lists, stacks, and queues (REVISED)',NULL,1046,1047,1069,1,1), +(1612,3,NULL,'Records (NEW)',NULL,1048,1049,1069,1,1), +(1613,3,NULL,'Tables**',NULL,1050,1051,1069,1,1), +(1614,3,NULL,'Trees',NULL,1052,1053,1069,1,1), +(1615,3,NULL,'Composite structures**',NULL,1056,1057,1070,1,1), +(1616,3,NULL,'Contiguous representations**',NULL,1058,1059,1070,1,1), +(1617,3,NULL,'Hash-table representations',NULL,1060,1061,1070,1,1), +(1618,3,NULL,'Linked representations',NULL,1062,1063,1070,1,1), +(1619,3,NULL,'Object representation (NEW)',NULL,1064,1065,1070,1,1), +(1620,3,NULL,'Primitive data items**',NULL,1066,1067,1070,1,1), +(1621,3,NULL,'Code breaking (NEW)',NULL,1070,1071,1071,1,1), +(1622,3,NULL,'Data encryption standard (DES)**',NULL,1072,1073,1071,1,1), +(1623,3,NULL,'Public key cryptosystems',NULL,1074,1075,1071,1,1), +(1624,3,NULL,'Standards (e.g., DES, PGP, RSA) (NEW)',NULL,1076,1077,1071,1,1), +(1625,3,NULL,'Data compaction and compression',NULL,1080,1081,1072,1,1), +(1626,3,NULL,'Error control codes',NULL,1082,1083,1072,1,1), +(1627,3,NULL,'Formal models of communication',NULL,1084,1085,1072,1,1), +(1628,3,NULL,'Nonsecret encoding schemes**',NULL,1086,1087,1072,1,1), +(1629,3,NULL,'Backup/recovery',NULL,1090,1091,1073,1,1), +(1630,3,NULL,'Optimization**',NULL,1092,1093,1073,1,1), +(1631,3,NULL,'Organization/structure',NULL,1094,1095,1073,1,1), +(1632,3,NULL,'Sorting/searching',NULL,1096,1097,1073,1,1), +(1633,3,'F.1.0','General','F.1.0',1106,1107,1076,1,1), +(1634,3,'F.1.1','Models of Computation (F.4.1)','F.1.1',1108,1121,1076,1,1), +(1635,3,NULL,'Automata (e.g., finite, push-down, resource-bounded)',NULL,1109,1110,1634,1,1), +(1636,3,NULL,'Bounded-action devices (e.g., Turing machines, random access machines)',NULL,1111,1112,1634,1,1), +(1637,3,NULL,'Computability theory',NULL,1113,1114,1634,1,1), +(1638,3,NULL,'Relations between models',NULL,1115,1116,1634,1,1), +(1639,3,NULL,'Self-modifying machines (e.g., neural networks)',NULL,1117,1118,1634,1,1), +(1640,3,NULL,'Unbounded-action devices (e.g., cellular automata, circuits, networks of machines)',NULL,1119,1120,1634,1,1), +(1641,3,'F.1.2','Modes of Computation','F.1.2',1122,1137,1076,1,1), +(1642,3,NULL,'Alternation and nondeterminism',NULL,1123,1124,1641,1,1), +(1643,3,NULL,'Interactive and reactive computation (REVISED)',NULL,1125,1126,1641,1,1), +(1644,3,NULL,'Online computation',NULL,1127,1128,1641,1,1), +(1645,3,NULL,'Parallelism and concurrency',NULL,1129,1130,1641,1,1), +(1646,3,NULL,'Probabilistic computation',NULL,1131,1132,1641,1,1), +(1647,3,NULL,'Relations among modes**',NULL,1133,1134,1641,1,1), +(1648,3,NULL,'Relativized computation',NULL,1135,1136,1641,1,1), +(1649,3,'F.1.3','Complexity Measures and Classes (F.2) (REVISED)','F.1.3',1138,1149,1076,1,1), +(1650,3,NULL,'Complexity hierarchies',NULL,1139,1140,1649,1,1), +(1651,3,NULL,'Machine-independent complexity**',NULL,1141,1142,1649,1,1), +(1652,3,NULL,'Reducibility and completeness',NULL,1143,1144,1649,1,1), +(1653,3,NULL,'Relations among complexity classes',NULL,1145,1146,1649,1,1), +(1654,3,NULL,'Relations among complexity measures',NULL,1147,1148,1649,1,1), +(1655,3,'F.1.m','Miscellaneous','F.1.m',1150,1151,1076,1,1), +(1656,3,'F.2.0','General','F.2.0',1154,1155,1077,1,1), +(1657,3,'F.2.1','Numerical Algorithms and Problems (G.1, G.4, I.1)','F.2.1',1156,1167,1077,1,1), +(1658,3,NULL,'Computation of transforms (e.g., fast Fourier transform)',NULL,1157,1158,1657,1,1), +(1659,3,NULL,'Computations in finite fields',NULL,1159,1160,1657,1,1), +(1660,3,NULL,'Computations on matrices',NULL,1161,1162,1657,1,1), +(1661,3,NULL,'Computations on polynomials',NULL,1163,1164,1657,1,1), +(1662,3,NULL,'Number-theoretic computations (e.g., factoring, primality testing)',NULL,1165,1166,1657,1,1), +(1663,3,'F.2.2','Nonnumerical Algorithms and Problems (E.2-5, G.2, H.2-3)','F.2.2',1168,1183,1077,1,1), +(1664,3,NULL,'Complexity of proof procedures',NULL,1169,1170,1663,1,1), +(1665,3,NULL,'Computations on discrete structures',NULL,1171,1172,1663,1,1), +(1666,3,NULL,'Geometrical problems and computations',NULL,1173,1174,1663,1,1), +(1667,3,NULL,'Pattern matching',NULL,1175,1176,1663,1,1), +(1668,3,NULL,'Routing and layout',NULL,1177,1178,1663,1,1), +(1669,3,NULL,'Sequencing and scheduling',NULL,1179,1180,1663,1,1), +(1670,3,NULL,'Sorting and searching',NULL,1181,1182,1663,1,1), +(1671,3,'F.2.3','Tradeoffs between Complexity Measures (F.1.3)','F.2.3',1184,1185,1077,1,1), +(1672,3,'F.2.m','Miscellaneous','F.2.m',1186,1187,1077,1,1), +(1673,3,'F.3.0','General','F.3.0',1190,1191,1078,1,1), +(1674,3,'F.3.1','Specifying and Verifying and Reasoning about Programs (D.2.1, D.2.4, D.3.1, E.1)','F.3.1',1192,1205,1078,1,1), +(1675,3,NULL,'Assertions',NULL,1193,1194,1674,1,1), +(1676,3,NULL,'Invariants',NULL,1195,1196,1674,1,1), +(1677,3,NULL,'Logics of programs',NULL,1197,1198,1674,1,1), +(1678,3,NULL,'Mechanical verification',NULL,1199,1200,1674,1,1), +(1679,3,NULL,'Pre- and post-conditions',NULL,1201,1202,1674,1,1), +(1680,3,NULL,'Specification techniques',NULL,1203,1204,1674,1,1), +(1681,3,'F.3.2','Semantics of Programming Languages (D.3.1)','F.3.2',1206,1219,1078,1,1), +(1682,3,NULL,'Algebraic approaches to semantics',NULL,1207,1208,1681,1,1), +(1683,3,NULL,'Denotational semantics',NULL,1209,1210,1681,1,1), +(1684,3,NULL,'Operational semantics',NULL,1211,1212,1681,1,1), +(1685,3,NULL,'Partial evaluation (NEW)',NULL,1213,1214,1681,1,1), +(1686,3,NULL,'Process models (NEW)',NULL,1215,1216,1681,1,1), +(1687,3,NULL,'Program analysis (NEW)',NULL,1217,1218,1681,1,1), +(1688,3,'F.3.3','Studies of Program Constructs (D.3.2-3)','F.3.3',1220,1231,1078,1,1), +(1689,3,NULL,'Control primitives',NULL,1221,1222,1688,1,1), +(1690,3,NULL,'Functional constructs',NULL,1223,1224,1688,1,1), +(1691,3,NULL,'Object-oriented constructs (NEW)',NULL,1225,1226,1688,1,1), +(1692,3,NULL,'Program and recursion schemes',NULL,1227,1228,1688,1,1), +(1693,3,NULL,'Type structure',NULL,1229,1230,1688,1,1), +(1694,3,'F.3.m','Miscellaneous','F.3.m',1232,1233,1078,1,1), +(1695,3,'F.4.0','General','F.4.0',1236,1237,1079,1,1), +(1696,3,'F.4.1','Mathematical Logic (F.1.1, I.2.2-4)','F.4.1',1238,1261,1079,1,1), +(1697,3,NULL,'Computability theory',NULL,1239,1240,1696,1,1), +(1698,3,NULL,'Computational logic',NULL,1241,1242,1696,1,1), +(1699,3,NULL,'Lambda calculus and related systems',NULL,1243,1244,1696,1,1), +(1700,3,NULL,'Logic and constraint programming (REVISED)',NULL,1245,1246,1696,1,1), +(1701,3,NULL,'Mechanical theorem proving',NULL,1247,1248,1696,1,1), +(1702,3,NULL,'Modal logic (NEW)',NULL,1249,1250,1696,1,1), +(1703,3,NULL,'Model theory',NULL,1251,1252,1696,1,1), +(1704,3,NULL,'Proof theory',NULL,1253,1254,1696,1,1), +(1705,3,NULL,'Recursive function theory',NULL,1255,1256,1696,1,1), +(1706,3,NULL,'Set theory (NEW)',NULL,1257,1258,1696,1,1), +(1707,3,NULL,'Temporal logic (NEW)',NULL,1259,1260,1696,1,1), +(1708,3,'F.4.2','Grammars and Other Rewriting Systems (D.3.1)','F.4.2',1262,1273,1079,1,1), +(1709,3,NULL,'Decision problems',NULL,1263,1264,1708,1,1), +(1710,3,NULL,'Grammar types (e.g., context-free, context-sensitive)',NULL,1265,1266,1708,1,1), +(1711,3,NULL,'Parallel rewriting systems (e.g., developmental systems, L-systems)',NULL,1267,1268,1708,1,1), +(1712,3,NULL,'Parsing',NULL,1269,1270,1708,1,1), +(1713,3,NULL,'Thue systems',NULL,1271,1272,1708,1,1), +(1714,3,'F.4.3','Formal Languages (D.3.1)','F.4.3',1274,1285,1079,1,1), +(1715,3,NULL,'Algebraic language theory',NULL,1275,1276,1714,1,1), +(1716,3,NULL,'Classes defined by grammars or automata (e.g., context-free languages, regular sets, recursive sets)',NULL,1277,1278,1714,1,1), +(1717,3,NULL,'Classes defined by resource-bounded automata**',NULL,1279,1280,1714,1,1), +(1718,3,NULL,'Decision problems',NULL,1281,1282,1714,1,1), +(1719,3,NULL,'Operations on languages',NULL,1283,1284,1714,1,1), +(1720,3,'F.4.m','Miscellaneous','F.4.m',1286,1287,1079,1,1), +(1721,3,'G.1.0','General','G.1.0',1296,1313,1082,1,1), +(1722,3,NULL,'Computer arithmetic',NULL,1297,1298,1721,1,1), +(1723,3,NULL,'Conditioning (and ill-conditioning) (REVISED)',NULL,1299,1300,1721,1,1), +(1724,3,NULL,'Error analysis',NULL,1301,1302,1721,1,1), +(1725,3,NULL,'Interval arithmetic (NEW)',NULL,1303,1304,1721,1,1), +(1726,3,NULL,'Multiple precision arithmetic (NEW)',NULL,1305,1306,1721,1,1), +(1727,3,NULL,'Numerical algorithms',NULL,1307,1308,1721,1,1), +(1728,3,NULL,'Parallel algorithms',NULL,1309,1310,1721,1,1), +(1729,3,NULL,'Stability (and instability)',NULL,1311,1312,1721,1,1), +(1730,3,'G.1.1','Interpolation (I.3.5, I.3.7)','G.1.1',1314,1325,1082,1,1), +(1731,3,NULL,'Difference formulas**',NULL,1315,1316,1730,1,1), +(1732,3,NULL,'Extrapolation',NULL,1317,1318,1730,1,1), +(1733,3,NULL,'Interpolation formulas',NULL,1319,1320,1730,1,1), +(1734,3,NULL,'Smoothing',NULL,1321,1322,1730,1,1), +(1735,3,NULL,'Spline and piecewise polynomial interpolation',NULL,1323,1324,1730,1,1), +(1736,3,'G.1.2','Approximation','G.1.2',1326,1351,1082,1,1), +(1737,3,NULL,'Approximation of surfaces and contours (NEW)',NULL,1327,1328,1736,1,1), +(1738,3,NULL,'Chebyshev approximation and theory',NULL,1329,1330,1736,1,1), +(1739,3,NULL,'Elementary function approximation',NULL,1331,1332,1736,1,1), +(1740,3,NULL,'Fast Fourier transforms (FFT) (NEW)',NULL,1333,1334,1736,1,1), +(1741,3,NULL,'Least squares approximation',NULL,1335,1336,1736,1,1), +(1742,3,NULL,'Linear approximation',NULL,1337,1338,1736,1,1), +(1743,3,NULL,'Minimax approximation and algorithms',NULL,1339,1340,1736,1,1), +(1744,3,NULL,'Nonlinear approximation',NULL,1341,1342,1736,1,1), +(1745,3,NULL,'Rational approximation',NULL,1343,1344,1736,1,1), +(1746,3,NULL,'Special function approximations (NEW)',NULL,1345,1346,1736,1,1), +(1747,3,NULL,'Spline and piecewise polynomial approximation',NULL,1347,1348,1736,1,1), +(1748,3,NULL,'Wavelets and fractals (NEW)',NULL,1349,1350,1736,1,1), +(1749,3,'G.1.3','Numerical Linear Algebra','G.1.3',1352,1371,1082,1,1), +(1750,3,NULL,'Conditioning',NULL,1353,1354,1749,1,1), +(1751,3,NULL,'Determinants**',NULL,1355,1356,1749,1,1), +(1752,3,NULL,'Eigenvalues and eigenvectors (direct and iterative methods) (REVISED)',NULL,1357,1358,1749,1,1), +(1753,3,NULL,'Error analysis',NULL,1359,1360,1749,1,1), +(1754,3,NULL,'Linear systems (direct and iterative methods)',NULL,1361,1362,1749,1,1), +(1755,3,NULL,'Matrix inversion',NULL,1363,1364,1749,1,1), +(1756,3,NULL,'Pseudoinverses**',NULL,1365,1366,1749,1,1), +(1757,3,NULL,'Singular value decomposition (NEW)',NULL,1367,1368,1749,1,1), +(1758,3,NULL,'Sparse, structured, and very large systems (direct and iterative methods) (REVISED)',NULL,1369,1370,1749,1,1), +(1759,3,'G.1.4','Quadrature and Numerical Differentiation (F.2.1)','G.1.4',1372,1389,1082,1,1), +(1760,3,NULL,'Adaptive and iterative quadrature (REVISED)',NULL,1373,1374,1759,1,1), +(1761,3,NULL,'Automatic differentiation (NEW)',NULL,1375,1376,1759,1,1), +(1762,3,NULL,'Equal interval integration**',NULL,1377,1378,1759,1,1), +(1763,3,NULL,'Error analysis',NULL,1379,1380,1759,1,1), +(1764,3,NULL,'Finite difference methods',NULL,1381,1382,1759,1,1), +(1765,3,NULL,'Gaussian quadrature',NULL,1383,1384,1759,1,1), +(1766,3,NULL,'Iterative methods',NULL,1385,1386,1759,1,1), +(1767,3,NULL,'Multidimensional (multiple) quadrature (REVISED)',NULL,1387,1388,1759,1,1), +(1768,3,'G.1.5','Roots of Nonlinear Equations','G.1.5',1390,1403,1082,1,1), +(1769,3,NULL,'Continuation (homotopy) methods (NEW)',NULL,1391,1392,1768,1,1), +(1770,3,NULL,'Convergence',NULL,1393,1394,1768,1,1), +(1771,3,NULL,'Error analysis',NULL,1395,1396,1768,1,1), +(1772,3,NULL,'Iterative methods',NULL,1397,1398,1768,1,1), +(1773,3,NULL,'Polynomials, methods for',NULL,1399,1400,1768,1,1), +(1774,3,NULL,'Systems of equations',NULL,1401,1402,1768,1,1), +(1775,3,'G.1.6','Optimization','G.1.6',1404,1429,1082,1,1), +(1776,3,NULL,'Constrained optimization',NULL,1405,1406,1775,1,1), +(1777,3,NULL,'Convex programming (NEW)',NULL,1407,1408,1775,1,1), +(1778,3,NULL,'Global optimization (NEW)',NULL,1409,1410,1775,1,1), +(1779,3,NULL,'Gradient methods',NULL,1411,1412,1775,1,1), +(1780,3,NULL,'Integer programming',NULL,1413,1414,1775,1,1), +(1781,3,NULL,'Least squares methods',NULL,1415,1416,1775,1,1), +(1782,3,NULL,'Linear programming',NULL,1417,1418,1775,1,1), +(1783,3,NULL,'Nonlinear programming',NULL,1419,1420,1775,1,1), +(1784,3,NULL,'Quadratic programming methods (NEW)',NULL,1421,1422,1775,1,1), +(1785,3,NULL,'Simulated annealing (NEW)',NULL,1423,1424,1775,1,1), +(1786,3,NULL,'Stochastic programming (NEW)',NULL,1425,1426,1775,1,1), +(1787,3,NULL,'Unconstrained optimization (NEW)',NULL,1427,1428,1775,1,1), +(1788,3,'G.1.7','Ordinary Differential Equations','G.1.7',1430,1451,1082,1,1), +(1789,3,NULL,'Boundary value problems',NULL,1431,1432,1788,1,1), +(1790,3,NULL,'Chaotic systems (NEW)',NULL,1433,1434,1788,1,1), +(1791,3,NULL,'Convergence and stability',NULL,1435,1436,1788,1,1), +(1792,3,NULL,'Differential-algebraic equations (NEW)',NULL,1437,1438,1788,1,1), +(1793,3,NULL,'Error analysis',NULL,1439,1440,1788,1,1), +(1794,3,NULL,'Finite difference methods (NEW)',NULL,1441,1442,1788,1,1), +(1795,3,NULL,'Initial value problems',NULL,1443,1444,1788,1,1), +(1796,3,NULL,'Multistep and multivalue methods (REVISED)',NULL,1445,1446,1788,1,1), +(1797,3,NULL,'One-step (single step) methods (REVISED)',NULL,1447,1448,1788,1,1), +(1798,3,NULL,'Stiff equations',NULL,1449,1450,1788,1,1), +(1799,3,'G.1.8','Partial Differential Equations','G.1.8',1452,1477,1082,1,1), +(1800,3,NULL,'Domain decomposition methods (NEW)',NULL,1453,1454,1799,1,1), +(1801,3,NULL,'Elliptic equations',NULL,1455,1456,1799,1,1), +(1802,3,NULL,'Finite difference methods (REVISED)',NULL,1457,1458,1799,1,1), +(1803,3,NULL,'Finite element methods',NULL,1459,1460,1799,1,1), +(1804,3,NULL,'Finite volume methods (NEW)',NULL,1461,1462,1799,1,1), +(1805,3,NULL,'Hyperbolic equations',NULL,1463,1464,1799,1,1), +(1806,3,NULL,'Inverse problems (NEW)',NULL,1465,1466,1799,1,1), +(1807,3,NULL,'Iterative solution techniques (NEW)',NULL,1467,1468,1799,1,1), +(1808,3,NULL,'Method of lines',NULL,1469,1470,1799,1,1), +(1809,3,NULL,'Multigrid and multilevel methods (NEW)',NULL,1471,1472,1799,1,1), +(1810,3,NULL,'Parabolic equations',NULL,1473,1474,1799,1,1), +(1811,3,NULL,'Spectral methods (NEW)',NULL,1475,1476,1799,1,1), +(1812,3,'G.1.9','Integral Equations','G.1.9',1478,1487,1082,1,1), +(1813,3,NULL,'Delay equations (NEW)',NULL,1479,1480,1812,1,1), +(1814,3,NULL,'Fredholm equations',NULL,1481,1482,1812,1,1), +(1815,3,NULL,'Integro-differential equations',NULL,1483,1484,1812,1,1), +(1816,3,NULL,'Volterra equations',NULL,1485,1486,1812,1,1), +(1817,3,'G.1.m','Miscellaneous','G.1.m',1488,1489,1082,1,1), +(1818,3,'G.2.0','General','G.2.0',1492,1493,1083,1,1), +(1819,3,'G.2.1','Combinatorics (F.2.2)','G.2.1',1494,1505,1083,1,1), +(1820,3,NULL,'Combinatorial algorithms',NULL,1495,1496,1819,1,1), +(1821,3,NULL,'Counting problems',NULL,1497,1498,1819,1,1), +(1822,3,NULL,'Generating functions',NULL,1499,1500,1819,1,1), +(1823,3,NULL,'Permutations and combinations',NULL,1501,1502,1819,1,1), +(1824,3,NULL,'Recurrences and difference equations',NULL,1503,1504,1819,1,1), +(1825,3,'G.2.2','Graph Theory (F.2.2)','G.2.2',1506,1519,1083,1,1), +(1826,3,NULL,'Graph algorithms',NULL,1507,1508,1825,1,1), +(1827,3,NULL,'Graph labeling (NEW)',NULL,1509,1510,1825,1,1), +(1828,3,NULL,'Hypergraphs (NEW)',NULL,1511,1512,1825,1,1), +(1829,3,NULL,'Network problems',NULL,1513,1514,1825,1,1), +(1830,3,NULL,'Path and circuit problems',NULL,1515,1516,1825,1,1), +(1831,3,NULL,'Trees',NULL,1517,1518,1825,1,1), +(1832,3,'G.2.3','Applications (NEW)','G.2.3',1520,1521,1083,1,1), +(1833,3,'G.2.m','Miscellaneous','G.2.m',1522,1523,1083,1,1), +(1834,3,NULL,'Contingency table analysis (NEW)',NULL,1526,1527,1084,1,1), +(1835,3,NULL,'Correlation and regression analysis (NEW)',NULL,1528,1529,1084,1,1), +(1836,3,NULL,'Distribution functions (NEW)',NULL,1530,1531,1084,1,1), +(1837,3,NULL,'Experimental design (NEW)',NULL,1532,1533,1084,1,1), +(1838,3,NULL,'Markov processes (NEW)',NULL,1534,1535,1084,1,1), +(1839,3,NULL,'Multivariate statistics (NEW)',NULL,1536,1537,1084,1,1), +(1840,3,NULL,'Nonparametric statistics (NEW)',NULL,1538,1539,1084,1,1), +(1841,3,NULL,'Probabilistic algorithms (including Monte Carlo)',NULL,1540,1541,1084,1,1), +(1842,3,NULL,'Queueing theory (NEW)',NULL,1542,1543,1084,1,1), +(1843,3,NULL,'Random number generation',NULL,1544,1545,1084,1,1), +(1844,3,NULL,'Reliability and life testing (NEW)',NULL,1546,1547,1084,1,1), +(1845,3,NULL,'Renewal theory (NEW)',NULL,1548,1549,1084,1,1), +(1846,3,NULL,'Robust regression (NEW)',NULL,1550,1551,1084,1,1), +(1847,3,NULL,'Statistical computing',NULL,1552,1553,1084,1,1), +(1848,3,NULL,'Statistical software',NULL,1554,1555,1084,1,1), +(1849,3,NULL,'Stochastic processes (NEW)',NULL,1556,1557,1084,1,1), +(1850,3,NULL,'Survival analysis (NEW)',NULL,1558,1559,1084,1,1), +(1851,3,NULL,'Time series analysis (NEW)',NULL,1560,1561,1084,1,1), +(1852,3,NULL,'Algorithm design and analysis (REVISED)',NULL,1564,1565,1085,1,1), +(1853,3,NULL,'Certification and testing',NULL,1566,1567,1085,1,1), +(1854,3,NULL,'Documentation (NEW)',NULL,1568,1569,1085,1,1), +(1855,3,NULL,'Efficiency',NULL,1570,1571,1085,1,1), +(1856,3,NULL,'Parallel and vector implementations (NEW)',NULL,1572,1573,1085,1,1), +(1857,3,NULL,'Portability**',NULL,1574,1575,1085,1,1), +(1858,3,NULL,'Reliability and robustness',NULL,1576,1577,1085,1,1), +(1859,3,NULL,'User interfaces (NEW)',NULL,1578,1579,1085,1,1), +(1860,3,NULL,'Verification**',NULL,1580,1581,1085,1,1), +(1861,3,NULL,'Queueing theory**',NULL,1584,1585,1086,1,1), +(1862,3,'H.1.0','General','H.1.0',1592,1593,1088,1,1), +(1863,3,'H.1.1','Systems and Information Theory (E.4)','H.1.1',1594,1601,1088,1,1), +(1864,3,NULL,'General systems theory',NULL,1595,1596,1863,1,1), +(1865,3,NULL,'Information theory',NULL,1597,1598,1863,1,1), +(1866,3,NULL,'Value of information',NULL,1599,1600,1863,1,1), +(1867,3,'H.1.2','User/Machine Systems','H.1.2',1602,1609,1088,1,1), +(1868,3,NULL,'Human factors',NULL,1603,1604,1867,1,1), +(1869,3,NULL,'Human information processing',NULL,1605,1606,1867,1,1), +(1870,3,NULL,'Software psychology (NEW)',NULL,1607,1608,1867,1,1), +(1871,3,'H.1.m','Miscellaneous','H.1.m',1610,1611,1088,1,1), +(1872,3,'H.2.0','General','H.2.0',1614,1617,1089,1,1), +(1873,3,NULL,'Security, integrity, and protection**',NULL,1615,1616,1872,1,1), +(1874,3,'H.2.1','Logical Design','H.2.1',1618,1625,1089,1,1), +(1875,3,NULL,'Data models',NULL,1619,1620,1874,1,1), +(1876,3,NULL,'Normal forms',NULL,1621,1622,1874,1,1), +(1877,3,NULL,'Schema and subschema',NULL,1623,1624,1874,1,1), +(1878,3,'H.2.2','Physical Design','H.2.2',1626,1633,1089,1,1), +(1879,3,NULL,'Access methods',NULL,1627,1628,1878,1,1), +(1880,3,NULL,'Deadlock avoidance',NULL,1629,1630,1878,1,1), +(1881,3,NULL,'Recovery and restart',NULL,1631,1632,1878,1,1), +(1882,3,'H.2.3','Languages (D.3.2)','H.2.3',1634,1645,1089,1,1), +(1883,3,NULL,'Data description languages (DDL)',NULL,1635,1636,1882,1,1), +(1884,3,NULL,'Data manipulation languages (DML)',NULL,1637,1638,1882,1,1), +(1885,3,NULL,'Database (persistent) programming languages',NULL,1639,1640,1882,1,1), +(1886,3,NULL,'Query languages',NULL,1641,1642,1882,1,1), +(1887,3,NULL,'Report writers',NULL,1643,1644,1882,1,1), +(1888,3,'H.2.4','Systems','H.2.4',1646,1667,1089,1,1), +(1889,3,NULL,'Concurrency',NULL,1647,1648,1888,1,1), +(1890,3,NULL,'Distributed databases (REVISED)',NULL,1649,1650,1888,1,1), +(1891,3,NULL,'Multimedia databases (NEW)',NULL,1651,1652,1888,1,1), +(1892,3,NULL,'Object-oriented databases (NEW)',NULL,1653,1654,1888,1,1), +(1893,3,NULL,'Parallel databases (NEW)',NULL,1655,1656,1888,1,1), +(1894,3,NULL,'Query processing',NULL,1657,1658,1888,1,1), +(1895,3,NULL,'Relational databases (NEW)',NULL,1659,1660,1888,1,1), +(1896,3,NULL,'Rule-based databases (NEW)',NULL,1661,1662,1888,1,1), +(1897,3,NULL,'Textual databases (NEW)',NULL,1663,1664,1888,1,1), +(1898,3,NULL,'Transaction processing',NULL,1665,1666,1888,1,1), +(1899,3,'H.2.5','Heterogeneous Databases','H.2.5',1668,1673,1089,1,1), +(1900,3,NULL,'Data translation**',NULL,1669,1670,1899,1,1), +(1901,3,NULL,'Program translation**',NULL,1671,1672,1899,1,1), +(1902,3,'H.2.6','Database Machines','H.2.6',1674,1675,1089,1,1), +(1903,3,'H.2.7','Database Administration','H.2.7',1676,1685,1089,1,1), +(1904,3,NULL,'Data dictionary/directory',NULL,1677,1678,1903,1,1), +(1905,3,NULL,'Data warehouse and repository (NEW)',NULL,1679,1680,1903,1,1), +(1906,3,NULL,'Logging and recovery',NULL,1681,1682,1903,1,1), +(1907,3,NULL,'Security, integrity, and protection (NEW)',NULL,1683,1684,1903,1,1), +(1908,3,'H.2.8','Database Applications','H.2.8',1686,1697,1089,1,1), +(1909,3,NULL,'Data mining (NEW)',NULL,1687,1688,1908,1,1), +(1910,3,NULL,'Image databases (NEW)',NULL,1689,1690,1908,1,1), +(1911,3,NULL,'Scientific databases (NEW)',NULL,1691,1692,1908,1,1), +(1912,3,NULL,'Spatial databases and GIS (NEW)',NULL,1693,1694,1908,1,1), +(1913,3,NULL,'Statistical databases (NEW)',NULL,1695,1696,1908,1,1), +(1914,3,'H.2.m','Miscellaneous','H.2.m',1698,1699,1089,1,1), +(1915,3,'H.3.0','General','H.3.0',1702,1703,1090,1,1), +(1916,3,'H.3.1','Content Analysis and Indexing','H.3.1',1704,1715,1090,1,1), +(1917,3,NULL,'Abstracting methods',NULL,1705,1706,1916,1,1), +(1918,3,NULL,'Dictionaries',NULL,1707,1708,1916,1,1), +(1919,3,NULL,'Indexing methods',NULL,1709,1710,1916,1,1), +(1920,3,NULL,'Linguistic processing',NULL,1711,1712,1916,1,1), +(1921,3,NULL,'Thesauruses',NULL,1713,1714,1916,1,1), +(1922,3,'H.3.2','Information Storage','H.3.2',1716,1721,1090,1,1), +(1923,3,NULL,'File organization',NULL,1717,1718,1922,1,1), +(1924,3,NULL,'Record classification**',NULL,1719,1720,1922,1,1), +(1925,3,'H.3.3','Information Search and Retrieval','H.3.3',1722,1737,1090,1,1), +(1926,3,NULL,'Clustering',NULL,1723,1724,1925,1,1), +(1927,3,NULL,'Information filtering (NEW)',NULL,1725,1726,1925,1,1), +(1928,3,NULL,'Query formulation',NULL,1727,1728,1925,1,1), +(1929,3,NULL,'Relevance feedback (NEW)',NULL,1729,1730,1925,1,1), +(1930,3,NULL,'Retrieval models',NULL,1731,1732,1925,1,1), +(1931,3,NULL,'Search process',NULL,1733,1734,1925,1,1), +(1932,3,NULL,'Selection process',NULL,1735,1736,1925,1,1), +(1933,3,'H.3.4','Systems and Software','H.3.4',1738,1751,1090,1,1), +(1934,3,NULL,'Current awareness systems (selective dissemination of information--SDI)**',NULL,1739,1740,1933,1,1), +(1935,3,NULL,'Distributed systems (NEW)',NULL,1741,1742,1933,1,1), +(1936,3,NULL,'Information networks',NULL,1743,1744,1933,1,1), +(1937,3,NULL,'Performance evaluation (efficiency and effectiveness) (NEW)',NULL,1745,1746,1933,1,1), +(1938,3,NULL,'Question-answering (fact retrieval) systems**',NULL,1747,1748,1933,1,1), +(1939,3,NULL,'User profiles and alert services (NEW)',NULL,1749,1750,1933,1,1), +(1940,3,'H.3.5','Online Information Services','H.3.5',1752,1759,1090,1,1), +(1941,3,NULL,'Commercial services (NEW)',NULL,1753,1754,1940,1,1), +(1942,3,NULL,'Data sharing (REVISED)',NULL,1755,1756,1940,1,1), +(1943,3,NULL,'Web-based services (NEW)',NULL,1757,1758,1940,1,1), +(1944,3,'H.3.6','Library Automation','H.3.6',1760,1763,1090,1,1), +(1945,3,NULL,'Large text archives',NULL,1761,1762,1944,1,1), +(1946,3,'H.3.7','Digital Libraries (NEW)','H.3.7',1764,1775,1090,1,1), +(1947,3,NULL,'Collection (NEW)',NULL,1765,1766,1946,1,1), +(1948,3,NULL,'Dissemination (NEW)',NULL,1767,1768,1946,1,1), +(1949,3,NULL,'Standards (NEW)',NULL,1769,1770,1946,1,1), +(1950,3,NULL,'Systems issues (NEW)',NULL,1771,1772,1946,1,1), +(1951,3,NULL,'User issues (NEW)',NULL,1773,1774,1946,1,1), +(1952,3,'H.3.m','Miscellaneous','H.3.m',1776,1777,1090,1,1), +(1953,3,'H.4.0','General','H.4.0',1780,1781,1091,1,1), +(1954,3,'H.4.1','Office Automation (I.7)','H.4.1',1782,1797,1091,1,1), +(1955,3,NULL,'Desktop publishing (NEW)',NULL,1783,1784,1954,1,1), +(1956,3,NULL,'Equipment**',NULL,1785,1786,1954,1,1), +(1957,3,NULL,'Groupware (NEW)',NULL,1787,1788,1954,1,1), +(1958,3,NULL,'Spreadsheets',NULL,1789,1790,1954,1,1), +(1959,3,NULL,'Time management (e.g., calendars, schedules)',NULL,1791,1792,1954,1,1), +(1960,3,NULL,'Word processing',NULL,1793,1794,1954,1,1), +(1961,3,NULL,'Workflow management (NEW)',NULL,1795,1796,1954,1,1), +(1962,3,'H.4.2','Types of Systems','H.4.2',1798,1803,1091,1,1), +(1963,3,NULL,'Decision support (e.g., MIS)',NULL,1799,1800,1962,1,1), +(1964,3,NULL,'Logistics',NULL,1801,1802,1962,1,1), +(1965,3,'H.4.3','Communications Applications','H.4.3',1804,1815,1091,1,1), +(1966,3,NULL,'Bulletin boards',NULL,1805,1806,1965,1,1), +(1967,3,NULL,'Computer conferencing, teleconferencing, and videoconferencing (REVISED)',NULL,1807,1808,1965,1,1), +(1968,3,NULL,'Electronic mail',NULL,1809,1810,1965,1,1), +(1969,3,NULL,'Information browsers (NEW)',NULL,1811,1812,1965,1,1), +(1970,3,NULL,'Videotex',NULL,1813,1814,1965,1,1), +(1971,3,'H.4.m','Miscellaneous','H.4.m',1816,1817,1091,1,1), +(1972,3,'H.5.0','General','H.5.0',1820,1821,1092,1,1), +(1973,3,'H.5.1','Multimedia Information Systems','H.5.1',1822,1835,1092,1,1), +(1974,3,NULL,'Animations',NULL,1823,1824,1973,1,1), +(1975,3,NULL,'Artificial, augmented, and virtual realities (REVISED)',NULL,1825,1826,1973,1,1), +(1976,3,NULL,'Audio input/output',NULL,1827,1828,1973,1,1), +(1977,3,NULL,'Evaluation/methodology',NULL,1829,1830,1973,1,1), +(1978,3,NULL,'Hypertext navigation and maps**',NULL,1831,1832,1973,1,1), +(1979,3,NULL,'Video (e.g., tape, disk, DVI)',NULL,1833,1834,1973,1,1), +(1980,3,'H.5.2','User Interfaces (D.2.2, H.1.2, I.3.6)','H.5.2',1836,1875,1092,1,1), +(1981,3,NULL,'Auditory (non-speech) feedback (NEW)',NULL,1837,1838,1980,1,1), +(1982,3,NULL,'Benchmarking (NEW)',NULL,1839,1840,1980,1,1), +(1983,3,NULL,'Ergonomics',NULL,1841,1842,1980,1,1), +(1984,3,NULL,'Evaluation/methodology',NULL,1843,1844,1980,1,1), +(1985,3,NULL,'Graphical user interfaces (GUI) (NEW)',NULL,1845,1846,1980,1,1), +(1986,3,NULL,'Haptic I/O (NEW)',NULL,1847,1848,1980,1,1), +(1987,3,NULL,'Input devices and strategies (e.g., mouse, touchscreen)',NULL,1849,1850,1980,1,1), +(1988,3,NULL,'Interaction styles (e.g., commands, menus, forms, direct manipulation)',NULL,1851,1852,1980,1,1), +(1989,3,NULL,'Natural language (NEW)',NULL,1853,1854,1980,1,1), +(1990,3,NULL,'Prototyping (NEW)',NULL,1855,1856,1980,1,1), +(1991,3,NULL,'Screen design (e.g., text, graphics, color)',NULL,1857,1858,1980,1,1), +(1992,3,NULL,'Standardization (NEW)',NULL,1859,1860,1980,1,1), +(1993,3,NULL,'Style guides (NEW)',NULL,1861,1862,1980,1,1), +(1994,3,NULL,'Theory and methods',NULL,1863,1864,1980,1,1), +(1995,3,NULL,'Training, help, and documentation',NULL,1865,1866,1980,1,1), +(1996,3,NULL,'User-centered design (NEW)',NULL,1867,1868,1980,1,1), +(1997,3,NULL,'User interface management systems (UIMS)',NULL,1869,1870,1980,1,1), +(1998,3,NULL,'Voice I/O (NEW)',NULL,1871,1872,1980,1,1), +(1999,3,NULL,'Windowing systems',NULL,1873,1874,1980,1,1), +(2000,3,'H.5.3','Group and Organization Interfaces','H.5.3',1876,1893,1092,1,1), +(2001,3,NULL,'Asynchronous interaction',NULL,1877,1878,2000,1,1), +(2002,3,NULL,'Collaborative computing (NEW)',NULL,1879,1880,2000,1,1), +(2003,3,NULL,'Computer-supported cooperative work (NEW)',NULL,1881,1882,2000,1,1), +(2004,3,NULL,'Evaluation/methodology',NULL,1883,1884,2000,1,1), +(2005,3,NULL,'Organizational design',NULL,1885,1886,2000,1,1), +(2006,3,NULL,'Synchronous interaction',NULL,1887,1888,2000,1,1), +(2007,3,NULL,'Theory and models',NULL,1889,1890,2000,1,1), +(2008,3,NULL,'Web-based interaction (NEW)',NULL,1891,1892,2000,1,1), +(2009,3,'H.5.4','Hypertext/Hypermedia (I.7, J.7) (NEW)','H.5.4',1894,1903,1092,1,1), +(2010,3,NULL,'Architectures (NEW)',NULL,1895,1896,2009,1,1), +(2011,3,NULL,'Navigation (NEW)',NULL,1897,1898,2009,1,1), +(2012,3,NULL,'Theory (NEW)',NULL,1899,1900,2009,1,1), +(2013,3,NULL,'User issues (NEW)',NULL,1901,1902,2009,1,1), +(2014,3,'H.5.5','Sound and Music Computing (J.5) (NEW)','H.5.5',1904,1913,1092,1,1), +(2015,3,NULL,'Methodologies and techniques (NEW)',NULL,1905,1906,2014,1,1), +(2016,3,NULL,'Modeling (NEW)',NULL,1907,1908,2014,1,1), +(2017,3,NULL,'Signal analysis, synthesis, and processing (NEW)',NULL,1909,1910,2014,1,1), +(2018,3,NULL,'Systems (NEW)',NULL,1911,1912,2014,1,1), +(2019,3,'H.5.m','Miscellaneous (NEW)','H.5.m',1914,1915,1092,1,1), +(2020,3,'I.1.0','General','I.1.0',1924,1925,1095,1,1), +(2021,3,'I.1.1','Expressions and Their Representation (E.1-2)','I.1.1',1926,1931,1095,1,1), +(2022,3,NULL,'Representations (general and polynomial)',NULL,1927,1928,2021,1,1), +(2023,3,NULL,'Simplification of expressions',NULL,1929,1930,2021,1,1), +(2024,3,'I.1.2','Algorithms (F.2.1-2)','I.1.2',1932,1939,1095,1,1), +(2025,3,NULL,'Algebraic algorithms',NULL,1933,1934,2024,1,1), +(2026,3,NULL,'Analysis of algorithms',NULL,1935,1936,2024,1,1), +(2027,3,NULL,'Nonalgebraic algorithms',NULL,1937,1938,2024,1,1), +(2028,3,'I.1.3','Languages and Systems (D.3.2-3, F.2.2)','I.1.3',1940,1951,1095,1,1), +(2029,3,NULL,'Evaluation strategies',NULL,1941,1942,2028,1,1), +(2030,3,NULL,'Nonprocedural languages**',NULL,1943,1944,2028,1,1), +(2031,3,NULL,'Special-purpose algebraic systems',NULL,1945,1946,2028,1,1), +(2032,3,NULL,'Special-purpose hardware**',NULL,1947,1948,2028,1,1), +(2033,3,NULL,'Substitution mechanisms**',NULL,1949,1950,2028,1,1), +(2034,3,'I.1.4','Applications','I.1.4',1952,1953,1095,1,1), +(2035,3,'I.1.m','Miscellaneous','I.1.m',1954,1955,1095,1,1), +(2036,3,'I.2.0','General','I.2.0',1958,1963,1096,1,1), +(2037,3,NULL,'Cognitive simulation',NULL,1959,1960,2036,1,1), +(2038,3,NULL,'Philosophical foundations',NULL,1961,1962,2036,1,1), +(2039,3,'I.2.1','Applications and Expert Systems (H.4, J)','I.2.1',1964,1979,1096,1,1), +(2040,3,NULL,'Cartography',NULL,1965,1966,2039,1,1), +(2041,3,NULL,'Games',NULL,1967,1968,2039,1,1), +(2042,3,NULL,'Industrial automation',NULL,1969,1970,2039,1,1), +(2043,3,NULL,'Law',NULL,1971,1972,2039,1,1), +(2044,3,NULL,'Medicine and science',NULL,1973,1974,2039,1,1), +(2045,3,NULL,'Natural language interfaces',NULL,1975,1976,2039,1,1), +(2046,3,NULL,'Office automation',NULL,1977,1978,2039,1,1), +(2047,3,'I.2.2','Automatic Programming (D.1.2, F.3.1, F.4.1)','I.2.2',1980,1991,1096,1,1), +(2048,3,NULL,'Automatic analysis of algorithms',NULL,1981,1982,2047,1,1), +(2049,3,NULL,'Program modification',NULL,1983,1984,2047,1,1), +(2050,3,NULL,'Program synthesis',NULL,1985,1986,2047,1,1), +(2051,3,NULL,'Program transformation',NULL,1987,1988,2047,1,1), +(2052,3,NULL,'Program verification',NULL,1989,1990,2047,1,1), +(2053,3,'I.2.3','Deduction and Theorem Proving (F.4.1)','I.2.3',1992,2009,1096,1,1), +(2054,3,NULL,'Answer/reason extraction',NULL,1993,1994,2053,1,1), +(2055,3,NULL,'Deduction (e.g., natural, rule-based)',NULL,1995,1996,2053,1,1), +(2056,3,NULL,'Inference engines (NEW)',NULL,1997,1998,2053,1,1), +(2057,3,NULL,'Logic programming',NULL,1999,2000,2053,1,1), +(2058,3,NULL,'Mathematical induction',NULL,2001,2002,2053,1,1), +(2059,3,NULL,'Metatheory**',NULL,2003,2004,2053,1,1), +(2060,3,NULL,'Nonmonotonic reasoning and belief revision',NULL,2005,2006,2053,1,1), +(2061,3,NULL,'Resolution',NULL,2007,2008,2053,1,1), +(2062,3,'I.2.4','Knowledge Representation Formalisms and Methods (F.4.1)','I.2.4',2010,2027,1096,1,1), +(2063,3,NULL,'Frames and scripts',NULL,2011,2012,2062,1,1), +(2064,3,NULL,'Modal logic (NEW)',NULL,2013,2014,2062,1,1), +(2065,3,NULL,'Predicate logic',NULL,2015,2016,2062,1,1), +(2066,3,NULL,'Relation systems',NULL,2017,2018,2062,1,1), +(2067,3,NULL,'Representation languages',NULL,2019,2020,2062,1,1), +(2068,3,NULL,'Representations (procedural and rule-based)',NULL,2021,2022,2062,1,1), +(2069,3,NULL,'Semantic networks',NULL,2023,2024,2062,1,1), +(2070,3,NULL,'Temporal logic (NEW)',NULL,2025,2026,2062,1,1), +(2071,3,'I.2.5','Programming Languages and Software (D.3.2)','I.2.5',2028,2031,1096,1,1), +(2072,3,NULL,'Expert system tools and techniques',NULL,2029,2030,2071,1,1), +(2073,3,'I.2.6','Learning (K.3.2)','I.2.6',2032,2047,1096,1,1), +(2074,3,NULL,'Analogies',NULL,2033,2034,2073,1,1), +(2075,3,NULL,'Concept learning',NULL,2035,2036,2073,1,1), +(2076,3,NULL,'Connectionism and neural nets',NULL,2037,2038,2073,1,1), +(2077,3,NULL,'Induction',NULL,2039,2040,2073,1,1), +(2078,3,NULL,'Knowledge acquisition',NULL,2041,2042,2073,1,1), +(2079,3,NULL,'Language acquisition',NULL,2043,2044,2073,1,1), +(2080,3,NULL,'Parameter learning',NULL,2045,2046,2073,1,1), +(2081,3,'I.2.7','Natural Language Processing','I.2.7',2048,2063,1096,1,1), +(2082,3,NULL,'Discourse',NULL,2049,2050,2081,1,1), +(2083,3,NULL,'Language generation',NULL,2051,2052,2081,1,1), +(2084,3,NULL,'Language models',NULL,2053,2054,2081,1,1), +(2085,3,NULL,'Language parsing and understanding',NULL,2055,2056,2081,1,1), +(2086,3,NULL,'Machine translation',NULL,2057,2058,2081,1,1), +(2087,3,NULL,'Speech recognition and synthesis',NULL,2059,2060,2081,1,1), +(2088,3,NULL,'Text analysis',NULL,2061,2062,2081,1,1), +(2089,3,'I.2.8','Problem Solving, Control Methods, and Search (F.2.2)','I.2.8',2064,2079,1096,1,1), +(2090,3,NULL,'Backtracking',NULL,2065,2066,2089,1,1), +(2091,3,NULL,'Control theory (NEW)',NULL,2067,2068,2089,1,1), +(2092,3,NULL,'Dynamic programming',NULL,2069,2070,2089,1,1), +(2093,3,NULL,'Graph and tree search strategies',NULL,2071,2072,2089,1,1), +(2094,3,NULL,'Heuristic methods',NULL,2073,2074,2089,1,1), +(2095,3,NULL,'Plan execution, formation, and generation',NULL,2075,2076,2089,1,1), +(2096,3,NULL,'Scheduling (NEW)',NULL,2077,2078,2089,1,1), +(2097,3,'I.2.9','Robotics','I.2.9',2080,2097,1096,1,1), +(2098,3,NULL,'Autonomous vehicles (NEW)',NULL,2081,2082,2097,1,1), +(2099,3,NULL,'Commercial robots and applications (NEW)',NULL,2083,2084,2097,1,1), +(2100,3,NULL,'Kinematics and dynamics (NEW)',NULL,2085,2086,2097,1,1), +(2101,3,NULL,'Manipulators',NULL,2087,2088,2097,1,1), +(2102,3,NULL,'Operator interfaces (NEW)',NULL,2089,2090,2097,1,1), +(2103,3,NULL,'Propelling mechanisms',NULL,2091,2092,2097,1,1), +(2104,3,NULL,'Sensors',NULL,2093,2094,2097,1,1), +(2105,3,NULL,'Workcell organization and planning (NEW)',NULL,2095,2096,2097,1,1), +(2106,3,'I.2.10','Vision and Scene Understanding (I.4.8, I.5)','I.2.10',2098,2119,1096,1,1), +(2107,3,NULL,'3D/stereo scene analysis (NEW)',NULL,2099,2100,2106,1,1), +(2108,3,NULL,'Architecture and control structures**',NULL,2101,2102,2106,1,1), +(2109,3,NULL,'Intensity, color, photometry, and thresholding',NULL,2103,2104,2106,1,1), +(2110,3,NULL,'Modeling and recovery of physical attributes',NULL,2105,2106,2106,1,1), +(2111,3,NULL,'Motion',NULL,2107,2108,2106,1,1), +(2112,3,NULL,'Perceptual reasoning',NULL,2109,2110,2106,1,1), +(2113,3,NULL,'Representations, data structures, and transforms',NULL,2111,2112,2106,1,1), +(2114,3,NULL,'Shape',NULL,2113,2114,2106,1,1), +(2115,3,NULL,'Texture',NULL,2115,2116,2106,1,1), +(2116,3,NULL,'Video analysis (NEW)',NULL,2117,2118,2106,1,1), +(2117,3,'I.2.11','Distributed Artificial Intelligence','I.2.11',2120,2129,1096,1,1), +(2118,3,NULL,'Coherence and coordination',NULL,2121,2122,2117,1,1), +(2119,3,NULL,'Intelligent agents (NEW)',NULL,2123,2124,2117,1,1), +(2120,3,NULL,'Languages and structures',NULL,2125,2126,2117,1,1), +(2121,3,NULL,'Multiagent systems (NEW)',NULL,2127,2128,2117,1,1), +(2122,3,'I.2.m','Miscellaneous','I.2.m',2130,2131,1096,1,1), +(2123,3,'I.3.0','General','I.3.0',2134,2135,1097,1,1), +(2124,3,'I.3.1','Hardware Architecture (B.4.2)','I.3.1',2136,2153,1097,1,1), +(2125,3,NULL,'Graphics processors',NULL,2137,2138,2124,1,1), +(2126,3,NULL,'Hardcopy devices**',NULL,2139,2140,2124,1,1), +(2127,3,NULL,'Input devices',NULL,2141,2142,2124,1,1), +(2128,3,NULL,'Parallel processing',NULL,2143,2144,2124,1,1), +(2129,3,NULL,'Raster display devices',NULL,2145,2146,2124,1,1), +(2130,3,NULL,'Storage devices**',NULL,2147,2148,2124,1,1), +(2131,3,NULL,'Three-dimensional displays**',NULL,2149,2150,2124,1,1), +(2132,3,NULL,'Vector display devices**',NULL,2151,2152,2124,1,1), +(2133,3,'I.3.2','Graphics Systems (C.2.1, C.2.4, C.3)','I.3.2',2154,2161,1097,1,1), +(2134,3,NULL,'Distributed/network graphics',NULL,2155,2156,2133,1,1), +(2135,3,NULL,'Remote systems**',NULL,2157,2158,2133,1,1), +(2136,3,NULL,'Stand-alone systems**',NULL,2159,2160,2133,1,1), +(2137,3,'I.3.3','Picture/Image Generation','I.3.3',2162,2175,1097,1,1), +(2138,3,NULL,'Antialiasing**',NULL,2163,2164,2137,1,1), +(2139,3,NULL,'Bitmap and framebuffer operations',NULL,2165,2166,2137,1,1), +(2140,3,NULL,'Digitizing and scanning',NULL,2167,2168,2137,1,1), +(2141,3,NULL,'Display algorithms',NULL,2169,2170,2137,1,1), +(2142,3,NULL,'Line and curve generation',NULL,2171,2172,2137,1,1), +(2143,3,NULL,'Viewing algorithms',NULL,2173,2174,2137,1,1), +(2144,3,'I.3.4','Graphics Utilities','I.3.4',2176,2195,1097,1,1), +(2145,3,NULL,'Application packages',NULL,2177,2178,2144,1,1), +(2146,3,NULL,'Device drivers**',NULL,2179,2180,2144,1,1), +(2147,3,NULL,'Graphics editors',NULL,2181,2182,2144,1,1), +(2148,3,NULL,'Graphics packages',NULL,2183,2184,2144,1,1), +(2149,3,NULL,'Meta files**',NULL,2185,2186,2144,1,1), +(2150,3,NULL,'Paint systems',NULL,2187,2188,2144,1,1), +(2151,3,NULL,'Picture description languages**',NULL,2189,2190,2144,1,1), +(2152,3,NULL,'Software support',NULL,2191,2192,2144,1,1), +(2153,3,NULL,'Virtual device interfaces',NULL,2193,2194,2144,1,1), +(2154,3,'I.3.5','Computational Geometry and Object Modeling','I.3.5',2196,2215,1097,1,1), +(2155,3,NULL,'Boundary representations',NULL,2197,2198,2154,1,1), +(2156,3,NULL,'Constructive solid geometry (CSG)**',NULL,2199,2200,2154,1,1), +(2157,3,NULL,'Curve, surface, solid, and object representations',NULL,2201,2202,2154,1,1), +(2158,3,NULL,'Geometric algorithms, languages, and systems',NULL,2203,2204,2154,1,1), +(2159,3,NULL,'Hierarchy and geometric transformations',NULL,2205,2206,2154,1,1), +(2160,3,NULL,'Modeling packages',NULL,2207,2208,2154,1,1), +(2161,3,NULL,'Object hierarchies',NULL,2209,2210,2154,1,1), +(2162,3,NULL,'Physically based modeling',NULL,2211,2212,2154,1,1), +(2163,3,NULL,'Splines',NULL,2213,2214,2154,1,1), +(2164,3,'I.3.6','Methodology and Techniques','I.3.6',2216,2229,1097,1,1), +(2165,3,NULL,'Device independence**',NULL,2217,2218,2164,1,1), +(2166,3,NULL,'Ergonomics',NULL,2219,2220,2164,1,1), +(2167,3,NULL,'Graphics data structures and data types',NULL,2221,2222,2164,1,1), +(2168,3,NULL,'Interaction techniques',NULL,2223,2224,2164,1,1), +(2169,3,NULL,'Languages',NULL,2225,2226,2164,1,1), +(2170,3,NULL,'Standards',NULL,2227,2228,2164,1,1), +(2171,3,'I.3.7','Three-Dimensional Graphics and Realism','I.3.7',2230,2247,1097,1,1), +(2172,3,NULL,'Animation',NULL,2231,2232,2171,1,1), +(2173,3,NULL,'Color, shading, shadowing, and texture',NULL,2233,2234,2171,1,1), +(2174,3,NULL,'Fractals',NULL,2235,2236,2171,1,1), +(2175,3,NULL,'Hidden line/surface removal',NULL,2237,2238,2171,1,1), +(2176,3,NULL,'Radiosity',NULL,2239,2240,2171,1,1), +(2177,3,NULL,'Raytracing',NULL,2241,2242,2171,1,1), +(2178,3,NULL,'Virtual reality',NULL,2243,2244,2171,1,1), +(2179,3,NULL,'Visible line/surface algorithms',NULL,2245,2246,2171,1,1), +(2180,3,'I.3.8','Applications','I.3.8',2248,2249,1097,1,1), +(2181,3,'I.3.m','Miscellaneous','I.3.m',2250,2251,1097,1,1), +(2182,3,'I.4.0','General','I.4.0',2254,2259,1098,1,1), +(2183,3,NULL,'Image displays',NULL,2255,2256,2182,1,1), +(2184,3,NULL,'Image processing software',NULL,2257,2258,2182,1,1), +(2185,3,'I.4.1','Digitization and Image Capture (REVISED)','I.4.1',2260,2275,1098,1,1), +(2186,3,NULL,'Camera calibration (NEW)',NULL,2261,2262,2185,1,1), +(2187,3,NULL,'Imaging geometry (NEW)',NULL,2263,2264,2185,1,1), +(2188,3,NULL,'Quantization',NULL,2265,2266,2185,1,1), +(2189,3,NULL,'Radiometry (NEW)',NULL,2267,2268,2185,1,1), +(2190,3,NULL,'Reflectance (NEW)',NULL,2269,2270,2185,1,1), +(2191,3,NULL,'Sampling',NULL,2271,2272,2185,1,1), +(2192,3,NULL,'Scanning',NULL,2273,2274,2185,1,1), +(2193,3,'I.4.2','Compression (Coding) (E.4)','I.4.2',2276,2281,1098,1,1), +(2194,3,NULL,'Approximate methods',NULL,2277,2278,2193,1,1), +(2195,3,NULL,'Exact coding**',NULL,2279,2280,2193,1,1), +(2196,3,'I.4.3','Enhancement','I.4.3',2282,2295,1098,1,1), +(2197,3,NULL,'Filtering',NULL,2283,2284,2196,1,1), +(2198,3,NULL,'Geometric correction',NULL,2285,2286,2196,1,1), +(2199,3,NULL,'Grayscale manipulation',NULL,2287,2288,2196,1,1), +(2200,3,NULL,'Registration',NULL,2289,2290,2196,1,1), +(2201,3,NULL,'Sharpening and deblurring**',NULL,2291,2292,2196,1,1), +(2202,3,NULL,'Smoothing',NULL,2293,2294,2196,1,1), +(2203,3,'I.4.4','Restoration','I.4.4',2296,2305,1098,1,1), +(2204,3,NULL,'Inverse filtering**',NULL,2297,2298,2203,1,1), +(2205,3,NULL,'Kalman filtering',NULL,2299,2300,2203,1,1), +(2206,3,NULL,'Pseudoinverse restoration**',NULL,2301,2302,2203,1,1), +(2207,3,NULL,'Wiener filtering**',NULL,2303,2304,2203,1,1), +(2208,3,'I.4.5','Reconstruction','I.4.5',2306,2313,1098,1,1), +(2209,3,NULL,'Series expansion methods',NULL,2307,2308,2208,1,1), +(2210,3,NULL,'Summation methods**',NULL,2309,2310,2208,1,1), +(2211,3,NULL,'Transform methods',NULL,2311,2312,2208,1,1), +(2212,3,'I.4.6','Segmentation','I.4.6',2314,2323,1098,1,1), +(2213,3,NULL,'Edge and feature detection',NULL,2315,2316,2212,1,1), +(2214,3,NULL,'Pixel classification',NULL,2317,2318,2212,1,1), +(2215,3,NULL,'Region growing, partitioning',NULL,2319,2320,2212,1,1), +(2216,3,NULL,'Relaxation (NEW)',NULL,2321,2322,2212,1,1), +(2217,3,'I.4.7','Feature Measurement','I.4.7',2324,2337,1098,1,1), +(2218,3,NULL,'Feature representation (NEW)',NULL,2325,2326,2217,1,1), +(2219,3,NULL,'Invariants',NULL,2327,2328,2217,1,1), +(2220,3,NULL,'Moments',NULL,2329,2330,2217,1,1), +(2221,3,NULL,'Projections',NULL,2331,2332,2217,1,1), +(2222,3,NULL,'Size and shape',NULL,2333,2334,2217,1,1), +(2223,3,NULL,'Texture',NULL,2335,2336,2217,1,1), +(2224,3,'I.4.8','Scene Analysis','I.4.8',2338,2365,1098,1,1), +(2225,3,NULL,'Color (NEW)',NULL,2339,2340,2224,1,1), +(2226,3,NULL,'Depth cues',NULL,2341,2342,2224,1,1), +(2227,3,NULL,'Motion (NEW)',NULL,2343,2344,2224,1,1), +(2228,3,NULL,'Object recognition (NEW)',NULL,2345,2346,2224,1,1), +(2229,3,NULL,'Photometry',NULL,2347,2348,2224,1,1), +(2230,3,NULL,'Range data',NULL,2349,2350,2224,1,1), +(2231,3,NULL,'Sensor fusion',NULL,2351,2352,2224,1,1), +(2232,3,NULL,'Shading (NEW)',NULL,2353,2354,2224,1,1), +(2233,3,NULL,'Shape (NEW)',NULL,2355,2356,2224,1,1), +(2234,3,NULL,'Stereo',NULL,2357,2358,2224,1,1), +(2235,3,NULL,'Surface fitting (NEW)',NULL,2359,2360,2224,1,1), +(2236,3,NULL,'Time-varying imagery',NULL,2361,2362,2224,1,1), +(2237,3,NULL,'Tracking (NEW)',NULL,2363,2364,2224,1,1), +(2238,3,'I.4.9','Applications','I.4.9',2366,2367,1098,1,1), +(2239,3,'I.4.10','Image Representation','I.4.10',2368,2379,1098,1,1), +(2240,3,NULL,'Hierarchical',NULL,2369,2370,2239,1,1), +(2241,3,NULL,'Morphological',NULL,2371,2372,2239,1,1), +(2242,3,NULL,'Multidimensional',NULL,2373,2374,2239,1,1), +(2243,3,NULL,'Statistical',NULL,2375,2376,2239,1,1), +(2244,3,NULL,'Volumetric',NULL,2377,2378,2239,1,1), +(2245,3,'I.4.m','Miscellaneous','I.4.m',2380,2381,1098,1,1), +(2246,3,'I.5.0','General','I.5.0',2384,2385,1099,1,1), +(2247,3,'I.5.1','Models','I.5.1',2386,2399,1099,1,1), +(2248,3,NULL,'Deterministic**',NULL,2387,2388,2247,1,1), +(2249,3,NULL,'Fuzzy set',NULL,2389,2390,2247,1,1), +(2250,3,NULL,'Geometric',NULL,2391,2392,2247,1,1), +(2251,3,NULL,'Neural nets',NULL,2393,2394,2247,1,1), +(2252,3,NULL,'Statistical',NULL,2395,2396,2247,1,1), +(2253,3,NULL,'Structural',NULL,2397,2398,2247,1,1), +(2254,3,'I.5.2','Design Methodology','I.5.2',2400,2407,1099,1,1), +(2255,3,NULL,'Classifier design and evaluation',NULL,2401,2402,2254,1,1), +(2256,3,NULL,'Feature evaluation and selection',NULL,2403,2404,2254,1,1), +(2257,3,NULL,'Pattern analysis',NULL,2405,2406,2254,1,1), +(2258,3,'I.5.3','Clustering','I.5.3',2408,2413,1099,1,1), +(2259,3,NULL,'Algorithms',NULL,2409,2410,2258,1,1), +(2260,3,NULL,'Similarity measures',NULL,2411,2412,2258,1,1), +(2261,3,'I.5.4','Applications','I.5.4',2414,2423,1099,1,1), +(2262,3,NULL,'Computer vision',NULL,2415,2416,2261,1,1), +(2263,3,NULL,'Signal processing',NULL,2417,2418,2261,1,1), +(2264,3,NULL,'Text processing',NULL,2419,2420,2261,1,1), +(2265,3,NULL,'Waveform analysis',NULL,2421,2422,2261,1,1), +(2266,3,'I.5.5','Implementation (C.3)','I.5.5',2424,2429,1099,1,1), +(2267,3,NULL,'Interactive systems',NULL,2425,2426,2266,1,1), +(2268,3,NULL,'Special architectures',NULL,2427,2428,2266,1,1), +(2269,3,'I.5.m','Miscellaneous','I.5.m',2430,2431,1099,1,1), +(2270,3,'I.6.0','General','I.6.0',2434,2435,1100,1,1), +(2271,3,'I.6.1','Simulation Theory','I.6.1',2436,2443,1100,1,1), +(2272,3,NULL,'Model classification',NULL,2437,2438,2271,1,1), +(2273,3,NULL,'Systems theory',NULL,2439,2440,2271,1,1), +(2274,3,NULL,'Types of simulation (continuous and discrete)*',NULL,2441,2442,2271,1,1), +(2275,3,'I.6.2','Simulation Languages','I.6.2',2444,2445,1100,1,1), +(2276,3,'I.6.3','Applications','I.6.3',2446,2447,1100,1,1), +(2277,3,'I.6.4','Model Validation and Analysis','I.6.4',2448,2449,1100,1,1), +(2278,3,'I.6.5','Model Development','I.6.5',2450,2453,1100,1,1), +(2279,3,NULL,'Modeling methodologies',NULL,2451,2452,2278,1,1), +(2280,3,'I.6.6','Simulation Output Analysis','I.6.6',2454,2455,1100,1,1), +(2281,3,'I.6.7','Simulation Support Systems','I.6.7',2456,2459,1100,1,1), +(2282,3,NULL,'Environments',NULL,2457,2458,2281,1,1), +(2283,3,'I.6.8','Types of Simulation','I.6.8',2460,2479,1100,1,1), +(2284,3,NULL,'Animation',NULL,2461,2462,2283,1,1), +(2285,3,NULL,'Combined',NULL,2463,2464,2283,1,1), +(2286,3,NULL,'Continuous',NULL,2465,2466,2283,1,1), +(2287,3,NULL,'Discrete event',NULL,2467,2468,2283,1,1), +(2288,3,NULL,'Distributed',NULL,2469,2470,2283,1,1), +(2289,3,NULL,'Gaming',NULL,2471,2472,2283,1,1), +(2290,3,NULL,'Monte Carlo',NULL,2473,2474,2283,1,1), +(2291,3,NULL,'Parallel',NULL,2475,2476,2283,1,1), +(2292,3,NULL,'Visual',NULL,2477,2478,2283,1,1), +(2293,3,'I.6.m','Miscellaneous','I.6.m',2480,2481,1100,1,1), +(2294,3,'I.7.0','General','I.7.0',2484,2485,1101,1,1), +(2295,3,'I.7.1','Document and Text Editing (REVISED)','I.7.1',2486,2495,1101,1,1), +(2296,3,NULL,'Document management (NEW)',NULL,2487,2488,2295,1,1), +(2297,3,NULL,'Languages**',NULL,2489,2490,2295,1,1), +(2298,3,NULL,'Spelling**',NULL,2491,2492,2295,1,1), +(2299,3,NULL,'Version control (NEW)',NULL,2493,2494,2295,1,1), +(2300,3,'I.7.2','Document Preparation','I.7.2',2496,2517,1101,1,1), +(2301,3,NULL,'Desktop publishing',NULL,2497,2498,2300,1,1), +(2302,3,NULL,'Format and notation',NULL,2499,2500,2300,1,1), +(2303,3,NULL,'Hypertext/hypermedia',NULL,2501,2502,2300,1,1), +(2304,3,NULL,'Index generation (NEW)',NULL,2503,2504,2300,1,1), +(2305,3,NULL,'Languages and systems',NULL,2505,2506,2300,1,1), +(2306,3,NULL,'Markup languages (NEW)',NULL,2507,2508,2300,1,1), +(2307,3,NULL,'Multi/mixed media',NULL,2509,2510,2300,1,1), +(2308,3,NULL,'Photocomposition/typesetting',NULL,2511,2512,2300,1,1), +(2309,3,NULL,'Scripting languages (NEW)',NULL,2513,2514,2300,1,1), +(2310,3,NULL,'Standards',NULL,2515,2516,2300,1,1), +(2311,3,'I.7.3','Index Generation**','I.7.3',2518,2519,1101,1,1), +(2312,3,'I.7.4','Electronic Publishing (H.5.4, J.7) (NEW)','I.7.4',2520,2521,1101,1,1), +(2313,3,'I.7.5','Document Capture (I.4.1) (NEW)','I.7.5',2522,2531,1101,1,1), +(2314,3,NULL,'Document analysis (NEW)',NULL,2523,2524,2313,1,1), +(2315,3,NULL,'Graphics recognition and interpretation (NEW)',NULL,2525,2526,2313,1,1), +(2316,3,NULL,'Optical character recognition (OCR) (NEW)',NULL,2527,2528,2313,1,1), +(2317,3,NULL,'Scanning (NEW)',NULL,2529,2530,2313,1,1), +(2318,3,'I.7.m','Miscellaneous','I.7.m',2532,2533,1101,1,1), +(2319,3,NULL,'Business',NULL,2542,2543,1104,1,1), +(2320,3,NULL,'Education',NULL,2544,2545,1104,1,1), +(2321,3,NULL,'Financial (e.g., EFTS)',NULL,2546,2547,1104,1,1), +(2322,3,NULL,'Government',NULL,2548,2549,1104,1,1), +(2323,3,NULL,'Law',NULL,2550,2551,1104,1,1), +(2324,3,NULL,'Manufacturing',NULL,2552,2553,1104,1,1), +(2325,3,NULL,'Marketing',NULL,2554,2555,1104,1,1), +(2326,3,NULL,'Military',NULL,2556,2557,1104,1,1), +(2327,3,NULL,'Aerospace',NULL,2560,2561,1105,1,1), +(2328,3,NULL,'Archaeology (NEW)',NULL,2562,2563,1105,1,1), +(2329,3,NULL,'Astronomy',NULL,2564,2565,1105,1,1), +(2330,3,NULL,'Chemistry',NULL,2566,2567,1105,1,1), +(2331,3,NULL,'Earth and atmospheric sciences',NULL,2568,2569,1105,1,1), +(2332,3,NULL,'Electronics',NULL,2570,2571,1105,1,1), +(2333,3,NULL,'Engineering',NULL,2572,2573,1105,1,1), +(2334,3,NULL,'Mathematics and statistics',NULL,2574,2575,1105,1,1), +(2335,3,NULL,'Physics',NULL,2576,2577,1105,1,1), +(2336,3,NULL,'Biology and genetics (REVISED)',NULL,2580,2581,1106,1,1), +(2337,3,NULL,'Health',NULL,2582,2583,1106,1,1), +(2338,3,NULL,'Medical information systems',NULL,2584,2585,1106,1,1), +(2339,3,NULL,'Economics',NULL,2588,2589,1107,1,1), +(2340,3,NULL,'Psychology',NULL,2590,2591,1107,1,1), +(2341,3,NULL,'Sociology',NULL,2592,2593,1107,1,1), +(2342,3,NULL,'Architecture (NEW)',NULL,2596,2597,1108,1,1), +(2343,3,NULL,'Arts, fine and performing**',NULL,2598,2599,1108,1,1), +(2344,3,NULL,'Fine arts (NEW)',NULL,2600,2601,1108,1,1), +(2345,3,NULL,'Language translation',NULL,2602,2603,1108,1,1), +(2346,3,NULL,'Linguistics',NULL,2604,2605,1108,1,1), +(2347,3,NULL,'Literature',NULL,2606,2607,1108,1,1), +(2348,3,NULL,'Music**',NULL,2608,2609,1108,1,1), +(2349,3,NULL,'Performing arts (e.g., dance, music) (NEW)',NULL,2610,2611,1108,1,1), +(2350,3,NULL,'Computer-aided design (CAD)',NULL,2614,2615,1109,1,1), +(2351,3,NULL,'Computer-aided manufacturing (CAM)',NULL,2616,2617,1109,1,1), +(2352,3,NULL,'Command and control',NULL,2620,2621,1110,1,1), +(2353,3,NULL,'Consumer products',NULL,2622,2623,1110,1,1), +(2354,3,NULL,'Industrial control',NULL,2624,2625,1110,1,1), +(2355,3,NULL,'Military',NULL,2626,2627,1110,1,1), +(2356,3,NULL,'Process control',NULL,2628,2629,1110,1,1), +(2357,3,NULL,'Publishing',NULL,2630,2631,1110,1,1), +(2358,3,NULL,'Real time',NULL,2632,2633,1110,1,1), +(2359,3,NULL,'Markets',NULL,2642,2643,1113,1,1), +(2360,3,NULL,'Standards',NULL,2644,2645,1113,1,1), +(2361,3,NULL,'Statistics',NULL,2646,2647,1113,1,1), +(2362,3,NULL,'Suppliers',NULL,2648,2649,1113,1,1), +(2363,3,NULL,'Hardware',NULL,2652,2653,1114,1,1), +(2364,3,NULL,'People',NULL,2654,2655,1114,1,1), +(2365,3,NULL,'Software',NULL,2656,2657,1114,1,1), +(2366,3,NULL,'Systems',NULL,2658,2659,1114,1,1), +(2367,3,NULL,'Theory',NULL,2660,2661,1114,1,1), +(2368,3,'K.3.0','General','K.3.0',2664,2665,1115,1,1), +(2369,3,'K.3.1','Computer Uses in Education','K.3.1',2666,2675,1115,1,1), +(2370,3,NULL,'Collaborative learning (NEW)',NULL,2667,2668,2369,1,1), +(2371,3,NULL,'Computer-assisted instruction (CAI)',NULL,2669,2670,2369,1,1), +(2372,3,NULL,'Computer-managed instruction (CMI)',NULL,2671,2672,2369,1,1), +(2373,3,NULL,'Distance learning (NEW)',NULL,2673,2674,2369,1,1), +(2374,3,'K.3.2','Computer and Information Science Education','K.3.2',2676,2689,1115,1,1), +(2375,3,NULL,'Accreditation (NEW)',NULL,2677,2678,2374,1,1), +(2376,3,NULL,'Computer science education',NULL,2679,2680,2374,1,1), +(2377,3,NULL,'Curriculum',NULL,2681,2682,2374,1,1), +(2378,3,NULL,'Information systems education',NULL,2683,2684,2374,1,1), +(2379,3,NULL,'Literacy (NEW)',NULL,2685,2686,2374,1,1), +(2380,3,NULL,'Self-assessment',NULL,2687,2688,2374,1,1), +(2381,3,'K.3.m','Miscellaneous','K.3.m',2690,2695,1115,1,1), +(2382,3,NULL,'Accreditation**',NULL,2691,2692,2381,1,1), +(2383,3,NULL,'Computer literacy**',NULL,2693,2694,2381,1,1), +(2384,3,'K.4.0','General','K.4.0',2698,2699,1116,1,1), +(2385,3,'K.4.1','Public Policy Issues','K.4.1',2700,2719,1116,1,1), +(2386,3,NULL,'Abuse and crime involving computers (NEW)',NULL,2701,2702,2385,1,1), +(2387,3,NULL,'Computer-related health issues (NEW)',NULL,2703,2704,2385,1,1), +(2388,3,NULL,'Ethics (NEW)',NULL,2705,2706,2385,1,1), +(2389,3,NULL,'Human safety',NULL,2707,2708,2385,1,1), +(2390,3,NULL,'Intellectual property rights (NEW)',NULL,2709,2710,2385,1,1), +(2391,3,NULL,'Privacy',NULL,2711,2712,2385,1,1), +(2392,3,NULL,'Regulation',NULL,2713,2714,2385,1,1), +(2393,3,NULL,'Transborder data flow',NULL,2715,2716,2385,1,1), +(2394,3,NULL,'Use/abuse of power (NEW)',NULL,2717,2718,2385,1,1), +(2395,3,'K.4.2','Social Issues','K.4.2',2720,2729,1116,1,1), +(2396,3,NULL,'Abuse and crime involving computers**',NULL,2721,2722,2395,1,1), +(2397,3,NULL,'Assistive technologies for persons with disabilities (NEW)',NULL,2723,2724,2395,1,1), +(2398,3,NULL,'Employment',NULL,2725,2726,2395,1,1), +(2399,3,NULL,'Handicapped persons/special needs**',NULL,2727,2728,2395,1,1), +(2400,3,'K.4.3','Organizational Impacts','K.4.3',2730,2739,1116,1,1), +(2401,3,NULL,'Automation (NEW)',NULL,2731,2732,2400,1,1), +(2402,3,NULL,'Computer-supported collaborative work (NEW)',NULL,2733,2734,2400,1,1), +(2403,3,NULL,'Employment (NEW)',NULL,2735,2736,2400,1,1), +(2404,3,NULL,'Reengineering (NEW)',NULL,2737,2738,2400,1,1), +(2405,3,'K.4.4','Electronic Commerce (J.1) (NEW)','K.4.4',2740,2753,1116,1,1), +(2406,3,NULL,'Cybercash, digital cash (NEW)',NULL,2741,2742,2405,1,1), +(2407,3,NULL,'Distributed commercial transactions (NEW)',NULL,2743,2744,2405,1,1), +(2408,3,NULL,'Electronic data interchange (EDI) (NEW)',NULL,2745,2746,2405,1,1), +(2409,3,NULL,'Intellectual property (NEW)',NULL,2747,2748,2405,1,1), +(2410,3,NULL,'Payment schemes (NEW)',NULL,2749,2750,2405,1,1), +(2411,3,NULL,'Security (NEW)',NULL,2751,2752,2405,1,1), +(2412,3,'K.4.m','Miscellaneous','K.4.m',2754,2755,1116,1,1), +(2413,3,'K.5.0','General','K.5.0',2758,2759,1117,1,1), +(2414,3,'K.5.1','Hardware/Software Protection (REVISED)','K.5.1',2760,2771,1117,1,1), +(2415,3,NULL,'Copyrights',NULL,2761,2762,2414,1,1), +(2416,3,NULL,'Licensing (NEW)',NULL,2763,2764,2414,1,1), +(2417,3,NULL,'Patents',NULL,2765,2766,2414,1,1), +(2418,3,NULL,'Proprietary rights',NULL,2767,2768,2414,1,1), +(2419,3,NULL,'Trade secrets**',NULL,2769,2770,2414,1,1), +(2420,3,'K.5.2','Governmental Issues','K.5.2',2772,2779,1117,1,1), +(2421,3,NULL,'Censorship (NEW)',NULL,2773,2774,2420,1,1), +(2422,3,NULL,'Regulation',NULL,2775,2776,2420,1,1), +(2423,3,NULL,'Taxation',NULL,2777,2778,2420,1,1), +(2424,3,'K.5.m','Miscellaneous','K.5.m',2780,2785,1117,1,1), +(2425,3,NULL,'Contracts**',NULL,2781,2782,2424,1,1), +(2426,3,NULL,'Hardware patents**',NULL,2783,2784,2424,1,1), +(2427,3,'K.6.0','General','K.6.0',2788,2791,1118,1,1), +(2428,3,NULL,'Economics',NULL,2789,2790,2427,1,1), +(2429,3,'K.6.1','Project and People Management','K.6.1',2792,2807,1118,1,1), +(2430,3,NULL,'Life cycle',NULL,2793,2794,2429,1,1), +(2431,3,NULL,'Management techniques (e.g., PERT/CPM)',NULL,2795,2796,2429,1,1), +(2432,3,NULL,'Staffing',NULL,2797,2798,2429,1,1), +(2433,3,NULL,'Strategic information systems planning (NEW)',NULL,2799,2800,2429,1,1), +(2434,3,NULL,'Systems analysis and design',NULL,2801,2802,2429,1,1), +(2435,3,NULL,'Systems development',NULL,2803,2804,2429,1,1), +(2436,3,NULL,'Training',NULL,2805,2806,2429,1,1), +(2437,3,'K.6.2','Installation Management','K.6.2',2808,2819,1118,1,1), +(2438,3,NULL,'Benchmarks',NULL,2809,2810,2437,1,1), +(2439,3,NULL,'Computer selection',NULL,2811,2812,2437,1,1), +(2440,3,NULL,'Computing equipment management',NULL,2813,2814,2437,1,1), +(2441,3,NULL,'Performance and usage measurement',NULL,2815,2816,2437,1,1), +(2442,3,NULL,'Pricing and resource allocation',NULL,2817,2818,2437,1,1), +(2443,3,'K.6.3','Software Management (D.2.9)','K.6.3',2820,2829,1118,1,1), +(2444,3,NULL,'Software development',NULL,2821,2822,2443,1,1), +(2445,3,NULL,'Software maintenance',NULL,2823,2824,2443,1,1), +(2446,3,NULL,'Software process (NEW)',NULL,2825,2826,2443,1,1), +(2447,3,NULL,'Software selection',NULL,2827,2828,2443,1,1), +(2448,3,'K.6.4','System Management','K.6.4',2830,2837,1118,1,1), +(2449,3,NULL,'Centralization/decentralization',NULL,2831,2832,2448,1,1), +(2450,3,NULL,'Management audit',NULL,2833,2834,2448,1,1), +(2451,3,NULL,'Quality assurance',NULL,2835,2836,2448,1,1), +(2452,3,'K.6.5','Security and Protection (D.4.6, K.4.2)','K.6.5',2838,2849,1118,1,1), +(2453,3,NULL,'Authentication',NULL,2839,2840,2452,1,1), +(2454,3,NULL,'Insurance**',NULL,2841,2842,2452,1,1), +(2455,3,NULL,'Invasive software (e.g., viruses, worms, Trojan horses)',NULL,2843,2844,2452,1,1), +(2456,3,NULL,'Physical security**',NULL,2845,2846,2452,1,1), +(2457,3,NULL,'Unauthorized access (e.g., hacking, phreaking) (NEW)',NULL,2847,2848,2452,1,1), +(2458,3,'K.6.m','Miscellaneous','K.6.m',2850,2855,1118,1,1), +(2459,3,NULL,'Insurance*',NULL,2851,2852,2458,1,1), +(2460,3,NULL,'Security*',NULL,2853,2854,2458,1,1), +(2461,3,'K.7.0','General','K.7.0',2858,2859,1119,1,1), +(2462,3,'K.7.1','Occupations','K.7.1',2860,2861,1119,1,1), +(2463,3,'K.7.2','Organizations','K.7.2',2862,2863,1119,1,1), +(2464,3,'K.7.3','Testing, Certification, and Licensing','K.7.3',2864,2865,1119,1,1), +(2465,3,'K.7.4','Professional Ethics (K.4) (NEW)','K.7.4',2866,2873,1119,1,1), +(2466,3,NULL,'Codes of ethics (NEW)',NULL,2867,2868,2465,1,1), +(2467,3,NULL,'Codes of good practice (NEW)',NULL,2869,2870,2465,1,1), +(2468,3,NULL,'Ethical dilemmas (NEW)',NULL,2871,2872,2465,1,1), +(2469,3,'K.7.m','Miscellaneous','K.7.m',2874,2879,1119,1,1), +(2470,3,NULL,'Codes of good practice**',NULL,2875,2876,2469,1,1), +(2471,3,NULL,'Ethics**',NULL,2877,2878,2469,1,1), +(2472,3,NULL,'Games*',NULL,2882,2883,1120,1,1), +(2473,3,'K.8.0','General','K.8.0',2884,2887,1120,1,1), +(2474,3,NULL,'Games',NULL,2885,2886,2473,1,1), +(2475,3,'K.8.1','Application Packages','K.8.1',2888,2901,1120,1,1), +(2476,3,NULL,'Data communications',NULL,2889,2890,2475,1,1), +(2477,3,NULL,'Database processing',NULL,2891,2892,2475,1,1), +(2478,3,NULL,'Freeware/shareware (NEW)',NULL,2893,2894,2475,1,1), +(2479,3,NULL,'Graphics',NULL,2895,2896,2475,1,1), +(2480,3,NULL,'Spreadsheets',NULL,2897,2898,2475,1,1), +(2481,3,NULL,'Word processing',NULL,2899,2900,2475,1,1), +(2482,3,'K.8.2','Hardware','K.8.2',2902,2903,1120,1,1), +(2483,3,'K.8.3','Management/Maintenance','K.8.3',2904,2905,1120,1,1), +(2484,3,'K.8.m','Miscellaneous (NEW)','K.8.m',2906,2907,1120,1,1); \ No newline at end of file diff --git a/database/factories/create_collections_data_ddc.sql b/database/factories/create_collections_data_ddc.sql new file mode 100644 index 0000000..38e789c --- /dev/null +++ b/database/factories/create_collections_data_ddc.sql @@ -0,0 +1,1044 @@ +-- Dewey classification +/* The ten main classes are: see number at db below +0 Computer science, information & general works +1 Philosophy & psychology +2 Religion +3 Social sciences +4 Language +5 Science +6 Technology +7 Arts & recreation +8 Literature +9 History & geography +*/ + +INSERT INTO collections (id, role_id, number, name, oai_subset, left_id, right_id, parent_id, visible, visible_publish) VALUES +(3,2,'0','Informatik, Informationswissenschaft, allgemeine Werke','0',2,189,NULL,1,1), +(4,2,'1','Philosophie und Psychologie','1',190,389,NULL,1,1), +(5,2,'2','Religion','2',390,589,NULL,1,1), +(6,2,'3','Sozialwissenschaften','3',590,791,NULL,1,1), +(7,2,'4','Sprache','4',792,983,NULL,1,1), +(8,2,'5','Naturwissenschaften und Mathematik','5',984,1191,NULL,1,1), +(9,2,'6','Technik, Medizin, angewandte Wissenschaften','6',1192,1399,NULL,1,1), +(10,2,'7','Künste und Unterhaltung','7',1400,1613,NULL,1,1), +(11,2,'8','Literatur','8',1614,1833,NULL,1,1), +(12,2,'9','Geschichte und Geografie','9',1834,2053,NULL,1,1), +(13,2,'00','Informatik, Wissen, Systeme','00',3,18,3,1,1), +(14,2,'01','Bibliografien','01',19,38,3,1,1), +(15,2,'02','Bibliotheks- und Informationswissenschaften','02',39,56,3,1,1), +(16,2,'03','Enzyklopädien, Faktenbücher','03',57,78,3,1,1), +(17,2,'05','Zeitschriften, fortlaufende Sammelwerke','05',79,100,3,1,1), +(18,2,'06','Verbände, Organisationen, Museen','06',101,122,3,1,1), +(19,2,'07','Publizistische Medien, Journalismus, Verlagswesen','07',123,144,3,1,1), +(20,2,'08','Allgemeine Sammelwerke, Zitatensammlungen','08',145,166,3,1,1), +(21,2,'09','Handschriften, seltene Bücher','09',167,188,3,1,1), +(22,2,'10','Philosophie','10',191,210,4,1,1), +(23,2,'11','Metaphysik','11',211,230,4,0,1), +(24,2,'12','Epistemologie','12',231,250,4,0,1), +(25,2,'13','Parapsychologie, Okkultismus','13',251,266,4,1,1), +(26,2,'14','Philosophische Schulen','14',267,288,4,0,1), +(27,2,'15','Psychologie','15',289,304,4,1,1), +(28,2,'16','Logik','16',305,322,4,0,1), +(29,2,'17','Ethik','17',323,344,4,0,1), +(30,2,'18','Antike, mittelalterliche und östliche Philosophie','18',345,366,4,0,1), +(31,2,'19','Neuzeitliche westliche Philosophie','19',367,388,4,0,1), +(32,2,'20','Religion','20',391,412,5,1,1), +(33,2,'21','Religionsphilosophie, Religionstheorie','21',413,428,5,0,1), +(34,2,'22','Bibel','22',429,450,5,1,1), +(35,2,'23','Christentum, Christliche Theologie','23',451,470,5,1,1), +(36,2,'24','Christliche Erfahrung, christliches Leben','24',471,488,5,0,1), +(37,2,'25','Christliche Pastoraltheologie, Ordensgemeinschaften','25',489,504,5,0,1), +(38,2,'26','Kirchenorganisation, Sozialarbeit, Religionsausübung','26',505,526,5,0,1), +(39,2,'27','Geschichte des Christentums','27',527,548,5,0,1), +(40,2,'28','Christliche Konfessionen','28',549,568,5,0,1), +(41,2,'29','Andere Religionen','29',569,588,5,1,1), +(42,2,'30','Sozialwissenschaften, Soziologie','30',591,608,6,1,1), +(43,2,'31','Statistiken','31',609,624,6,1,1), +(44,2,'32','Politikwissenschaft','32',625,644,6,1,1), +(45,2,'33','Wirtschaft','33',645,666,6,1,1), +(46,2,'34','Recht','34',667,688,6,1,1), +(47,2,'35','Öffentliche Verwaltung, Militärwissenschaft','35',689,710,6,1,1), +(48,2,'36','Soziale Probleme, Sozialdienste','36',711,732,6,1,1), +(49,2,'37','Bildung und Erziehung','37',733,750,6,1,1), +(50,2,'38','Handel, Kommunikation, Verkehr','38',751,772,6,1,1), +(51,2,'39','Bräuche, Etikette, Folklore','39',773,790,6,1,1), +(52,2,'40','Sprache','40',793,814,7,1,1), +(53,2,'41','Linguistik','41',815,834,7,0,1), +(54,2,'42','Englisch, Altenglisch','42',835,852,7,1,1), +(55,2,'43','Deutsch, germanische Sprachen allgemein','43',853,870,7,1,1), +(56,2,'44','Französisch, romanische Sprachen allgemein','44',871,888,7,1,1), +(57,2,'45','Italienisch, Rumänisch, Rätoromanisch','45',889,906,7,1,1), +(58,2,'46','Spanisch, Portugiesisch','46',907,924,7,1,1), +(59,2,'47','Latein, italische Sprachen','47',925,942,7,1,1), +(60,2,'48','Griechisch','48',943,960,7,1,1), +(61,2,'49','Andere Sprachen','49',961,982,7,1,1), +(62,2,'50','Naturwissenschaften','50',985,1004,8,1,1), +(63,2,'51','Mathematik','51',1005,1024,8,1,1), +(64,2,'52','Astronomie','52',1025,1044,8,1,1), +(65,2,'53','Physik','53',1045,1066,8,1,1), +(66,2,'54','Chemie','54',1067,1084,8,1,1), +(67,2,'55','Geowissenschaften, Geologie','55',1085,1106,8,1,1), +(68,2,'56','Fossilien, Paläontologie','56',1107,1128,8,1,1), +(69,2,'57','Biowissenschaften, Biologie','57',1129,1148,8,1,1), +(70,2,'58','Pflanzen (Botanik)','58',1149,1168,8,1,1), +(71,2,'59','Tiere (Zoologie)','59',1169,1190,8,1,1), +(72,2,'60','Technik','60',1193,1214,9,1,1), +(73,2,'61','Medizin und Gesundheit','61',1215,1234,9,1,1), +(74,2,'62','Ingenieurwissenschaften','62',1235,1254,9,1,1), +(75,2,'63','Landwirtschaft','63',1255,1276,9,1,1), +(76,2,'64','Hauswirtschaft und Familie','64',1277,1298,9,1,1), +(77,2,'65','Management, Öffentlichkeitsarbeit','65',1299,1314,9,1,1), +(78,2,'66','Chemische Verfahrenstechnik','66',1315,1336,9,1,1), +(79,2,'67','Industrielle Fertigung','67',1337,1358,9,1,1), +(80,2,'68','Industrielle Fertigung für einzelne Verwendungszwecke','68',1359,1378,9,0,1), +(81,2,'69','Hausbau, Bauhandwerk','69',1379,1398,9,1,1), +(82,2,'70','Künste','70',1401,1422,10,1,1), +(83,2,'71','Landschaftsgestaltung, Raumplanung','71',1423,1444,10,1,1), +(84,2,'72','Architektur','72',1445,1466,10,1,1), +(85,2,'73','Bildhauerkunst, Keramik, Metallkunst','73',1467,1488,10,1,1), +(86,2,'74','Zeichnung, angewandte Kunst','74',1489,1510,10,1,1), +(87,2,'75','Malerei','75',1511,1530,10,1,1), +(88,2,'76','Grafik','76',1531,1548,10,1,1), +(89,2,'77','Fotografie, Computerkunst','77',1549,1568,10,1,1), +(90,2,'78','Musik','78',1569,1590,10,1,1), +(91,2,'79','Sport, Spiele, Unterhaltung','79',1591,1612,10,1,1), +(92,2,'80','Literatur, Rhetorik, Literaturwissenschaft','80',1615,1634,11,1,1), +(93,2,'81','Amerikanische Literatur in Englisch','81',1635,1656,11,1,1), +(94,2,'82','Englische, altenglische Literaturen','82',1657,1678,11,1,1), +(95,2,'83','Deutsche und verwandte Literaturen','83',1679,1700,11,1,1), +(96,2,'84','Französische und verwandte Literaturen','84',1701,1722,11,1,1), +(97,2,'85','Italienische, rumänische, rätoromanische Literaturen','85',1723,1744,11,1,1), +(98,2,'86','Spanische, portugiesische Literaturen','86',1745,1766,11,1,1), +(99,2,'87','Lateinische, italische Literaturen','87',1767,1788,11,1,1), +(100,2,'88','Griechische Literaturen','88',1789,1810,11,1,1), +(101,2,'89','Andere Literaturen','89',1811,1832,11,1,1), +(102,2,'90','Geschichte','90',1835,1856,12,1,1), +(103,2,'91','Geografie, Reisen','91',1857,1880,12,1,1), +(104,2,'92','Biografie, Genealogie','92',1881,1902,12,1,1), +(105,2,'93','Geschichte des Altertums (bis ca. 499), Archäologie','93',1903,1924,12,1,1), +(106,2,'94','Geschichte Europas','94',1925,1946,12,1,1), +(107,2,'95','Geschichte Asiens','95',1947,1968,12,1,1), +(108,2,'96','Geschichte Afrikas','96',1969,1990,12,1,1), +(109,2,'97','Geschichte Nordamerikas','97',1991,2012,12,1,1), +(110,2,'98','Geschichte Südamerikas','98',2013,2034,12,1,1), +(111,2,'99','Geschichte anderer Gebiete','99',2035,2052,12,1,1), +(112,2,'000','Informatik, Informationswissenschaft, allgemeine Werke','000',4,5,13,1,1), +(113,2,'001','Wissen','001',6,7,13,0,1), +(114,2,'002','Das Buch','002',8,9,13,0,1), +(115,2,'003','Systeme','003',10,11,13,0,1), +(116,2,'004','Datenverarbeitung, Informatik','004',12,13,13,1,1), +(117,2,'005','Computerprogrammierung, Programme, Daten','005',14,15,13,0,1), +(118,2,'006','Spezielle Computerverfahren','006',16,17,13,0,1), +(119,2,'010','Bibliografie','010',20,21,14,0,1), +(120,2,'011','Bibliografien','011',22,23,14,0,1), +(121,2,'012','Bibliografien von Einzelpersonen','012',24,25,14,0,1), +(122,2,'014','Bibliografien anonymer und pseudonymer Werke','014',26,27,14,0,1), +(123,2,'015','Bibliografien von Werken aus einzelnen Orten','015',28,29,14,0,1), +(124,2,'016','Bibliografien von Werken über einzelne Themen','016',30,31,14,0,1), +(125,2,'017','Allgemeine Sachkataloge','017',32,33,14,0,1), +(126,2,'018','Kataloge nach Autor, Erscheinungsjahr usw.','018',34,35,14,0,1), +(127,2,'019','Kreuzkataloge','019',36,37,14,0,1), +(128,2,'020','Bibliotheks- und Informationswissenschaften','020',40,41,15,0,1), +(129,2,'021','Beziehungen zwischen Bibliotheken','021',42,43,15,0,1), +(130,2,'022','Verwaltung von Bibliotheksgebäuden','022',44,45,15,0,1), +(131,2,'023','Personalmanagement','023',46,47,15,0,1), +(132,2,'025','Bibliothekarische Tätigkeiten','025',48,49,15,0,1), +(133,2,'026','Spezialbibliotheken','026',50,51,15,0,1), +(134,2,'027','Allgemeinbibliotheken','027',52,53,15,0,1), +(135,2,'028','Lesen und Nutzung anderer Informationsmedien','028',54,55,15,0,1), +(136,2,'030','Allgemeinenzyklopädien','030',58,59,16,0,1), +(137,2,'031','Enzyklopädien in amerikanischem Englisch','031',60,61,16,0,1), +(138,2,'032','Enzyklopädien in Englisch','032',62,63,16,0,1), +(139,2,'033','Enzyklopädien in Deutsch und Niederländisch','033',64,65,16,0,1), +(140,2,'034','Enzyklopädien in Französisch, Okzitanisch und Katalanisch','034',66,67,16,0,1), +(141,2,'035','Enzyklopädien in Italienisch, Rumänisch und Rätoromanisch','035',68,69,16,0,1), +(142,2,'036','Enzyklopädien in Spanisch und Portugiesisch','036',70,71,16,0,1), +(143,2,'037','Enzyklopädien in slawischen Sprachen','037',72,73,16,0,1), +(144,2,'038','Enzyklopädien in skandinavischen Sprachen','038',74,75,16,0,1), +(145,2,'039','Enzyklopädien in anderen Sprachen','039',76,77,16,0,1), +(146,2,'050','Zeitschriften, allgemeine fortlaufende Sammelwerke','050',80,81,17,0,1), +(147,2,'051','Fortlaufende Sammelwerke in amerikanischem Englisch','051',82,83,17,0,1), +(148,2,'052','Fortlaufende Sammelwerke in Englisch','052',84,85,17,0,1), +(149,2,'053','Fortlaufende Sammelwerke in Deutsch und Niederländisch','053',86,87,17,0,1), +(150,2,'054','Fortlaufende Sammelwerke in Französisch, Okzitanisch und Katalanisch','054',88,89,17,0,1), +(151,2,'055','Fortlaufende Sammelwerke in Italienisch, Rumänisch und Rätoromanisch','055',90,91,17,0,1), +(152,2,'056','Fortlaufende Sammelwerke in Spanisch und Portugiesisch','056',92,93,17,0,1), +(153,2,'057','Fortlaufende Sammelwerke in slawischen Sprachen','057',94,95,17,0,1), +(154,2,'058','Fortlaufende Sammelwerke in skandinavischen Sprachen','058',96,97,17,0,1), +(155,2,'059','Fortlaufende Sammelwerke in anderen Sprachen','059',98,99,17,0,1), +(156,2,'060','Allgemeine Organisationen, Museumswissenschaft','060',102,103,18,0,1), +(157,2,'061','Allgemeine Organisationen in Nordamerika','061',104,105,18,0,1), +(158,2,'062','Allgemeine Organisationen auf den Britischen Inseln, in England','062',106,107,18,0,1), +(159,2,'063','Allgemeine Organisationen in Mitteleuropa, in Deutschland','063',108,109,18,0,1), +(160,2,'064','Allgemeine Organisationen in Frankreich und Monaco','064',110,111,18,0,1), +(161,2,'065','Allgemeine Organisationen in Italien und auf benachbarten Inseln','065',112,113,18,0,1), +(162,2,'066','Allgemeine Organisationen auf der Iberischen Halbinsel und benachbarten Inseln','066',114,115,18,0,1), +(163,2,'067','Allgemeine Organisationen in Osteuropa, in Russland','067',116,117,18,0,1), +(164,2,'068','Allgemeine Organisationen in anderen geografischen Gebieten','068',118,119,18,0,1), +(165,2,'069','Museumswissenschaft','069',120,121,18,0,1), +(166,2,'070','Publizistische Medien, Journalismus, Verlagswesen','070',124,125,19,0,1), +(167,2,'071','Journalismus und Zeitungen in Nordamerika','071',126,127,19,0,1), +(168,2,'072','Journalismus und Zeitungen auf den Britischen Inseln, in England','072',128,129,19,0,1), +(169,2,'073','Journalismus und Zeitungen in Mitteleuropa, in Deutschland','073',130,131,19,0,1), +(170,2,'074','Journalismus und Zeitungen in Frankreich und Monaco','074',132,133,19,0,1), +(171,2,'075','Journalismus und Zeitungen in Italien und auf benachbarten Inseln','075',134,135,19,0,1), +(172,2,'076','Journalismus und Zeitungen auf der Iberischen Halbinsel und benachbarten Inseln','076',136,137,19,0,1), +(173,2,'077','Journalismus und Zeitungen in Osteuropa, in Russland','077',138,139,19,0,1), +(174,2,'078','Journalismus und Zeitungen in Skandinavien','078',140,141,19,0,1), +(175,2,'079','Journalismus und Zeitungen in anderen geografischen Gebieten','079',142,143,19,0,1), +(176,2,'080','Allgemeine Sammelwerke, Zitatensammlungen','080',146,147,20,0,1), +(177,2,'081','Sammelwerke in amerikanischem Englisch','081',148,149,20,0,1), +(178,2,'082','Sammelwerke in Englisch','082',150,151,20,0,1), +(179,2,'083','Sammelwerke in Deutsch und Niederländisch','083',152,153,20,0,1), +(180,2,'084','Sammelwerke in Französisch, Okzitanisch und Katalanisch','084',154,155,20,0,1), +(181,2,'085','Sammelwerke in Italienisch, Rumänisch und Rätoromanisch','085',156,157,20,0,1), +(182,2,'086','Sammelwerke in Spanisch und Portugiesisch','086',158,159,20,0,1), +(183,2,'087','Sammelwerke in slawischen Sprachen','087',160,161,20,0,1), +(184,2,'088','Sammelwerke in skandinavischen Sprachen','088',162,163,20,0,1), +(185,2,'089','Sammelwerke in anderen Sprachen','089',164,165,20,0,1), +(186,2,'090','Handschriften, seltene Bücher','090',168,169,21,0,1), +(187,2,'091','Handschriften','091',170,171,21,0,1), +(188,2,'092','Blockbücher','092',172,173,21,0,1), +(189,2,'093','Inkunabeln','093',174,175,21,0,1), +(190,2,'094','Gedruckte Bücher','094',176,177,21,0,1), +(191,2,'095','Bücher mit besonderem Einband','095',178,179,21,0,1), +(192,2,'096','Bücher mit besonderen Illustrationen','096',180,181,21,0,1), +(193,2,'097','Bücher aus besonderem Besitz oder besonderer Herkunft','097',182,183,21,0,1), +(194,2,'098','Verbotene Werke, Fälschungen, Scherzdrucke','098',184,185,21,0,1), +(195,2,'099','Bücher mit besonderem Format','099',186,187,21,0,1), +(196,2,'100','Philosophie und Psychologie','100',192,193,22,0,1), +(197,2,'101','Theorie der Philosophie','101',194,195,22,0,1), +(198,2,'102','Verschiedenes','102',196,197,22,0,1), +(199,2,'103','Wörterbücher, Enzyklopädien','103',198,199,22,0,1), +(200,2,'105','Fortlaufende Sammelwerke','105',200,201,22,0,1), +(201,2,'106','Organisationen, Management','106',202,203,22,0,1), +(202,2,'107','Ausbildung, Forschung, verwandte Themen','107',204,205,22,0,1), +(203,2,'108','Behandlung nach Personengruppen','108',206,207,22,0,1), +(204,2,'109','Histor. Behandlung, Behandlung mehrerer Einzelpersonen','109',208,209,22,0,1), +(205,2,'110','Metaphysik','110',212,213,23,1,1), +(206,2,'111','Ontologie','111',214,215,23,1,1), +(207,2,'113','Kosmologie','113',216,217,23,1,1), +(208,2,'114','Raum','114',218,219,23,1,1), +(209,2,'115','Zeit','115',220,221,23,1,1), +(210,2,'116','Veränderung','116',222,223,23,1,1), +(211,2,'117','Struktur','117',224,225,23,1,1), +(212,2,'118','Kraft und Energie','118',226,227,23,1,1), +(213,2,'119','Zahl und Quantität','119',228,229,23,1,1), +(214,2,'120','Epistemologie, Kausalität, Menschheit','120',232,233,24,1,1), +(215,2,'121','Epistemologie','121',234,235,24,1,1), +(216,2,'122','Kausalität','122',236,237,24,1,1), +(217,2,'123','Determinismus, Indeterminismus','123',238,239,24,1,1), +(218,2,'124','Teleologie','124',240,241,24,1,1), +(219,2,'126','Das Selbst','126',242,243,24,1,1), +(220,2,'127','Das Unbewusste, das Unterbewusste','127',244,245,24,1,1), +(221,2,'128','Menschheit','128',246,247,24,1,1), +(222,2,'129','Ursprung und Schicksal individueller Seelen','129',248,249,24,1,1), +(223,2,'130','Parapsychologie und Okkultismus','130',252,253,25,0,1), +(224,2,'131','Parapsychologische und okkulte Techniken','131',254,255,25,0,1), +(225,2,'133','Einzelne Themen der Parapsychologie und des Okkultismus','133',256,257,25,0,1), +(226,2,'135','Träume, Mysterien','135',258,259,25,0,1), +(227,2,'137','Divinatorische Graphologie','137',260,261,25,0,1), +(228,2,'138','Physiognomie','138',262,263,25,0,1), +(229,2,'139','Phrenologie','139',264,265,25,0,1), +(230,2,'140','Einzelne philosophische Schulen','140',268,269,26,1,1), +(231,2,'141','Idealismus und verwandte Systeme','141',270,271,26,1,1), +(232,2,'142','Kritizismus','142',272,273,26,1,1), +(233,2,'143','Bergsonismus, Intuitionismus','143',274,275,26,1,1), +(234,2,'144','Humanismus und verwandte Systeme','144',276,277,26,1,1), +(235,2,'145','Sensualismus','145',278,279,26,1,1), +(236,2,'146','Naturalismus und verwandte Systeme','146',280,281,26,1,1), +(237,2,'147','Pantheismus und verwandte Systeme','147',282,283,26,1,1), +(238,2,'148','Eklektizismus, Liberalismus, Traditionalismus','148',284,285,26,1,1), +(239,2,'149','Andere philosophische Systeme','149',286,287,26,1,1), +(240,2,'150','Psychologie','150',290,291,27,0,1), +(241,2,'152','Sinneswahrnehmung, Bewegung, Emotionen, Triebe','152',292,293,27,0,1), +(242,2,'153','Kognitive Prozesse, Intelligenz','153',294,295,27,0,1), +(243,2,'154','Unterbewusste und bewusstseinsveränderte Zustände','154',296,297,27,0,1), +(244,2,'155','Differentielle Psychologie, Entwicklungspsychologie','155',298,299,27,0,1), +(245,2,'156','Vergleichende Psychologie','156',300,301,27,0,1), +(246,2,'158','Angewandte Psychologie','158',302,303,27,0,1), +(247,2,'160','Logik','160',306,307,28,1,1), +(248,2,'161','Induktion','161',308,309,28,1,1), +(249,2,'162','Deduktion','162',310,311,28,1,1), +(250,2,'165','Fehlschlüsse, Fehlerquellen','165',312,313,28,1,1), +(251,2,'166','Syllogismen','166',314,315,28,1,1), +(252,2,'167','Hypothesen','167',316,317,28,1,1), +(253,2,'168','Argument, Überzeugungung','168',318,319,28,1,1), +(254,2,'169','Analogie','169',320,321,28,1,1), +(255,2,'170','Ethik','170',324,325,29,1,1), +(256,2,'171','Ethische Systeme','171',326,327,29,1,1), +(257,2,'172','Politische Ethik','172',328,329,29,1,1), +(258,2,'173','Familienethik','173',330,331,29,1,1), +(259,2,'174','Berufsethik','174',332,333,29,1,1), +(260,2,'175','Ethik von Freizeit und Erholung','175',334,335,29,1,1), +(261,2,'176','Sexual- und Reproduktionsethik','176',336,337,29,1,1), +(262,2,'177','Ethik sozialer Beziehungen','177',338,339,29,1,1), +(263,2,'178','Konsumethik','178',340,341,29,1,1), +(264,2,'179','Andere ethische Normen','179',342,343,29,1,1), +(265,2,'180','Antike, mittelalterliche und östliche Philosophie','180',346,347,30,1,1), +(266,2,'181','Östliche Philosophie','181',348,349,30,1,1), +(267,2,'182','Vorsokratische griechische Philosophien','182',350,351,30,1,1), +(268,2,'183','Sokratische und verwandte Philosophien','183',352,353,30,1,1), +(269,2,'184','Platonische Philosophie','184',354,355,30,1,1), +(270,2,'185','Aristotelische Philosophie','185',356,357,30,1,1), +(271,2,'186','Skeptische und neuplatonische Philosophien','186',358,359,30,1,1), +(272,2,'187','Epikureische Philosophie','187',360,361,30,1,1), +(273,2,'188','Stoische Philosophie','188',362,363,30,1,1), +(274,2,'189','Mittelalterliche westliche Philosophie','189',364,365,30,1,1), +(275,2,'190','Neuzeitliche westliche Philosophie','190',368,369,31,1,1), +(276,2,'191','Philosophie in den USA und Kanada','191',370,371,31,1,1), +(277,2,'192','Philosophie auf den Britischen Inseln','192',372,373,31,1,1), +(278,2,'193','Philosophie in Deutschland und Österreich','193',374,375,31,1,1), +(279,2,'194','Philosophie in Frankreich','194',376,377,31,1,1), +(280,2,'195','Philosophie in Italien','195',378,379,31,1,1), +(281,2,'196','Philosophie in Spanien und Portugal','196',380,381,31,1,1), +(282,2,'197','Philosophie in Russland und der früheren Sowjetunion','197',382,383,31,1,1), +(283,2,'198','Philosophie in Skandinavien','198',384,385,31,1,1), +(284,2,'199','Philosophie in anderen geografischen Gebieten','199',386,387,31,1,1), +(285,2,'200','Religion','200',392,393,32,0,1), +(286,2,'201','Religiöse Mythologie, Soziallehre','201',394,395,32,0,1), +(287,2,'202','Lehren','202',396,397,32,0,1), +(288,2,'203','Gottesdienst und andere Formen der öffentlichen Religionsausübung','203',398,399,32,0,1), +(289,2,'204','Religiöse Erfahrung, religiöses Leben, religiöse Praxis','204',400,401,32,0,1), +(290,2,'205','Religiöse Ethik','205',402,403,32,0,1), +(291,2,'206','Religiöse Führer und Organisation','206',404,405,32,0,1), +(292,2,'207','Mission, religiöse Erziehung','207',406,407,32,0,1), +(293,2,'208','Quellen','208',408,409,32,0,1), +(294,2,'209','Sekten, Reformbewegungen','209',410,411,32,0,1), +(295,2,'210','Religionsphilosophie, Religionstheorie','210',414,415,33,1,1), +(296,2,'211','Gottesvorstellungen','211',416,417,33,1,1), +(297,2,'212','Gottesfrage, Gotteserkenntnis, Eigenschaften Gottes','212',418,419,33,1,1), +(298,2,'213','Schöpfung','213',420,421,33,1,1), +(299,2,'214','Theodizee','214',422,423,33,1,1), +(300,2,'215','Naturwissenschaft und Religion','215',424,425,33,1,1), +(301,2,'218','Der Mensch','218',426,427,33,1,1), +(302,2,'220','Bibel','220',430,431,34,0,1), +(303,2,'221','Altes Testament (Tenach)','221',432,433,34,0,1), +(304,2,'222','Geschichtsbücher des Alten Testaments','222',434,435,34,0,1), +(305,2,'223','Poetische Bücher des Alten Testaments','223',436,437,34,0,1), +(306,2,'224','Prophetische Bücher des Alten Testaments','224',438,439,34,0,1), +(307,2,'225','Neues Testament','225',440,441,34,0,1), +(308,2,'226','Evangelien, Apostelgeschichte','226',442,443,34,0,1), +(309,2,'227','Briefe','227',444,445,34,0,1), +(310,2,'228','Johannes-Apokalypse (Offenbarung des Johannes)','228',446,447,34,0,1), +(311,2,'229','Apokryphen, Pseudepigraphen','229',448,449,34,0,1), +(312,2,'230','Christentum, Christliche Theologie','230',452,453,35,0,1), +(313,2,'231','Gott','231',454,455,35,0,1), +(314,2,'232','Jesus Christus und seine Familie','232',456,457,35,0,1), +(315,2,'233','Der Mensch','233',458,459,35,0,1), +(316,2,'234','Erlösung, Gnade','234',460,461,35,0,1), +(317,2,'235','Geistliche Wesen','235',462,463,35,0,1), +(318,2,'236','Eschatologie','236',464,465,35,0,1), +(319,2,'238','Glaubensbekenntnisse, Katechismen','238',466,467,35,0,1), +(320,2,'239','Apologetik, Polemik','239',468,469,35,0,1), +(321,2,'240','Christliche Ethik, spirituelle Theologie','240',472,473,36,1,1), +(322,2,'241','Christliche Ethik','241',474,475,36,1,1), +(323,2,'242','Erbauungsliteratur','242',476,477,36,1,1), +(324,2,'243','Evangelistisches Schrifttum für Einzelpersonen','243',478,479,36,1,1), +(325,2,'246','Kunst im Christentum','246',480,481,36,1,1), +(326,2,'247','Kirchenausstattung, liturgisches Gerät','247',482,483,36,1,1), +(327,2,'248','Christliche Erfahrung, christliche Praxis, christliches Leben','248',484,485,36,1,1), +(328,2,'249','Christliches Leben in der Familie','249',486,487,36,1,1), +(329,2,'250','Christliche Orden und Ortskirchen','250',490,491,37,1,1), +(330,2,'251','Homiletik','251',492,493,37,1,1), +(331,2,'252','Predigttexte','252',494,495,37,1,1), +(332,2,'253','Pastoraltheologie','253',496,497,37,1,1), +(333,2,'254','Gemeindeverwaltung','254',498,499,37,1,1), +(334,2,'255','Religiöse Kongregationen und Orden','255',500,501,37,1,1), +(335,2,'259','Familienseelsorge, Kategorialseelsorge','259',502,503,37,1,1), +(336,2,'260','Soziallehre, Ekklesiologie','260',506,507,38,1,1), +(337,2,'261','Soziallehre','261',508,509,38,1,1), +(338,2,'262','Ekklesiologie','262',510,511,38,1,1), +(339,2,'263','Heilige Tage, Zeiten und Orte','263',512,513,38,1,1), +(340,2,'264','Öffentliche Religionsausübung','264',514,515,38,1,1), +(341,2,'265','Sakramente, andere Riten und Handlungen','265',516,517,38,1,1), +(342,2,'266','Mission','266',518,519,38,1,1), +(343,2,'267','Religiöse Verbände','267',520,521,38,1,1), +(344,2,'268','Religiöse Erziehung','268',522,523,38,1,1), +(345,2,'269','Geistliche Erneuerung','269',524,525,38,1,1), +(346,2,'270','Geschichte des Christentums, Kirchengeschichte','270',528,529,39,1,1), +(347,2,'271','Religiöse Orden in der Kirchengeschichte','271',530,531,39,1,1), +(348,2,'272','Verfolgung in der Kirchengeschichte','272',532,533,39,1,1), +(349,2,'273','Dogmatische Kontroversen, Häresie','273',534,535,39,1,1), +(350,2,'274','Geschichte des Christentums in Europa','274',536,537,39,1,1), +(351,2,'275','Geschichte des Christentums in Asien','275',538,539,39,1,1), +(352,2,'276','Geschichte des Christentums in Afrika','276',540,541,39,1,1), +(353,2,'277','Geschichte des Christentums in Nordamerika','277',542,543,39,1,1), +(354,2,'278','Geschichte des Christentums in Südamerika','278',544,545,39,1,1), +(355,2,'279','Geschichte des Christentums in anderen Gebieten','279',546,547,39,1,1), +(356,2,'280','Christliche Konfessionen und Sekten','280',550,551,40,1,1), +(357,2,'281','Alte Kirche, Ostkirchen','281',552,553,40,1,1), +(358,2,'282','Römisch-Katholische Kirche','282',554,555,40,1,1), +(359,2,'283','Anglikanische Kirchen','283',556,557,40,1,1), +(360,2,'284','Protestanten kontinentaleuropäischen Ursprungs','284',558,559,40,1,1), +(361,2,'285','Presbyterianer, Reformierte, Kongregationalisten','285',560,561,40,1,1), +(362,2,'286','Baptisten, Disciples of Christ, Adventisten','286',562,563,40,1,1), +(363,2,'287','Methodisten und verwandte Kirchen','287',564,565,40,1,1), +(364,2,'289','Andere Konfessionen und Sekten','289',566,567,40,1,1), +(365,2,'290','Andere Religionen','290',570,571,41,0,1), +(366,2,'292','Griechische und römische Religion','292',572,573,41,0,1), +(367,2,'293','Germanische Religion','293',574,575,41,0,1), +(368,2,'294','Religionen indischen Ursprungs','294',576,577,41,0,1), +(369,2,'295','Parsismus','295',578,579,41,0,1), +(370,2,'296','Judentum','296',580,581,41,0,1), +(371,2,'297','Islam, Babismus, Bahaismus','297',582,583,41,0,1), +(372,2,'298','(Optionale Notation)','298',584,585,41,0,1), +(373,2,'299','An anderer Stelle nicht vorgesehene Religionen','299',586,587,41,0,1), +(374,2,'300','Sozialwissenschaften','300',592,593,42,0,1), +(375,2,'301','Soziologie, Anthropologie','301',594,595,42,0,1), +(376,2,'302','Soziale Interaktion','302',596,597,42,0,1), +(377,2,'303','Gesellschaftliche Prozesse','303',598,599,42,0,1), +(378,2,'304','Das Sozialverhalten beeinflussende Faktoren','304',600,601,42,0,1), +(379,2,'305','Soziale Gruppen','305',602,603,42,0,1), +(380,2,'306','Kultur und Institutionen','306',604,605,42,0,1), +(381,2,'307','Gemeinschaften','307',606,607,42,0,1), +(382,2,'310','Sammlungen allgemeiner Statistiken','310',610,611,43,0,1), +(383,2,'314','Allgemeine Statistiken zu Europa','314',612,613,43,0,1), +(384,2,'315','Allgemeine Statistiken zu Asien','315',614,615,43,0,1), +(385,2,'316','Allgemeine Statistiken zu Afrika','316',616,617,43,0,1), +(386,2,'317','Allgemeine Statistiken zu Nordamerika','317',618,619,43,0,1), +(387,2,'318','Allgemeine Statistiken zu Südamerika','318',620,621,43,0,1), +(388,2,'319','Allgemeine Statistiken zu anderen Gebieten','319',622,623,43,0,1), +(389,2,'320','Politikwissenschaft','320',626,627,44,0,1), +(390,2,'321','Staatsformen und Regierungssysteme','321',628,629,44,0,1), +(391,2,'322','Beziehungen des Staats zu organisierten Gruppen','322',630,631,44,0,1), +(392,2,'323','Grundrechte und politische Rechte','323',632,633,44,0,1), +(393,2,'324','Der politische Prozess','324',634,635,44,0,1), +(394,2,'325','Internationale Migration, Kolonisation','325',636,637,44,0,1), +(395,2,'326','Sklaverei und Sklavenbefreiung','326',638,639,44,0,1), +(396,2,'327','Internationale Beziehungen','327',640,641,44,0,1), +(397,2,'328','Der Gesetzgebungsprozess','328',642,643,44,0,1), +(398,2,'330','Wirtschaft','330',646,647,45,0,1), +(399,2,'331','Arbeitsökonomie','331',648,649,45,0,1), +(400,2,'332','Finanzwirtschaft','332',650,651,45,0,1), +(401,2,'333','Boden- und Energiewirtschaft','333',652,653,45,0,1), +(402,2,'334','Genossenschaften','334',654,655,45,0,1), +(403,2,'335','Sozialismus und verwandte Systeme','335',656,657,45,0,1), +(404,2,'336','Öffentliche Finanzen','336',658,659,45,0,1), +(405,2,'337','Weltwirtschaft','337',660,661,45,0,1), +(406,2,'338','Produktion','338',662,663,45,0,1), +(407,2,'339','Makroökonomie und verwandte Themen','339',664,665,45,0,1), +(408,2,'340','Recht','340',668,669,46,0,1), +(409,2,'341','Völkerrecht','341',670,671,46,0,1), +(410,2,'342','Verfassungs- und Verwaltungsrecht','342',672,673,46,0,1), +(411,2,'343','Wehrrecht, Steuerrecht, Wirtschaftsrecht','343',674,675,46,0,1), +(412,2,'344','Arbeitsrecht, Sozialrecht, Bildungsrecht, Kulturrecht','344',676,677,46,0,1), +(413,2,'345','Strafrecht','345',678,679,46,0,1), +(414,2,'346','Privatrecht','346',680,681,46,0,1), +(415,2,'347','Zivilprozessrecht, Zivilgerichte','347',682,683,46,0,1), +(416,2,'348','Gesetze, Verordnungen, Rechtsfälle','348',684,685,46,0,1), +(417,2,'349','Recht einzelner Gebietskörperschaften und Gebiete','349',686,687,46,0,1), +(418,2,'350','Öffentliche Verwaltung, Militärwissenschaft','350',690,691,47,1,1), +(419,2,'351','Öffentliche Verwaltung','351',692,693,47,0,1), +(420,2,'352','Allgemeines zur öffentlichen Verwaltung','352',694,695,47,0,1), +(421,2,'353','Einzelne Bereiche der öffentlichen Verwaltung','353',696,697,47,0,1), +(422,2,'354','Verwaltung von Wirtschaft und Umwelt','354',698,699,47,0,1), +(423,2,'355','Militärwissenschaft','355',700,701,47,1,1), +(424,2,'356','Infanterie und Kampfführung','356',702,703,47,0,1), +(425,2,'357','Kavalleriestreitkräfte und Kampfführung','357',704,705,47,0,1), +(426,2,'358','Luftstreitkräfte und andere spezialisierte Streitkräfte','358',706,707,47,0,1), +(427,2,'359','Seestreitkräfte und Kampfführung','359',708,709,47,0,1), +(428,2,'360','Soziale Probleme und Sozialdienste, Verbände','360',712,713,48,0,1), +(429,2,'361','Soziale Probleme und Sozialhilfe im Allgemeinen','361',714,715,48,0,1), +(430,2,'362','Probleme und Dienste der Sozialhilfe','362',716,717,48,0,1), +(431,2,'363','Andere soziale Probleme und Sozialdienste','363',718,719,48,0,1), +(432,2,'364','Kriminologie','364',720,721,48,0,1), +(433,2,'365','Justizvollzugsanstalten und verwandte Einrichtungen','365',722,723,48,0,1), +(434,2,'366','Verbände','366',724,725,48,0,1), +(435,2,'367','Allgemeine Klubs','367',726,727,48,0,1), +(436,2,'368','Versicherungen','368',728,729,48,0,1), +(437,2,'369','Verschiedene Arten von Verbänden','369',730,731,48,0,1), +(438,2,'370','Bildung und Erziehung','370',734,735,49,0,1), +(439,2,'371','Schulen, schulische Tätigkeiten, Sonderpädagogik','371',736,737,49,0,1), +(440,2,'372','Primar- und Elementarbildung','372',738,739,49,0,1), +(441,2,'373','Sekundarbildung','373',740,741,49,0,1), +(442,2,'374','Erwachsenenbildung','374',742,743,49,0,1), +(443,2,'375','Curricula','375',744,745,49,0,1), +(444,2,'378','Hochschulbildung','378',746,747,49,0,1), +(445,2,'379','Bildungspolitik','379',748,749,49,0,1), +(446,2,'380','Handel, Kommunikation, Verkehr','380',752,753,50,0,1), +(447,2,'381','Handel','381',754,755,50,0,1), +(448,2,'382','Internationaler Handel','382',756,757,50,0,1), +(449,2,'383','Postverkehr','383',758,759,50,0,1), +(450,2,'384','Kommunikation, Telekommunikation','384',760,761,50,0,1), +(451,2,'385','Schienenverkehr','385',762,763,50,0,1), +(452,2,'386','Binnenschifffahrt, Fährverkehr','386',764,765,50,0,1), +(453,2,'387','Schifffahrt, Luft-, Weltraumverkehr','387',766,767,50,0,1), +(454,2,'388','Verkehr, Landverkehr','388',768,769,50,0,1), +(455,2,'389','Metrologie, Normung','389',770,771,50,0,1), +(456,2,'390','Bräuche, Etikette, Folklore','390',774,775,51,0,1), +(457,2,'391','Kleidung, äußeres Erscheinungsbild','391',776,777,51,0,1), +(458,2,'392','Bräuche im Lebenslauf und im häuslichen Leben','392',778,779,51,0,1), +(459,2,'393','Sterbe- und Bestattungsriten','393',780,781,51,0,1), +(460,2,'394','Allgemeine Bräuche','394',782,783,51,0,1), +(461,2,'395','Etikette (Manieren)','395',784,785,51,0,1), +(462,2,'398','Folklore','398',786,787,51,0,1), +(463,2,'399','Bräuche des Krieges und der Diplomatie','399',788,789,51,0,1), +(464,2,'400','Sprache','400',794,795,52,0,1), +(465,2,'401','Sprachphilosophie, Sprachtheorie','401',796,797,52,0,1), +(466,2,'402','Verschiedenes','402',798,799,52,0,1), +(467,2,'403','Wörterbücher, Enzyklopädien','403',800,801,52,0,1), +(468,2,'404','Spezielle Themen','404',802,803,52,0,1), +(469,2,'405','Fortlaufende Sammelwerke','405',804,805,52,0,1), +(470,2,'406','Organisationen, Management','406',806,807,52,0,1), +(471,2,'407','Ausbildung, Forschung, verwandte Themen','407',808,809,52,0,1), +(472,2,'408','Behandlung nach Personengruppen','408',810,811,52,0,1), +(473,2,'409','Geografische, personenbezogene Behandlung','409',812,813,52,0,1), +(474,2,'410','Linguistik','410',816,817,53,1,1), +(475,2,'411','Schriftsysteme','411',818,819,53,1,1), +(476,2,'412','Etymologie','412',820,821,53,1,1), +(477,2,'413','Wörterbücher','413',822,823,53,1,1), +(478,2,'414','Phonologie, Phonetik','414',824,825,53,1,1), +(479,2,'415','Grammatik','415',826,827,53,1,1), +(480,2,'417','Dialektologie, historische Linguistik','417',828,829,53,1,1), +(481,2,'418','Standardsprache, Angewandte Linguistik','418',830,831,53,1,1), +(482,2,'419','Gebärdensprachen','419',832,833,53,1,1), +(483,2,'420','Englisch, Altenglisch','420',836,837,54,0,1), +(484,2,'421','Schriftsystem und Phonologie des Englischen','421',838,839,54,0,1), +(485,2,'422','Etymologie des Englischen','422',840,841,54,0,1), +(486,2,'423','Englische Wörterbücher','423',842,843,54,0,1), +(487,2,'425','Englische Grammatik','425',844,845,54,0,1), +(488,2,'427','Varianten des Englischen, Mittelenglisch','427',846,847,54,0,1), +(489,2,'428','Gebrauch des Standard-Englisch','428',848,849,54,0,1), +(490,2,'429','Altenglisch (Angelsächsisch)','429',850,851,54,0,1), +(491,2,'430','Germanische Sprachen, Deutsch','430',854,855,55,1,1), +(492,2,'431','Schriftsysteme und Phonologie des Deutschen','431',856,857,55,0,1), +(493,2,'432','Etymologie des Deutschen','432',858,859,55,0,1), +(494,2,'433','Deutsche Wörterbücher','433',860,861,55,0,1), +(495,2,'435','Deutsche Grammatik','435',862,863,55,0,1), +(496,2,'437','Varianten des Deutschen','437',864,865,55,0,1), +(497,2,'438','Gebrauch des Standard-Deutsch','438',866,867,55,0,1), +(498,2,'439','Andere germanische Sprachen','439',868,869,55,1,1), +(499,2,'440','Romanische Sprachen, Französisch','440',872,873,56,0,1), +(500,2,'441','Schriftsysteme und Phonologie des Französischen','441',874,875,56,0,1), +(501,2,'442','Etymologie des Französischen','442',876,877,56,0,1), +(502,2,'443','Französische Wörterbücher','443',878,879,56,0,1), +(503,2,'445','Französische Grammatik','445',880,881,56,0,1), +(504,2,'447','Varianten des Französischen','447',882,883,56,0,1), +(505,2,'448','Gebrauch des Standard-Französisch','448',884,885,56,0,1), +(506,2,'449','Okzitanisch, Katalanisch','449',886,887,56,0,1), +(507,2,'450','Italienisch, Rumänisch, Rätoromanisch','450',890,891,57,0,1), +(508,2,'451','Schriftsysteme und Phonologie des Italienischen','451',892,893,57,0,1), +(509,2,'452','Etymologie des Italienischen','452',894,895,57,0,1), +(510,2,'453','Italienische Wörterbücher','453',896,897,57,0,1), +(511,2,'455','Italienische Grammatik','455',898,899,57,0,1), +(512,2,'457','Varianten des Italienischen','457',900,901,57,0,1), +(513,2,'458','Gebrauch des Standard-Italienisch','458',902,903,57,0,1), +(514,2,'459','Rumänisch, Rätoromanisch','459',904,905,57,0,1), +(515,2,'460','Spanisch, Portugiesisch','460',908,909,58,0,1), +(516,2,'461','Schriftsysteme und Phonologie des Spanischen','461',910,911,58,0,1), +(517,2,'462','Etymologie des Spanischen','462',912,913,58,0,1), +(518,2,'463','Spanische Wörterbücher','463',914,915,58,0,1), +(519,2,'465','Spanische Grammatik','465',916,917,58,0,1), +(520,2,'467','Varianten des Spanischen','467',918,919,58,0,1), +(521,2,'468','Gebrauch des Standard-Spanisch','468',920,921,58,0,1), +(522,2,'469','Portugiesisch','469',922,923,58,0,1), +(523,2,'470','Italische Sprachen, Latein','470',926,927,59,0,1), +(524,2,'471','Schriftsysteme und Phonologie des klassischen Latein','471',928,929,59,0,1), +(525,2,'472','Etymologie des klassischen Latein','472',930,931,59,0,1), +(526,2,'473','Wörterbücher des klassischen Latein','473',932,933,59,0,1), +(527,2,'475','Grammatik des klassischen Latein','475',934,935,59,0,1), +(528,2,'477','Altlatein, Mittellatein, Neulatein, Kirchenlatein, Vulgärlatein','477',936,937,59,0,1), +(529,2,'478','Gebrauch des klassischen Latein','478',938,939,59,0,1), +(530,2,'479','Andere italische Sprachen','479',940,941,59,0,1), +(531,2,'480','Hellenische Sprachen, klassisches Griechisch','480',944,945,60,0,1), +(532,2,'481','Schriftsysteme und Phonologie des klassischen Griechisch','481',946,947,60,0,1), +(533,2,'482','Etymologie des klassischen Griechisch','482',948,949,60,0,1), +(534,2,'483','Wörterbücher des klassischen Griechisch','483',950,951,60,0,1), +(535,2,'485','Grammatik des klassischen Griechisch','485',952,953,60,0,1), +(536,2,'487','Vorklassisches Griechisch, Mittelgriechisch','487',954,955,60,0,1), +(537,2,'488','Gebrauch des klassischen Griechisch','488',956,957,60,0,1), +(538,2,'489','Andere hellenische Sprachen, Neugriechisch','489',958,959,60,0,1), +(539,2,'490','Andere Sprachen','490',962,963,61,0,1), +(540,2,'491','Ostindoeuropäische und keltische Sprachen','491',964,965,61,0,1), +(541,2,'492','Afroasiatische Sprachen, semitische Sprachen','492',966,967,61,0,1), +(542,2,'493','Nichtsemitische afroasiatische Sprachen','493',968,969,61,0,1), +(543,2,'494','Altaische, uralische, paläosibirische, drawidische Sprachen','494',970,971,61,0,1), +(544,2,'495','Ost- und südostasiatische Sprachen','495',972,973,61,0,1), +(545,2,'496','Afrikanische Sprachen','496',974,975,61,0,1), +(546,2,'497','Nordamerikanische Indianersprachen','497',976,977,61,0,1), +(547,2,'498','Südamerikanische Indianersprachen','498',978,979,61,0,1), +(548,2,'499','Austronesische und andere Sprachen','499',980,981,61,0,1), +(549,2,'500','Naturwissenschaften und Mathematik','500',986,987,62,0,1), +(550,2,'501','Philosophie, Theorie','501',988,989,62,0,1), +(551,2,'502','Verschiedenes','502',990,991,62,0,1), +(552,2,'503','Wörterbücher, Enzyklopädien','503',992,993,62,0,1), +(553,2,'505','Fortlaufende Sammelwerke','505',994,995,62,0,1), +(554,2,'506','Organisationen, Management','506',996,997,62,0,1), +(555,2,'507','Ausbildung, Forschung, verwandte Themen','507',998,999,62,0,1), +(556,2,'508','Naturgeschichte','508',1000,1001,62,0,1), +(557,2,'509','Histor., geogr., personenbezogene Behandlung','509',1002,1003,62,0,1), +(558,2,'510','Mathematik','510',1006,1007,63,0,1), +(559,2,'511','Allgemeine mathematische Prinzipien','511',1008,1009,63,0,1), +(560,2,'512','Algebra','512',1010,1011,63,0,1), +(561,2,'513','Arithmetik','513',1012,1013,63,0,1), +(562,2,'514','Topologie','514',1014,1015,63,0,1), +(563,2,'515','Analysis','515',1016,1017,63,0,1), +(564,2,'516','Geometrie','516',1018,1019,63,0,1), +(565,2,'518','Numerische Analysis','518',1020,1021,63,0,1), +(566,2,'519','Wahrscheinlichkeiten, angewandte Mathematik','519',1022,1023,63,0,1), +(567,2,'520','Astronomie und zugeordnete Wissenschaften','520',1026,1027,64,0,1), +(568,2,'521','Himmelsmechanik','521',1028,1029,64,0,1), +(569,2,'522','Techniken, Ausstattung, Materialien','522',1030,1031,64,0,1), +(570,2,'523','Einzelne Himmelskörper und Himmelsphänomene','523',1032,1033,64,0,1), +(571,2,'525','Erde (Astronomische Geografie)','525',1034,1035,64,0,1), +(572,2,'526','Mathematische Geografie','526',1036,1037,64,0,1), +(573,2,'527','Astronavigation','527',1038,1039,64,0,1), +(574,2,'528','Ephemeriden','528',1040,1041,64,0,1), +(575,2,'529','Chronologie','529',1042,1043,64,0,1), +(576,2,'530','Physik','530',1046,1047,65,0,1), +(577,2,'531','Klassische Mechanik, Festkörpermechanik','531',1048,1049,65,0,1), +(578,2,'532','Mechanik der Fluide, Mechanik der Flüssigkeiten','532',1050,1051,65,0,1), +(579,2,'533','Gasmechanik','533',1052,1053,65,0,1), +(580,2,'534','Schall und verwandte Schwingungen','534',1054,1055,65,0,1), +(581,2,'535','Licht, Infrarot- und Ultraviolettphänomene','535',1056,1057,65,0,1), +(582,2,'536','Wärme','536',1058,1059,65,0,1), +(583,2,'537','Elektrizität, Elektronik','537',1060,1061,65,0,1), +(584,2,'538','Magnetismus','538',1062,1063,65,0,1), +(585,2,'539','Moderne Physik','539',1064,1065,65,0,1), +(586,2,'540','Chemie und zugeordnete Wissenschaften','540',1068,1069,66,0,1), +(587,2,'541','Physikalische Chemie','541',1070,1071,66,0,1), +(588,2,'542','Techniken, Ausstattung, Materialien','542',1072,1073,66,0,1), +(589,2,'543','Analytische Chemie','543',1074,1075,66,0,1), +(590,2,'546','Anorganische Chemie','546',1076,1077,66,0,1), +(591,2,'547','Organische Chemie','547',1078,1079,66,0,1), +(592,2,'548','Kristallografie','548',1080,1081,66,0,1), +(593,2,'549','Mineralogie','549',1082,1083,66,0,1), +(594,2,'550','Geowissenschaften','550',1086,1087,67,0,1), +(595,2,'551','Geologie, Hydrologie, Meteorologie','551',1088,1089,67,0,1), +(596,2,'552','Petrologie','552',1090,1091,67,0,1), +(597,2,'553','Lagerstättenkunde','553',1092,1093,67,0,1), +(598,2,'554','Geowissenschaften Europas','554',1094,1095,67,0,1), +(599,2,'555','Geowissenschaften Asiens','555',1096,1097,67,0,1), +(600,2,'556','Geowissenschaften Afrikas','556',1098,1099,67,0,1), +(601,2,'557','Geowissenschaften Nordamerikas','557',1100,1101,67,0,1), +(602,2,'558','Geowissenschaften Südamerikas','558',1102,1103,67,0,1), +(603,2,'559','Geowissenschaften anderer Gebiete','559',1104,1105,67,0,1), +(604,2,'560','Paläontologie, Paläozoologie','560',1108,1109,68,0,1), +(605,2,'561','Paläobotanik, fossile Mikroorganismen','561',1110,1111,68,0,1), +(606,2,'562','Fossile Evertebrata (Wirbellose)','562',1112,1113,68,0,1), +(607,2,'563','Fossile Wirbellose des Meeres und der Meeresküste','563',1114,1115,68,0,1), +(608,2,'564','Fossile Mollusca (Weichtiere), Tentaculata (Kranzfühler)','564',1116,1117,68,0,1), +(609,2,'565','Fossile Arthropoden (Gliederfüßer)','565',1118,1119,68,0,1), +(610,2,'566','Fossile Chordata (Chordatiere)','566',1120,1121,68,0,1), +(611,2,'567','Fossile wechselwarme Wirbeltiere, fossile Pisces (Fische)','567',1122,1123,68,0,1), +(612,2,'568','Fossile Aves (Vögel)','568',1124,1125,68,0,1), +(613,2,'569','Fossile Mammalia (Säugetiere)','569',1126,1127,68,0,1), +(614,2,'570','Biowissenschaften, Biologie','570',1130,1131,69,0,1), +(615,2,'571','Physiologie und verwandte Themen','571',1132,1133,69,0,1), +(616,2,'572','Biochemie','572',1134,1135,69,0,1), +(617,2,'573','Einzelne physiologische Systeme bei Tieren','573',1136,1137,69,0,1), +(618,2,'575','Einzelne Teile von und physiologische Systeme bei Pflanzen','575',1138,1139,69,0,1), +(619,2,'576','Genetik und Evolution','576',1140,1141,69,0,1), +(620,2,'577','Ökologie','577',1142,1143,69,0,1), +(621,2,'578','Naturgeschichte von Organismen','578',1144,1145,69,0,1), +(622,2,'579','Mikroorganismen, Pilze, Algen','579',1146,1147,69,0,1), +(623,2,'580','Pflanzen (Botanik)','580',1150,1151,70,0,1), +(624,2,'581','Einzelne Themen in der Naturgeschichte','581',1152,1153,70,0,1), +(625,2,'582','Pflanzen mit spezifischen Merkmalen und Blüten','582',1154,1155,70,0,1), +(626,2,'583','Magnoliopsida (Zweikeimblättrige)','583',1156,1157,70,0,1), +(627,2,'584','Liliopsida (Einkeimblättrige)','584',1158,1159,70,0,1), +(628,2,'585','Gymnospermae (Nacktsamer), Coniferae (Nadelgehölze)','585',1160,1161,70,0,1), +(629,2,'586','Cryptogamia (Blütenlose Pflanzen)','586',1162,1163,70,0,1), +(630,2,'587','Pteridophyta (Farnpflanzen)','587',1164,1165,70,0,1), +(631,2,'588','Bryophyta (Moose)','588',1166,1167,70,0,1), +(632,2,'590','Tiere (Zoologie)','590',1170,1171,71,0,1), +(633,2,'591','Einzelne Themen in der Naturgeschichte','591',1172,1173,71,0,1), +(634,2,'592','Evertebrata (Wirbellose)','592',1174,1175,71,0,1), +(635,2,'593','Wirbellose des Meeres und der Meeresküste','593',1176,1177,71,0,1), +(636,2,'594','Mollusca (Weichtiere), Tentaculata (Kranzfühler)','594',1178,1179,71,0,1), +(637,2,'595','Arthropoden (Gliederfüßer)','595',1180,1181,71,0,1), +(638,2,'596','Chordata (Chordatiere)','596',1182,1183,71,0,1), +(639,2,'597','Wechselwarme Wirbeltiere, Pisces (Fische)','597',1184,1185,71,0,1), +(640,2,'598','Aves (Vögel)','598',1186,1187,71,0,1), +(641,2,'599','Mammalia (Säugetiere)','599',1188,1189,71,0,1), +(642,2,'600','Technik, Technologie','600',1194,1195,72,0,1), +(643,2,'601','Philosophie, Theorie','601',1196,1197,72,0,1), +(644,2,'602','Verschiedenes','602',1198,1199,72,0,1), +(645,2,'603','Wörterbücher, Enzyklopädien','603',1200,1201,72,0,1), +(646,2,'604','Spezielle Themen','604',1202,1203,72,0,1), +(647,2,'605','Fortlaufende Sammelwerke','605',1204,1205,72,0,1), +(648,2,'606','Organisationen','606',1206,1207,72,0,1), +(649,2,'607','Ausbildung, Forschung, verwandte Themen','607',1208,1209,72,0,1), +(650,2,'608','Erfindungen, Patente','608',1210,1211,72,0,1), +(651,2,'609','Histor., geogr., personenbezogene Behandlung','609',1212,1213,72,0,1), +(652,2,'610','Medizin und Gesundheit','610',1216,1217,73,0,1), +(653,2,'611','Menschliche Anatomie, Zytologie, Histologie','611',1218,1219,73,0,1), +(654,2,'612','Humanphysiologie','612',1220,1221,73,0,1), +(655,2,'613','Persönliche Gesundheit und Sicherheit','613',1222,1223,73,0,1), +(656,2,'614','Inzidenz und Prävention von Krankheiten','614',1224,1225,73,0,1), +(657,2,'615','Pharmakologie, Therapeutik','615',1226,1227,73,0,1), +(658,2,'616','Krankheiten','616',1228,1229,73,0,1), +(659,2,'617','Chirurgie und verwandte medizinische Fachrichtungen','617',1230,1231,73,0,1), +(660,2,'618','Gynäkologie, Geburtsmedizin, Pädiatrie, Geriatrie','618',1232,1233,73,0,1), +(661,2,'620','Ingenieurwissenschaften und zugeordnete Tätigkeiten','620',1236,1237,74,0,1), +(662,2,'621','Angewandte Physik','621',1238,1239,74,0,1), +(663,2,'622','Bergbau und verwandte Tätigkeiten','622',1240,1241,74,0,1), +(664,2,'623','Militär- und Schiffstechnik','623',1242,1243,74,0,1), +(665,2,'624','Ingenieurbau','624',1244,1245,74,0,1), +(666,2,'625','Eisenbahn- und Straßenbau','625',1246,1247,74,0,1), +(667,2,'627','Wasserbau','627',1248,1249,74,0,1), +(668,2,'628','Sanitär- und Kommunaltechnik, Umwelttechnik','628',1250,1251,74,0,1), +(669,2,'629','Andere Fachrichtungen der Ingenieurwissenschaften','629',1252,1253,74,0,1), +(670,2,'630','Landwirtschaft und verwandte Bereiche','630',1256,1257,75,0,1), +(671,2,'631','Techniken, Ausstattung, Materialien','631',1258,1259,75,0,1), +(672,2,'632','Schäden, Krankheiten, Schädlinge an Pflanzen','632',1260,1261,75,0,1), +(673,2,'633','Feld- und Plantagenfrüchte','633',1262,1263,75,0,1), +(674,2,'634','Obstanlagen, Früchte, Forstwirtschaft','634',1264,1265,75,0,1), +(675,2,'635','Gartenpflanzen (Gartenbau)','635',1266,1267,75,0,1), +(676,2,'636','Viehwirtschaft','636',1268,1269,75,0,1), +(677,2,'637','Milchverarbeitung und verwandte Produkte','637',1270,1271,75,0,1), +(678,2,'638','Insektenzucht','638',1272,1273,75,0,1), +(679,2,'639','Jagd, Fischfang, Naturschutz','639',1274,1275,75,0,1), +(680,2,'640','Hauswirtschaft und Familie','640',1278,1279,76,0,1), +(681,2,'641','Essen und Trinken','641',1280,1281,76,0,1), +(682,2,'642','Mahlzeiten, Tischkultur','642',1282,1283,76,0,1), +(683,2,'643','Wohnen, Haushaltsausstattung','643',1284,1285,76,0,1), +(684,2,'644','Gebäudeversorgung für Haushalte','644',1286,1287,76,0,1), +(685,2,'645','Einrichtungsgegenstände','645',1288,1289,76,0,1), +(686,2,'646','Nähen, Kleidung, persönliches Leben, Familienleben','646',1290,1291,76,0,1), +(687,2,'647','Großhaushaltsführung','647',1292,1293,76,0,1), +(688,2,'648','Haushaltsführung','648',1294,1295,76,0,1), +(689,2,'649','Kindererziehung, häusliche Betreuung','649',1296,1297,76,0,1), +(690,2,'650','Management und unterstützende Tätigkeiten','650',1300,1301,77,0,1), +(691,2,'651','Büroarbeit','651',1302,1303,77,0,1), +(692,2,'652','Techniken der schriftlichen Kommunikation','652',1304,1305,77,0,1), +(693,2,'653','Stenografie','653',1306,1307,77,0,1), +(694,2,'657','Rechnungslegung','657',1308,1309,77,0,1), +(695,2,'658','Allgemeines Management','658',1310,1311,77,0,1), +(696,2,'659','Werbung, Öffentlichkeitsarbeit','659',1312,1313,77,0,1), +(697,2,'660','Chemische Verfahrenstechnik','660',1316,1317,78,0,1), +(698,2,'661','Industriechemikalien','661',1318,1319,78,0,1), +(699,2,'662','Explosivstoffe, Brennstoffe und verwandte Produkte','662',1320,1321,78,0,1), +(700,2,'663','Getränketechnologie','663',1322,1323,78,0,1), +(701,2,'664','Lebensmitteltechnologie','664',1324,1325,78,0,1), +(702,2,'665','Industrielle Öle, Fette, Wachse, technische Gase','665',1326,1327,78,0,1), +(703,2,'666','Keramiktechnologie und zugeordnete Technologien','666',1328,1329,78,0,1), +(704,2,'667','Reinigungs-, Färbe-, Beschichtungstechniken','667',1330,1331,78,0,1), +(705,2,'668','Technik anderer organischer Produkte','668',1332,1333,78,0,1), +(706,2,'669','Metallurgie','669',1334,1335,78,0,1), +(707,2,'670','Industrielle Fertigung','670',1338,1339,79,0,1), +(708,2,'671','Metallverarbeitung und Rohprodukte aus Metall','671',1340,1341,79,0,1), +(709,2,'672','Eisen, Stahl, andere Eisenlegierungen','672',1342,1343,79,0,1), +(710,2,'673','Nichteisenmetalle','673',1344,1345,79,0,1), +(711,2,'674','Holzverarbeitung, Holzprodukte, Kork','674',1346,1347,79,0,1), +(712,2,'675','Leder- und Pelzverarbeitung','675',1348,1349,79,0,1), +(713,2,'676','Zellstoff und Papierherstellung','676',1350,1351,79,0,1), +(714,2,'677','Textilien','677',1352,1353,79,0,1), +(715,2,'678','Elastomere, Elastomerprodukte','678',1354,1355,79,0,1), +(716,2,'679','Andere Produkte aus einzelnen Werkstoffen','679',1356,1357,79,0,1), +(717,2,'680','Industrielle Fertigung für einzelne Verwendungszwecke','680',1360,1361,80,0,1), +(718,2,'681','Präzisionsinstrumente und andere Geräte','681',1362,1363,80,0,1), +(719,2,'682','Schmiedehandwerk','682',1364,1365,80,0,1), +(720,2,'683','Eisenwaren, Haushaltsgeräte','683',1366,1367,80,0,1), +(721,2,'684','Wohnungseinrichtung, Heimwerkstätten','684',1368,1369,80,0,1), +(722,2,'685','Leder- und Pelzwaren und verwandte Produkte','685',1370,1371,80,0,1), +(723,2,'686','Drucken und verwandte Tätigkeiten','686',1372,1373,80,0,1), +(724,2,'687','Kleidung, Accessoires','687',1374,1375,80,0,1), +(725,2,'688','Andere Endprodukte, Verpackungstechnik','688',1376,1377,80,0,1), +(726,2,'690','Hausbau, Bauhandwerk','690',1380,1381,81,0,1), +(727,2,'691','Baustoffe','691',1382,1383,81,0,1), +(728,2,'692','Bauhilfstechniken','692',1384,1385,81,0,1), +(729,2,'693','Einzelne Baustoffarten und Zwecke','693',1386,1387,81,0,1), +(730,2,'694','Holzbau, Zimmerhandwerk','694',1388,1389,81,0,1), +(731,2,'695','Dachdeckung','695',1390,1391,81,0,1), +(732,2,'696','Versorgungseinrichtungen','696',1392,1393,81,0,1), +(733,2,'697','Heizungs-, Lüftungs-, Klimatechnik','697',1394,1395,81,0,1), +(734,2,'698','Ausbau','698',1396,1397,81,0,1), +(735,2,'700','Künste, Bildende und angewandte Kunst','700',1402,1403,82,0,1), +(736,2,'701','Kunstphilosophie, Kunsttheorie der bildenden und angewandten Kunst','701',1404,1405,82,0,1), +(737,2,'702','Verschiedenes zur bildenden und angewandten Kunst','702',1406,1407,82,0,1), +(738,2,'703','Wörterbücher, Enzyklopädien zur bildenden und angewandten Kunst','703',1408,1409,82,0,1), +(739,2,'704','Spezielle Themen zur bildenden und angewandten Kunst','704',1410,1411,82,0,1), +(740,2,'705','Fortlaufende Sammelwerke zur bildenden und angewandten Kunst','705',1412,1413,82,0,1), +(741,2,'706','Organisationen, Management der bildenden und angewandten Kunst','706',1414,1415,82,0,1), +(742,2,'707','Ausbildung, Forschung, verwandte Themen zur bildenden und angewandten Kunst','707',1416,1417,82,0,1), +(743,2,'708','Galerien, Museen, Privatsammlungen zur bildenden und angewandten Kunst','708',1418,1419,82,0,1), +(744,2,'709','Histor., geogr., personenbezogene Behandlung der bildenden und angewandten Kunst','709',1420,1421,82,0,1), +(745,2,'710','Städtebau, Raumplanung, Landschaftsgestaltung','710',1424,1425,83,0,1), +(746,2,'711','Raumplanung','711',1426,1427,83,0,1), +(747,2,'712','Landschaftsgestaltung','712',1428,1429,83,0,1), +(748,2,'713','Landschaftsgestaltung von Verkehrswegen','713',1430,1431,83,0,1), +(749,2,'714','Wasser als Gestaltungselement','714',1432,1433,83,0,1), +(750,2,'715','Gehölze als Gestaltungselemente','715',1434,1435,83,0,1), +(751,2,'716','Krautige Pflanzen als Gestaltungselemente','716',1436,1437,83,0,1), +(752,2,'717','Andere Gestaltungselemente','717',1438,1439,83,0,1), +(753,2,'718','Landschaftsgestaltung von Friedhöfen','718',1440,1441,83,0,1), +(754,2,'719','Naturlandschaften','719',1442,1443,83,0,1), +(755,2,'720','Architektur','720',1446,1447,84,0,1), +(756,2,'721','Architektonische Struktur','721',1448,1449,84,0,1), +(757,2,'722','Architektur bis ca. 300','722',1450,1451,84,0,1), +(758,2,'723','Architektur von ca. 300 bis 1399','723',1452,1453,84,0,1), +(759,2,'724','Architektur ab 1400','724',1454,1455,84,0,1), +(760,2,'725','Öffentliche Bauwerke','725',1456,1457,84,0,1), +(761,2,'726','Gebäude für religiöse und verwandte Zwecke','726',1458,1459,84,0,1), +(762,2,'727','Gebäude für Lehr- und Forschungszwecke','727',1460,1461,84,0,1), +(763,2,'728','Wohnbauten und verwandte Gebäude','728',1462,1463,84,0,1), +(764,2,'729','Entwurf und Gestaltung, Innenarchitektur','729',1464,1465,84,0,1), +(765,2,'730','Plastische Künste, Bildhauerkunst','730',1468,1469,85,0,1), +(766,2,'731','Verfahren, Formen und Motive in der Bildhauerkunst','731',1470,1471,85,0,1), +(767,2,'732','Bildhauerei bis ca. 500','732',1472,1473,85,0,1), +(768,2,'733','Griechische, etruskische, römische Bildhauerkunst','733',1474,1475,85,0,1), +(769,2,'734','Bildhauerkunst von ca. 500 bis 1399','734',1476,1477,85,0,1), +(770,2,'735','Bildhauerkunst ab 1400','735',1478,1479,85,0,1), +(771,2,'736','Schnitzen, Schnitzereien','736',1480,1481,85,0,1), +(772,2,'737','Numismatik, Siegelkunde','737',1482,1483,85,0,1), +(773,2,'738','Keramikkunst','738',1484,1485,85,0,1), +(774,2,'739','Metallkunst','739',1486,1487,85,0,1), +(775,2,'740','Zeichnung, angewandte Kunst','740',1490,1491,86,1,1), +(776,2,'741','Zeichnung, Zeichnungen','741',1492,1493,86,0,1), +(777,2,'742','Perspektive','742',1496,1497,86,0,1), +(778,2,'743','Zeichnung und Zeichnungen nach Motiv','743',1498,1499,86,0,1), +(779,2,'745','Angewandte Kunst','745',1500,1501,86,0,1), +(780,2,'746','Textilkunst','746',1502,1503,86,0,1), +(781,2,'747','Innendekoration','747',1504,1505,86,0,1), +(782,2,'748','Glas','748',1506,1507,86,0,1), +(783,2,'749','Möbel, Möbelzubehör','749',1508,1509,86,0,1), +(784,2,'750','Malerei, Gemälde','750',1512,1513,87,0,1), +(785,2,'751','Techniken, Ausstattung, Materialien, Formen','751',1514,1515,87,0,1), +(786,2,'752','Farbe','752',1516,1517,87,0,1), +(787,2,'753','Symbolik, Allegorie, Mythologie, Legende','753',1518,1519,87,0,1), +(788,2,'754','Genremalerei','754',1520,1521,87,0,1), +(789,2,'755','Religion','755',1522,1523,87,0,1), +(790,2,'757','Menschliche Figuren','757',1524,1525,87,0,1), +(791,2,'758','Andere Motive','758',1526,1527,87,0,1), +(792,2,'759','Histor., geogr., personenbezogene Behandlung','759',1528,1529,87,0,1), +(793,2,'760','Grafik, Druckgrafik, Drucke','760',1532,1533,88,0,1), +(794,2,'761','Hochdruckverfahren (Blockdruck)','761',1534,1535,88,0,1), +(795,2,'763','Lithografische Druckverfahren','763',1536,1537,88,0,1), +(796,2,'764','Farblithografie, Serigrafie','764',1538,1539,88,0,1), +(797,2,'765','Metallgravur','765',1540,1541,88,0,1), +(798,2,'766','Mezzotinto, Aquatinta und verwandte Techniken','766',1542,1543,88,0,1), +(799,2,'767','Radierung, Kaltnadelarbeit','767',1544,1545,88,0,1), +(800,2,'769','Drucke','769',1546,1547,88,0,1), +(801,2,'770','Fotografie, Fotografien, Computerkunst','770',1550,1551,89,0,1), +(802,2,'771','Techniken, Ausstattung, Materialien','771',1552,1553,89,0,1), +(803,2,'772','Entwicklungsverfahren mit Metallsalzen','772',1554,1555,89,0,1), +(804,2,'773','Pigmentdruckverfahren','773',1556,1557,89,0,1), +(805,2,'774','Holografie','774',1558,1559,89,0,1), +(806,2,'775','Digitale Fotografie','775',1560,1561,89,0,1), +(807,2,'776','Computerkunst (Digitale Kunst)','776',1562,1563,89,0,1), +(808,2,'778','Bereiche und Arten der Fotografie','778',1564,1565,89,0,1), +(809,2,'779','Fotografien','779',1566,1567,89,0,1), +(810,2,'780','Musik','780',1570,1571,90,0,1), +(811,2,'781','Allgemeine Prinzipien, musikalische Formen','781',1572,1573,90,0,1), +(812,2,'782','Vokalmusik','782',1574,1575,90,0,1), +(813,2,'783','Musik für Einzelstimmen, die Stimme','783',1576,1577,90,0,1), +(814,2,'784','Instrumente, Instrumentalensembles','784',1578,1579,90,0,1), +(815,2,'785','Ensembles mit einem Instrument pro Stimme','785',1580,1581,90,0,1), +(816,2,'786','Tasteninstrumente, andere Instrumente','786',1582,1583,90,0,1), +(817,2,'787','Saiteninstrumente','787',1584,1585,90,0,1), +(818,2,'788','Blasinstrumente','788',1586,1587,90,0,1), +(819,2,'789','(Optionale Notation)','789',1588,1589,90,0,1), +(820,2,'790','Freizeitgestaltung, darstellende Künste, Sport','790',1592,1593,91,1,1), +(821,2,'791','Öffentliche Darbietungen, Film, Rundfunk','791',1594,1595,91,1,1), +(822,2,'792','Bühnenkunst','792',1596,1597,91,1,1), +(823,2,'793','Spiele und Freizeitaktivitäten für drinnen','793',1598,1599,91,1,1), +(824,2,'794','Unterhaltungsspiele für drinnen','794',1600,1601,91,0,1), +(825,2,'795','Glücksspiele','795',1602,1603,91,0,1), +(826,2,'796','Sportarten, Sportspiele','796',1604,1605,91,1,1), +(827,2,'797','Wasser- und Luftsport','797',1606,1607,91,0,1), +(828,2,'798','Pferdesport, Tierrennen','798',1608,1609,91,0,1), +(829,2,'799','Fischfang, Jagd, Schießen','799',1610,1611,91,0,1), +(830,2,'800','Literatur und Rhetorik','800',1616,1617,92,0,1), +(831,2,'801','Literaturtheorie','801',1618,1619,92,0,1), +(832,2,'802','Verschiedenes','802',1620,1621,92,0,1), +(833,2,'803','Wörterbücher, Enzyklopädien','803',1622,1623,92,0,1), +(834,2,'805','Fortlaufende Sammelwerke','805',1624,1625,92,0,1), +(835,2,'806','Organisationen, Management','806',1626,1627,92,0,1), +(836,2,'807','Ausbildung, Forschung, verwandte Themen','807',1628,1629,92,0,1), +(837,2,'808','Rhetorik, Sammlungen von Literatur','808',1630,1631,92,0,1), +(838,2,'809','Geschichte, Darstellung, Literaturwissenschaft und –k ritik','809',1632,1633,92,0,1), +(839,2,'810','Amerikanische Literatur in in Englisch','810',1636,1637,93,0,1), +(840,2,'811','Amerikanische Versdichtung','811',1638,1639,93,0,1), +(841,2,'812','Amerikanische Dramen','812',1640,1641,93,0,1), +(842,2,'813','Amerikanische Erzählprosa','813',1642,1643,93,0,1), +(843,2,'814','Amerikanische Essays','814',1644,1645,93,0,1), +(844,2,'815','Amerikanische Reden','815',1646,1647,93,0,1), +(845,2,'816','Amerikanische Briefe','816',1648,1649,93,0,1), +(846,2,'817','Amerikanischer Humor, amerikanische Satire','817',1650,1651,93,0,1), +(847,2,'818','Amerikanische vermischte Schriften','818',1652,1653,93,0,1), +(848,2,'819','(Optionale Notation)','819',1654,1655,93,0,1), +(849,2,'820','Englische, altenglische Literaturen','820',1658,1659,94,0,1), +(850,2,'821','Englische Versdichtung','821',1660,1661,94,0,1), +(851,2,'822','Englische Dramen','822',1662,1663,94,0,1), +(852,2,'823','Englische Erzählprosa','823',1664,1665,94,0,1), +(853,2,'824','Englische Essays','824',1666,1667,94,0,1), +(854,2,'825','Englische Reden','825',1668,1669,94,0,1), +(855,2,'826','Englische Briefe','826',1670,1671,94,0,1), +(856,2,'827','Englischer Humor, englische Satire','827',1672,1673,94,0,1), +(857,2,'828','Englische vermischte Schriften','828',1674,1675,94,0,1), +(858,2,'829','Altenglische (Angelsächsische) Literatur','829',1676,1677,94,0,1), +(859,2,'830','Literaturen germanischer Sprachen, Deutsche Literatur','830',1680,1681,95,1,1), +(860,2,'831','Deutsche Versdichtung','831',1682,1683,95,0,1), +(861,2,'832','Deutsche Dramen','832',1684,1685,95,0,1), +(862,2,'833','Deutsche Erzählprosa','833',1686,1687,95,0,1), +(863,2,'834','Deutsche Essays','834',1688,1689,95,0,1), +(864,2,'835','Deutsche Reden','835',1690,1691,95,0,1), +(865,2,'836','Deutsche Briefe','836',1692,1693,95,0,1), +(866,2,'837','Deutscher Humor, deutsche Satire','837',1694,1695,95,0,1), +(867,2,'838','Deutsche vermischte Schriften','838',1696,1697,95,0,1), +(868,2,'839','Andere germanische Literaturen','839',1698,1699,95,1,1), +(869,2,'840','Literaturen romanischer Sprachen, Französische Literatur','840',1702,1703,96,0,1), +(870,2,'841','Französische Versdichtung','841',1704,1705,96,0,1), +(871,2,'842','Französische Dramen','842',1706,1707,96,0,1), +(872,2,'843','Französische Erzählprosa','843',1708,1709,96,0,1), +(873,2,'844','Französische Essays','844',1710,1711,96,0,1), +(874,2,'845','Französische Reden','845',1712,1713,96,0,1), +(875,2,'846','Französische Briefe','846',1714,1715,96,0,1), +(876,2,'847','Französischer Humor, französische Satire','847',1716,1717,96,0,1), +(877,2,'848','Französische vermischte Schriften','848',1718,1719,96,0,1), +(878,2,'849','Okzitanische, katalanische Literaturen','849',1720,1721,96,0,1), +(879,2,'850','Italienische, rumänische, rätoromanische Literaturen','850',1724,1725,97,0,1), +(880,2,'851','Italienische Versdichtung','851',1726,1727,97,0,1), +(881,2,'852','Italienische Dramen','852',1728,1729,97,0,1), +(882,2,'853','Italienische Erzählprosa','853',1730,1731,97,0,1), +(883,2,'854','Italienische Essays','854',1732,1733,97,0,1), +(884,2,'855','Italienische Reden','855',1734,1735,97,0,1), +(885,2,'856','Italienische Briefe','856',1736,1737,97,0,1), +(886,2,'857','Italienischer Humor, italienische Satire','857',1738,1739,97,0,1), +(887,2,'858','Italienische vermischte Schriften','858',1740,1741,97,0,1), +(888,2,'859','Rumänische, rätoromanische Literaturen','859',1742,1743,97,0,1), +(889,2,'860','Spanische, portugiesische Literaturen','860',1746,1747,98,0,1), +(890,2,'861','Spanische Versdichtung','861',1748,1749,98,0,1), +(891,2,'862','Spanische Dramen','862',1750,1751,98,0,1), +(892,2,'863','Spanische Erzählprosa','863',1752,1753,98,0,1), +(893,2,'864','Spanische Essays','864',1754,1755,98,0,1), +(894,2,'865','Spanische Reden','865',1756,1757,98,0,1), +(895,2,'866','Spanische Briefe','866',1758,1759,98,0,1), +(896,2,'867','Spanischer Humor, spanische Satire','867',1760,1761,98,0,1), +(897,2,'868','Spanische vermischte Schriften','868',1762,1763,98,0,1), +(898,2,'869','Portugiesische Literatur','869',1764,1765,98,0,1), +(899,2,'870','Italische Literaturen, Lateinische Literatur','870',1768,1769,99,0,1), +(900,2,'871','Lateinische Versdichtung','871',1770,1771,99,0,1), +(901,2,'872','Lateinische dramatische Versdichtung, Dramen','872',1772,1773,99,0,1), +(902,2,'873','Lateinische erzählende Versdichtung, Erzählprosa','873',1774,1775,99,0,1), +(903,2,'874','Lateinische lyrische Versdichtung','874',1776,1777,99,0,1), +(904,2,'875','Lateinische Reden','875',1778,1779,99,0,1), +(905,2,'876','Lateinische Briefe','876',1780,1781,99,0,1), +(906,2,'877','Lateinischer Humor, lateinische Satire','877',1782,1783,99,0,1), +(907,2,'878','Lateinische vermischte Schriften','878',1784,1785,99,0,1), +(908,2,'879','Literaturen anderer italischer Sprachen','879',1786,1787,99,0,1), +(909,2,'880','Hellenische Literaturen, Klassische griechische Literatur','880',1790,1791,100,0,1), +(910,2,'881','Klassische griechische Versdichtung','881',1792,1793,100,0,1), +(911,2,'882','Klassische griechische dramatische Versdichtung, Dramen','882',1794,1795,100,0,1), +(912,2,'883','Klassische griechische erzählende Versdichtung, Erzählprosa','883',1796,1797,100,0,1), +(913,2,'884','Klassische griechische lyrische Versdichtung','884',1798,1799,100,0,1), +(914,2,'885','Klassische griechische Reden','885',1800,1801,100,0,1), +(915,2,'886','Klassische griechische Briefe','886',1802,1803,100,0,1), +(916,2,'887','Humor und Satire in klassischem Griechisch','887',1804,1805,100,0,1), +(917,2,'888','Klassische griechische vermischte Schriften','888',1806,1807,100,0,1), +(918,2,'889','Neugriechische Literatur','889',1808,1809,100,0,1), +(919,2,'890','Literaturen anderer Sprachen','890',1812,1813,101,0,1), +(920,2,'891','Ostindoeuropäische, keltische Literaturen','891',1814,1815,101,0,1), +(921,2,'892','Afroasiatische Literaturen, Semitische Literaturen','892',1816,1817,101,0,1), +(922,2,'893','Nichtsemitische afroasiatische Literaturen','893',1818,1819,101,0,1), +(923,2,'894','Altaische, uralische, paläosibirische, drawidische Literaturen','894',1820,1821,101,0,1), +(924,2,'895','Ost- und südostasiatische Literaturen','895',1822,1823,101,0,1), +(925,2,'896','Afrikanische Literaturen','896',1824,1825,101,0,1), +(926,2,'897','Literaturen nordamerikanischer Indianersprachen','897',1826,1827,101,0,1), +(927,2,'898','Literaturen südamerikanischer Indianersprachen','898',1828,1829,101,0,1), +(928,2,'899','Austronesische und andere Literaturen','899',1830,1831,101,0,1), +(929,2,'900','Geschichte und Geografie','900',1836,1837,102,0,1), +(930,2,'901','Geschichtsphilosophie, Geschichtstheorie','901',1838,1839,102,0,1), +(931,2,'902','Verschiedenes','902',1840,1841,102,0,1), +(932,2,'903','Wörterbücher, Enzyklopädien','903',1842,1843,102,0,1), +(933,2,'904','Allgemeine Darstellungen von Ereignissen','904',1844,1845,102,0,1), +(934,2,'905','Fortlaufende Sammelwerke','905',1846,1847,102,0,1), +(935,2,'906','Organisationen, Management','906',1848,1849,102,0,1), +(936,2,'907','Ausbildung, Forschung, verwandte Themen','907',1850,1851,102,0,1), +(937,2,'908','Behandlung nach Personengruppen','908',1852,1853,102,0,1), +(938,2,'909','Weltgeschichte','909',1854,1855,102,0,1), +(939,2,'910','Geografie, Reisen','910',1858,1859,103,1,1), +(940,2,'911','Historische Geografie','911',1860,1861,103,0,1), +(941,2,'912','Atlanten, Karten, Grafiken, Pläne','912',1862,1863,103,0,1), +(942,2,'913','Geografie der und Reisen in der Alten Welt','913',1864,1865,103,0,1), +(943,2,'914','Geografie Europas und Reisen in Europa','914',1866,1867,103,0,1), +(944,2,'915','Geografie Asiens und Reisen in Asien','915',1870,1871,103,0,1), +(945,2,'916','Geografie Afrikas und Reisen in Afrika','916',1872,1873,103,0,1), +(946,2,'917','Geografie Nordamerikas und Reisen in Nordamerika','917',1874,1875,103,0,1), +(947,2,'918','Geografie Südamerikas und Reisen in Südamerika','918',1876,1877,103,0,1), +(948,2,'919','Geografie anderer Gebiete und Reisen in anderen Gebieten','919',1878,1879,103,0,1), +(949,2,'920','Biografien, Genealogie, Insignien','920',1882,1883,104,0,1), +(950,2,'921','(Optionale Notation)','921',1884,1885,104,0,1), +(951,2,'922','(Optionale Notation)','922',1886,1887,104,0,1), +(952,2,'923','(Optionale Notation)','923',1888,1889,104,0,1), +(953,2,'924','(Optionale Notation)','924',1890,1891,104,0,1), +(954,2,'925','(Optionale Notation)','925',1892,1893,104,0,1), +(955,2,'926','(Optionale Notation)','926',1894,1895,104,0,1), +(956,2,'927','(Optionale Notation)','927',1896,1897,104,0,1), +(957,2,'928','(Optionale Notation)','928',1898,1899,104,0,1), +(958,2,'929','Genealogie, Namenkunde, Insignien','929',1900,1901,104,0,1), +(959,2,'930','Geschichte des Altertums bis ca. 499, Archäologie','930',1904,1905,105,0,1), +(960,2,'931','Geschichte Chinas bis 420','931',1906,1907,105,0,1), +(961,2,'932','Geschichte Ägyptens bis 640','932',1908,1909,105,0,1), +(962,2,'933','Geschichte Palästinas bis 70','933',1910,1911,105,0,1), +(963,2,'934','Geschichte Indiens bis 647','934',1912,1913,105,0,1), +(964,2,'935','Geschichte Mesopotamiens und der iranischen Hochebene bis 637','935',1914,1915,105,0,1), +(965,2,'936','Geschichte Europas nördlich und westlich von Italien bis ca. 499','936',1916,1917,105,0,1), +(966,2,'937','Geschichte Italiens und benachbarter Gebiete bis 476','937',1918,1919,105,0,1), +(967,2,'938','Geschichte Griechenlands bis 323','938',1920,1921,105,0,1), +(968,2,'939','Geschichte anderer Teile der Welt bis ca. 640','939',1922,1923,105,0,1), +(969,2,'940','Geschichte Europas','940',1926,1927,106,1,1), +(970,2,'941','Geschichte der Britischen Inseln','941',1928,1929,106,0,1), +(971,2,'942','Geschichte Englands und Wales','942',1930,1931,106,0,1), +(972,2,'943','Geschichte Mitteleuropas, Deutschlands','943',1932,1933,106,1,1), +(973,2,'944','Geschichte Frankreichs und Monacos','944',1934,1935,106,0,1), +(974,2,'945','Geschichte der italienische Halbinsel und benachbarter Inseln','945',1936,1937,106,0,1), +(975,2,'946','Geschichte der iberischen Halbinsel und benachbarter Inseln','946',1938,1939,106,0,1), +(976,2,'947','Geschichte Osteuropas, Russlands','947',1940,1941,106,0,1), +(977,2,'948','Geschichte Skandinaviens','948',1942,1943,106,0,1), +(978,2,'949','Geschichte anderer Teile Europas','949',1944,1945,106,0,1), +(979,2,'950','Geschichte Asiens, des Fernen Ostens','950',1948,1949,107,0,1), +(980,2,'951','Geschichte Chinas und benachbarter Gebiete','951',1950,1951,107,0,1), +(981,2,'952','Geschichte Japans','952',1952,1953,107,0,1), +(982,2,'953','Geschichte der arabischen Halbinsel und benachbarter Gebiete','953',1954,1955,107,0,1), +(983,2,'954','Geschichte Südasiens, Indiens','954',1956,1957,107,0,1), +(984,2,'955','Geschichte Irans','955',1958,1959,107,0,1), +(985,2,'956','Geschichte des Nahen Ostens (Mittleren Ostens)','956',1960,1961,107,0,1), +(986,2,'957','Geschichte Sibiriens (der Asiatischen Russlands)','957',1962,1963,107,0,1), +(987,2,'958','Geschichte Zentralasiens','958',1964,1965,107,0,1), +(988,2,'959','Geschichte Südostasiens','959',1966,1967,107,0,1), +(989,2,'960','Geschichte Afrikas','960',1970,1971,108,0,1), +(990,2,'961','Geschichte Tunesiens und Libyens','961',1972,1973,108,0,1), +(991,2,'962','Geschichte Ägyptens und Sudans','962',1974,1975,108,0,1), +(992,2,'963','Geschichte Äthiopiens und Eritreas','963',1976,1977,108,0,1), +(993,2,'964','Geschichte der nordwestafrikanischen Küste und vorgelagerter Inseln','964',1978,1979,108,0,1), +(994,2,'965','Geschichte Algeriens','965',1980,1981,108,0,1), +(995,2,'966','Geschichte Westafrikas und vorgelagerter Inseln','966',1982,1983,108,0,1), +(996,2,'967','Geschichte Zentralafrikas und vorgelagerter Inseln','967',1984,1985,108,0,1), +(997,2,'968','Geschichte Südafrikas, der Republik Südafrika','968',1986,1987,108,0,1), +(998,2,'969','Geschichte der Inseln im südlichen Indischen Ozean','969',1988,1989,108,0,1), +(999,2,'970','Geschichte Nordamerikas','970',1992,1993,109,0,1), +(1000,2,'971','Geschichte Kanadas','971',1994,1995,109,0,1), +(1001,2,'972','Geschichte Mittelamerikas, Mexikos','972',1996,1997,109,0,1), +(1002,2,'973','Geschichte der USA','973',1998,1999,109,0,1), +(1003,2,'974','Geschichte der nordöstlichen Staaten der USA','974',2000,2001,109,0,1), +(1004,2,'975','Geschichte der südöstlichen Staaten der USA','975',2002,2003,109,0,1), +(1005,2,'976','Geschichte der südlichen zentralen Staaten der USA','976',2004,2005,109,0,1), +(1006,2,'977','Geschichte der nördlichen zentralen Staaten der USA','977',2006,2007,109,0,1), +(1007,2,'978','Geschichte der westlichen Staaten der USA','978',2008,2009,109,0,1), +(1008,2,'979','Geschichte der Staaten des Großen Beckens und der pazifischen Gebirgsketten','979',2010,2011,109,0,1), +(1009,2,'980','Geschichte Südamerikas','980',2014,2015,110,0,1), +(1010,2,'981','Geschichte Brasiliens','981',2016,2017,110,0,1), +(1011,2,'982','Geschichte Argentiniens','982',2018,2019,110,0,1), +(1012,2,'983','Geschichte Chiles','983',2020,2021,110,0,1), +(1013,2,'984','Geschichte Boliviens','984',2022,2023,110,0,1), +(1014,2,'985','Geschichte Perus','985',2024,2025,110,0,1), +(1015,2,'986','Geschichte Kolumbiens und Ecuadors','986',2026,2027,110,0,1), +(1016,2,'987','Geschichte Venezuelas','987',2028,2029,110,0,1), +(1017,2,'988','Geschichte Guayanas','988',2030,2031,110,0,1), +(1018,2,'989','Geschichte Paraguays und Uruguays','989',2032,2033,110,0,1), +(1019,2,'990','Geschichte anderer Gebiete','990',2036,2037,111,0,1), +(1020,2,'993','Geschichte Neuseelands','993',2038,2039,111,0,1), +(1021,2,'994','Geschichte Australiens','994',2040,2041,111,0,1), +(1022,2,'995','Geschichte Melanesiens, Neuguineas','995',2042,2043,111,0,1), +(1023,2,'996','Geschichte anderer Teile des Pazifischen Ozeans, Polynesiens','996',2044,2045,111,0,1), +(1024,2,'997','Geschichte der atlantischen Inseln','997',2046,2047,111,0,1), +(1025,2,'998','Geschichte der arktischen Inseln und der Antarktis','998',2048,2049,111,0,1), +(1026,2,'999','Geschichte der außerirdischen Welten','999',2050,2051,111,0,1), +(1027,2,'741.5','Comics, Cartoons, Karikaturen','741.5',1494,1495,86,1,1), +(1028,2,'914.3','Landeskunde Deutschlands','914.3',1868,1869,103,1,1); + + + diff --git a/database/migrations/dataset_2_documents.ts b/database/migrations/dataset_2_documents.ts index 565e1f9..6629689 100644 --- a/database/migrations/dataset_2_documents.ts +++ b/database/migrations/dataset_2_documents.ts @@ -86,3 +86,22 @@ export default class Documents extends BaseSchema { // CONSTRAINT documents_server_state_check CHECK (server_state::text = ANY (ARRAY['deleted'::character varying::text, 'inprogress'::character varying::text, 'published'::character varying::text, 'released'::character varying::text, 'editor_accepted'::character varying::text, 'approved'::character varying::text, 'rejected_reviewer'::character varying::text, 'rejected_editor'::character varying::text, 'reviewed'::character varying::text])), // CONSTRAINT documents_type_check CHECK (type::text = ANY (ARRAY['analysisdata'::character varying::text, 'measurementdata'::character varying::text, 'monitoring'::character varying::text, 'remotesensing'::character varying::text, 'gis'::character varying::text, 'models'::character varying::text, 'mixedtype'::character varying::text])) // ) + + +// ALTER TABLE documents DROP CONSTRAINT documents_server_state_check; + +// ALTER TABLE documents +// ADD CONSTRAINT documents_server_state_check CHECK ( +// server_state::text = ANY (ARRAY[ +// 'deleted', +// 'inprogress', +// 'published', +// 'released', +// 'editor_accepted', +// 'approved', +// 'rejected_reviewer', +// 'rejected_editor', +// 'reviewed', +// 'rejected_to_reviewer' -- new value added +// ]::text[]) +// ); \ No newline at end of file diff --git a/database/migrations/dataset_6_collection_roles.ts b/database/migrations/dataset_6_collection_roles.ts index 73f83e8..1491d9a 100644 --- a/database/migrations/dataset_6_collection_roles.ts +++ b/database/migrations/dataset_6_collection_roles.ts @@ -32,3 +32,21 @@ export default class CollectionsRoles extends BaseSchema { // visible_oai boolean NOT NULL DEFAULT true, // CONSTRAINT collections_roles_pkey PRIMARY KEY (id) // ) + +// change to normal intzeger: +// ALTER TABLE collections_roles ALTER COLUMN id DROP DEFAULT; +// DROP SEQUENCE IF EXISTS collections_roles_id_seq; + +// -- Step 1: Temporarily change one ID to a value not currently used +// UPDATE collections_roles SET id = 99 WHERE name = 'ccs'; + +// -- Step 2: Change 'ddc' ID to 2 (the old 'ccs' ID) +// UPDATE collections_roles SET id = 2 WHERE name = 'ddc'; + +// -- Step 3: Change the temporary ID (99) to 3 (the old 'ddc' ID) +// UPDATE collections_roles SET id = 3 WHERE name = 'ccs'; + +// UPDATE collections_roles SET id = 99 WHERE name = 'bk'; +// UPDATE collections_roles SET id = 1 WHERE name = 'institutes'; +// UPDATE collections_roles SET id = 4 WHERE name = 'pacs'; +// UPDATE collections_roles SET id = 7 WHERE name = 'bk'; \ No newline at end of file diff --git a/database/migrations/dataset_7_collections.ts b/database/migrations/dataset_7_collections.ts index 4fe4b8b..b942111 100644 --- a/database/migrations/dataset_7_collections.ts +++ b/database/migrations/dataset_7_collections.ts @@ -5,7 +5,7 @@ export default class Collections extends BaseSchema { public async up() { this.schema.createTable(this.tableName, (table) => { - table.increments('id').defaultTo("nextval('collections_id_seq')"); + table.increments('id');//.defaultTo("nextval('collections_id_seq')"); table.integer('role_id').unsigned(); table .foreign('role_id', 'collections_role_id_foreign') @@ -25,6 +25,8 @@ export default class Collections extends BaseSchema { .onUpdate('CASCADE'); table.boolean('visible').notNullable().defaultTo(true); table.boolean('visible_publish').notNullable().defaultTo(true); + table.integer('left_id').unsigned(); + table.integer('right_id').unsigned(); }); } @@ -59,3 +61,26 @@ export default class Collections extends BaseSchema { // change to normal intzeger: // ALTER TABLE collections ALTER COLUMN id DROP DEFAULT; // DROP SEQUENCE IF EXISTS collections_id_seq; + + +// ALTER TABLE collections +// ADD COLUMN left_id INTEGER; +// COMMENT ON COLUMN collections.left_id IS 'comment'; +// ALTER TABLE collections +// ADD COLUMN right_id INTEGER; +// COMMENT ON COLUMN collections.right_id IS 'comment'; + +// -- Step 1: Drop the existing default +// ALTER TABLE collections +// ALTER COLUMN visible DROP DEFAULT, +// ALTER COLUMN visible_publish DROP DEFAULT; + +// -- Step 2: Change column types with proper casting +// ALTER TABLE collections +// ALTER COLUMN visible TYPE smallint USING CASE WHEN visible THEN 1 ELSE 0 END, +// ALTER COLUMN visible_publish TYPE smallint USING CASE WHEN visible_publish THEN 1 ELSE 0 END; + +// -- Step 3: Set new defaults as smallint +// ALTER TABLE collections +// ALTER COLUMN visible SET DEFAULT 1, +// ALTER COLUMN visible_publish SET DEFAULT 1; \ No newline at end of file diff --git a/index.d.ts b/index.d.ts index 8165192..f6767a1 100644 --- a/index.d.ts +++ b/index.d.ts @@ -183,3 +183,9 @@ declare module 'saxon-js' { export function transform(options: ITransformOptions): Promise<ITransformOutput> | ITransformOutput; } + +declare global { + interface File { + sort_order?: number; + } + } \ No newline at end of file diff --git a/package-lock.json b/package-lock.json index 6cf37e3..6b10877 100644 --- a/package-lock.json +++ b/package-lock.json @@ -9,6 +9,7 @@ "version": "1.0.0", "dependencies": { "@adonisjs/auth": "^9.2.4", + "@adonisjs/bodyparser": "^10.0.1", "@adonisjs/core": "^6.17.0", "@adonisjs/cors": "^2.2.1", "@adonisjs/drive": "^3.2.0", @@ -29,6 +30,7 @@ "@phc/format": "^1.0.0", "@poppinss/manager": "^5.0.2", "@vinejs/vine": "^3.0.0", + "argon2": "^0.43.0", "axios": "^1.7.9", "bcrypt": "^5.1.1", "bcryptjs": "^2.4.3", @@ -48,7 +50,7 @@ "notiwind": "^2.0.0", "pg": "^8.9.0", "qrcode": "^1.5.3", - "redis": "^4.6.10", + "redis": "^5.0.0", "reflect-metadata": "^0.2.1", "saxon-js": "^2.5.0", "toastify-js": "^1.12.0", @@ -89,7 +91,7 @@ "eslint-plugin-prettier": "^5.0.0-alpha.2", "hot-hook": "^0.4.0", "numeral": "^2.0.6", - "pinia": "^2.0.30", + "pinia": "^3.0.2", "pino-pretty": "^13.0.0", "postcss-loader": "^8.1.1", "prettier": "^3.4.2", @@ -129,16 +131,16 @@ } }, "node_modules/@adonisjs/application": { - "version": "8.3.1", - "resolved": "https://registry.npmjs.org/@adonisjs/application/-/application-8.3.1.tgz", - "integrity": "sha512-hfZBgZ23BQAXvoSHDkc/I0hTSXyFVxypNqHPQ/WCk4VoWlBVWVgGaGnHLvIGhrZ3RMvyoC5NBgC0PR5G+/fGSw==", + "version": "8.4.1", + "resolved": "https://registry.npmjs.org/@adonisjs/application/-/application-8.4.1.tgz", + "integrity": "sha512-2vwO/8DoKJ9AR4Vvllz08RcomBoETc3FMf+q+ri1BVVjc76tLGV3KcYZp8+uKOuEreiK6poQ7NwJrR1P5ANA/w==", "license": "MIT", "dependencies": { - "@poppinss/hooks": "^7.2.3", - "@poppinss/macroable": "^1.0.2", - "@poppinss/utils": "^6.7.3", + "@poppinss/hooks": "^7.2.5", + "@poppinss/macroable": "^1.0.4", + "@poppinss/utils": "^6.9.3", "glob-parent": "^6.0.2", - "tempura": "^0.4.0" + "tempura": "^0.4.1" }, "engines": { "node": ">=18.16.0" @@ -180,9 +182,9 @@ } }, "node_modules/@adonisjs/auth": { - "version": "9.3.2", - "resolved": "https://registry.npmjs.org/@adonisjs/auth/-/auth-9.3.2.tgz", - "integrity": "sha512-ZaOeSEsCMZkXlfS3YYp2fXh6Eri/uq87mHmhW/uN8/Iww7VlpJbaacGokwHk1gBvU3hScYNVYwiazn3jkcNygw==", + "version": "9.4.0", + "resolved": "https://registry.npmjs.org/@adonisjs/auth/-/auth-9.4.0.tgz", + "integrity": "sha512-dzvnJRKY+RcKUXCRT6ebnlGV0wAfejTSGqS0XbgjB97r6Pww14MhsY89EBr1nSydQzvjdbtIR3EDGbU97BVmbQ==", "license": "MIT", "dependencies": { "@adonisjs/presets": "^2.6.4", @@ -219,18 +221,18 @@ } }, "node_modules/@adonisjs/bodyparser": { - "version": "10.0.3", - "resolved": "https://registry.npmjs.org/@adonisjs/bodyparser/-/bodyparser-10.0.3.tgz", - "integrity": "sha512-rgnAE+w7/+8tlCG+GxT8/99TLyccMFHtUyIP99K4YbSg0af6kTHrbXOJkKE8YHKU8cFwECybu3uZOoIoHOYLyQ==", + "version": "10.1.0", + "resolved": "https://registry.npmjs.org/@adonisjs/bodyparser/-/bodyparser-10.1.0.tgz", + "integrity": "sha512-sQVi1WASKSONr6DDG0YGf4rcd7Hfm9D5fdAqGcH1NWUfVP+2+6ogg0Z++X0a4wRbS7bU3TthTDmMX2n+839Cww==", "license": "MIT", "dependencies": { "@paralleldrive/cuid2": "^2.2.2", "@poppinss/macroable": "^1.0.4", "@poppinss/multiparty": "^2.0.1", - "@poppinss/utils": "^6.9.2", + "@poppinss/utils": "^6.9.3", "@types/qs": "^6.9.18", "bytes": "^3.1.2", - "file-type": "^20.1.0", + "file-type": "^20.5.0", "inflation": "^2.1.0", "media-typer": "^1.1.0", "qs": "^6.14.0", @@ -244,42 +246,42 @@ } }, "node_modules/@adonisjs/config": { - "version": "5.0.2", - "resolved": "https://registry.npmjs.org/@adonisjs/config/-/config-5.0.2.tgz", - "integrity": "sha512-NXjFqDHNGRTZ1EnA4zr20GFEt7qw/JvZ4ZV8/PzFyVc7dPoFprpoyE3bw7kmlKHhcQdBbF7YXCGB4q+HQUnqiQ==", + "version": "5.0.3", + "resolved": "https://registry.npmjs.org/@adonisjs/config/-/config-5.0.3.tgz", + "integrity": "sha512-dO7gkYxZsrsnR8n7d5KUpyi+Q5c6BnV2rmFDqEmEjz5AkOZLLzJJJbeHgMb+M27le7ifEUoa8MRu6RED8NMsJg==", "license": "MIT", "dependencies": { - "@poppinss/utils": "^6.7.3" + "@poppinss/utils": "^6.9.4" }, "engines": { "node": ">=18.16.0" } }, "node_modules/@adonisjs/core": { - "version": "6.17.2", - "resolved": "https://registry.npmjs.org/@adonisjs/core/-/core-6.17.2.tgz", - "integrity": 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"/> +</defs> +</svg> diff --git a/public/site.webmanifest b/public/site.webmanifest new file mode 100644 index 0000000..45dc8a2 --- /dev/null +++ b/public/site.webmanifest @@ -0,0 +1 @@ +{"name":"","short_name":"","icons":[{"src":"/android-chrome-192x192.png","sizes":"192x192","type":"image/png"},{"src":"/android-chrome-512x512.png","sizes":"512x512","type":"image/png"}],"theme_color":"#ffffff","background_color":"#ffffff","display":"standalone"} \ No newline at end of file diff --git a/resources/css/app.css b/resources/css/app.css index 7ae8714..0301a3a 100644 --- a/resources/css/app.css +++ b/resources/css/app.css @@ -1,7 +1,7 @@ /* @import url('https://fonts.googleapis.com/css2?family=Poppins:wght@400;500&display=swap'); */ /* @import url('https://fonts.googleapis.com/css?family=Roboto:400,400i,600,700'); */ -@import '_checkbox-radio-switch.css'; +/* @import '_checkbox-radio-switch.css'; */ @import '_progress.css'; @import '_scrollbars.css'; @import '_table.css'; diff --git a/resources/js/Components/CardBoxClient.vue b/resources/js/Components/CardBoxClient.vue index b89ed7a..cd9bf57 100644 --- a/resources/js/Components/CardBoxClient.vue +++ b/resources/js/Components/CardBoxClient.vue @@ -39,6 +39,10 @@ const props = defineProps({ type: String, default: null, }, + allowEmailContact: { + type: Boolean, + default: false, + } }); const pillType = computed(() => { @@ -81,9 +85,8 @@ const pillType = computed(() => { <h4 class="text-xl text-ellipsis"> {{ name }} </h4> - <p class="text-gray-500 dark:text-slate-400"> - <!-- {{ date }} @ {{ login }} --> - {{ email }} + <p class="text-gray-500 dark:text-slate-400"> + <div v-if="props.allowEmailContact"> {{ email }}</div> </p> </div> </BaseLevel> diff --git a/resources/js/Components/CardBoxModal.vue b/resources/js/Components/CardBoxModal.vue index 6e7f9aa..b0fdf01 100644 --- a/resources/js/Components/CardBoxModal.vue +++ b/resources/js/Components/CardBoxModal.vue @@ -61,10 +61,10 @@ const cancel = () => confirmCancel('cancel'); <CardBox v-show="value" :title="title" - class="shadow-lg max-h-modal w-11/12 md:w-3/5 lg:w-2/5 xl:w-4/12 z-50" + class="p-4 shadow-lg max-h-modal w-11/12 md:w-3/5 lg:w-2/5 xl:w-4/12 z-50" :header-icon="mdiClose" modal - @header-icon-click="cancel" + @header-icon-click="cancel" > <div class="space-y-3"> <h1 v-if="largeTitle" class="text-2xl"> diff --git a/resources/js/Components/CardBoxSimple.vue b/resources/js/Components/CardBoxSimple.vue new file mode 100644 index 0000000..ef6a624 --- /dev/null +++ b/resources/js/Components/CardBoxSimple.vue @@ -0,0 +1,75 @@ +<script setup lang="ts"> + +import { computed, useSlots } from 'vue'; + + +const props = defineProps({ + title: { + type: String, + default: null, + }, + icon: { + type: String, + default: null, + }, + showHeaderIcon: { + type: Boolean, + default: true, + }, + headerIcon: { + type: String, + default: null, + }, + rounded: { + type: String, + default: 'rounded-xl', + }, + hasFormData: Boolean, + empty: Boolean, + form: Boolean, + hoverable: Boolean, + modal: Boolean, +}); + +const emit = defineEmits(['header-icon-click', 'submit']); + +const is = computed(() => (props.form ? 'form' : 'div')); + +const slots = useSlots(); + +// const footer = computed(() => slots.footer && !!slots.footer()); + +const componentClass = computed(() => { + const base = [props.rounded, props.modal ? 'dark:bg-slate-900' : 'dark:bg-slate-900/70']; + + if (props.hoverable) { + base.push('hover:shadow-lg transition-shadow duration-500'); + } + + return base; +}); + + + +// const headerIconClick = () => { +// emit('header-icon-click'); +// }; + +// const submit = (e) => { +// emit('submit', e); +// }; +</script> + +<template> + <component :is="is" :class="componentClass" class="bg-white flex flex-col border border-gray-100 dark:border-slate-800 mb-4"> + + <div v-if="empty" class="text-center py-24 text-gray-500 dark:text-slate-400"> + <p>Nothing's here…</p> + </div> + + <div v-else class="flex-1" :class="[!hasFormData && 'p-6']"> + <slot /> + </div> + + </component> +</template> diff --git a/resources/js/Components/CardBoxWidget.vue b/resources/js/Components/CardBoxWidget.vue index 58b3e3c..fe10723 100644 --- a/resources/js/Components/CardBoxWidget.vue +++ b/resources/js/Components/CardBoxWidget.vue @@ -1,4 +1,4 @@ -<script setup> +<script lang="ts" setup> import { mdiCog } from '@mdi/js'; import CardBox from '@/Components/CardBox.vue'; import NumberDynamic from '@/Components/NumberDynamic.vue'; @@ -49,6 +49,9 @@ defineProps({ <PillTagTrend :trend="trend" :trend-type="trendType" small /> <BaseButton :icon="mdiCog" icon-w="w-4" icon-h="h-4" color="white" small /> </BaseLevel> + <BaseLevel v-else class="mb-3" mobile> + <BaseIcon v-if="icon" :path="icon" size="48" w="w-4" h="h-4" :class="color" /> + </BaseLevel> <BaseLevel mobile> <div> <h3 class="text-lg leading-tight text-gray-500 dark:text-slate-400"> diff --git a/resources/js/Components/FileUpload.vue b/resources/js/Components/FileUpload.vue index d1a2979..c5ee2ce 100644 --- a/resources/js/Components/FileUpload.vue +++ b/resources/js/Components/FileUpload.vue @@ -17,6 +17,15 @@ <p class="text-lg text-blue-700">Drop files to upload</p> </div> + <!-- Loading Spinner when processing big files --> + <div v-if="isLoading" class="absolute inset-0 z-60 flex items-center justify-center bg-gray-500 bg-opacity-50"> + <svg class="animate-spin h-12 w-12 text-white" xmlns="http://www.w3.org/2000/svg" fill="none" + viewBox="0 0 24 24"> + <circle class="opacity-25" cx="12" cy="12" r="10" stroke="currentColor" stroke-width="4"></circle> + <path class="opacity-75" fill="currentColor" d="M12 2a10 10 0 0110 10h-4a6 6 0 00-6-6V2z"></path> + </svg> + </div> + <!-- scroll area --> <div class="h-full p-8 w-full h-full flex flex-col"> <header class="flex items-center justify-center w-full"> @@ -32,9 +41,9 @@ <p class="mb-2 text-sm text-gray-500 dark:text-gray-400"> <span class="font-semibold">Click to upload</span> or drag and drop </p> - <!-- <p class="text-xs text-gray-500 dark:text-gray-400">SVG, PNG, JPG or GIF (MAX. 800x400px)</p> --> </div> - <input id="dropzone-file" type="file" class="hidden" @change="onChangeFile" multiple="true" /> + <input id="dropzone-file" type="file" class="hidden" @click="showSpinner" @change="onChangeFile" + @cancel="cancelSpinner" multiple="true" /> </label> </header> @@ -182,7 +191,7 @@ <!-- sticky footer --> <footer class="flex justify-end px-8 pb-8 pt-4"> - <button id="cancel" + <button v-if="showClearButton" id="cancel" class="ml-3 rounded-sm px-3 py-1 hover:bg-gray-300 focus:shadow-outline focus:outline-none" @click="clearAllFiles"> Clear @@ -241,6 +250,8 @@ class FileUploadComponent extends Vue { @Ref('overlay') overlay: HTMLDivElement; + + public isLoading: boolean = false; private counter: number = 0; // @Prop() files: Array<TestFile>; @@ -257,6 +268,12 @@ class FileUploadComponent extends Vue { }) filesToDelete: Array<TethysFile>; + @Prop({ + type: Boolean, + default: true, + }) + showClearButton: boolean; + // // deletetFiles: Array<TethysFile> = []; get deletetFiles(): Array<TethysFile> { return this.filesToDelete; @@ -264,7 +281,7 @@ class FileUploadComponent extends Vue { set deletetFiles(values: Array<TethysFile>) { // this.modelValue = value; this.filesToDelete.length = 0; - this.filesToDelete.push(...values); + this.filesToDelete.push(...values); } get items(): Array<TethysFile | File> { @@ -342,10 +359,10 @@ class FileUploadComponent extends Vue { } // reset counter and append file to gallery when file is dropped - public dropHandler(event: DragEvent): void { event.preventDefault(); const dataTransfer = event.dataTransfer; + // let bigFileFound = false; if (dataTransfer) { for (const file of event.dataTransfer?.files) { // let fileName = String(file.name.replace(/\.[^/.]+$/, '')); @@ -353,28 +370,73 @@ class FileUploadComponent extends Vue { // if (file.type.match('image.*')) { // this.generateURL(file); // } + // if (file.size > 62914560) { // 60 MB in bytes + // bigFileFound = true; + // } this._addFile(file); } this.overlay.classList.remove('draggedover'); this.counter = 0; } + // if (bigFileFound) { + // this.isLoading = true; + // // Assume file processing delay; adjust timeout as needed or rely on async processing completion. + // setTimeout(() => { + // this.isLoading = false; + // }, 1500); + // } + } + + public showSpinner() { + // event.preventDefault(); + this.isLoading = true; + } + + public cancelSpinner() { + // const target = event.target as HTMLInputElement; + // // If no files were selected, remove spinner + // if (!target.files || target.files.length === 0) { + // this.isLoading = false; + // } + this.isLoading = false; } public onChangeFile(event: Event) { event.preventDefault(); + let target = event.target as HTMLInputElement; // let uploadedFile = event.target.files[0]; // let fileName = String(event.target.files[0].name.replace(/\.[^/.]+$/, '')); - for (const file of event.target.files) { - // let fileName = String(event.target.files[0].name.replace(/\.[^/.]+$/, '')); - // file.label = fileName; - // if (file.type.match('image.*')) { - // this.generateURL(file); - // } - this._addFile(file); + if (target && target.files) { + for (const file of event.target.files) { + // let fileName = String(event.target.files[0].name.replace(/\.[^/.]+$/, '')); + // file.label = fileName; + // if (file.type.match('image.*')) { + // this.generateURL(file); + // } + // Immediately set spinner if any file is large (over 100 MB) + // for (const file of target.files) { + // if (file.size > 62914560) { // 100 MB + // bigFileFound = true; + // break; + // } + // } + // if (bigFileFound) { + // this.isLoading = true; + // } + this._addFile(file); + + } } + // if (bigFileFound) { + // this.isLoading = true; + // setTimeout(() => { + // this.isLoading = false; + // }, 1500); + // } // this.overlay.classList.remove('draggedover'); this.counter = 0; + this.isLoading = false; } get errors(): IDictionary { @@ -396,7 +458,9 @@ class FileUploadComponent extends Vue { public clearAllFiles(event: Event) { event.preventDefault(); - this.items.splice(0); + if (this.showClearButton == true) { + this.items.splice(0); + } } public removeFile(key: number) { @@ -445,7 +509,7 @@ class FileUploadComponent extends Vue { let localUrl: string = ''; if (file instanceof File) { localUrl = URL.createObjectURL(file as Blob); - } + } // else if (file.fileData) { // // const blob = new Blob([file.fileData]); // // localUrl = URL.createObjectURL(blob); @@ -465,17 +529,6 @@ class FileUploadComponent extends Vue { return localUrl; } - // private async downloadFile(id: number): Promise<string> { - // const response = await axios.get<Blob>(`/api/download/${id}`, { - // responseType: 'blob', - // }); - // const url = URL.createObjectURL(response.data); - // setTimeout(() => { - // URL.revokeObjectURL(url); - // }, 1000); - // return url; - // } - public getFileSize(file: File) { if (file.size > 1024) { if (file.size > 1048576) { @@ -488,17 +541,6 @@ class FileUploadComponent extends Vue { } } - // private _addFile(file) { - // // const isImage = file.type.match('image.*'); - // // const objectURL = URL.createObjectURL(file); - - // // this.files[objectURL] = file; - // // let test: TethysFile = { upload: file, label: "dfdsfs", sorting: 0 }; - // // file.sorting = this.files.length; - // file.sort_order = (this.items.length + 1), - // this.files.push(file); - // } - private _addFile(file: File) { // const reader = new FileReader(); // reader.onload = (event) => { @@ -530,14 +572,11 @@ class FileUploadComponent extends Vue { // this.items.push(test); this.items[this.items.length] = test; } else { + file.sort_order = this.items.length + 1; this.items.push(file); } } - // use to check if a file is being dragged - // private _hasFiles({ types = [] as Array<string> }) { - // return types.indexOf('Files') > -1; - // } private _hasFiles(dataTransfer: DataTransfer | null): boolean { return dataTransfer ? dataTransfer.items.length > 0 : false; } diff --git a/resources/js/Components/FooterBar.vue b/resources/js/Components/FooterBar.vue index edf8ecf..4408cf0 100644 --- a/resources/js/Components/FooterBar.vue +++ b/resources/js/Components/FooterBar.vue @@ -15,9 +15,10 @@ const year = computed(() => new Date().getFullYear()); <!-- Get more with <a href="https://tailwind-vue.justboil.me/" target="_blank" class="text-blue-600">Premium version</a> --> </div> - <div class="md:py-3"> + <div class="md:py-1"> <a href="https://www.tethys.at" target="_blank"> - <JustboilLogo class="w-auto h-8 md:h-6" /> + <!-- <JustboilLogo class="w-auto h-8 md:h-6" /> --> + <JustboilLogo class="w-auto h-12 md:h-10 dark:invert" /> </a> </div> </BaseLevel> diff --git a/resources/js/Components/FormCheckRadio.vue b/resources/js/Components/FormCheckRadio.vue index 1f991e7..5d22212 100644 --- a/resources/js/Components/FormCheckRadio.vue +++ b/resources/js/Components/FormCheckRadio.vue @@ -1,43 +1,59 @@ -<script setup> +<script setup lang="ts"> import { computed } from 'vue'; -const props = defineProps({ - name: { - type: String, - required: true, - }, - type: { - type: String, - default: 'checkbox', - validator: (value) => ['checkbox', 'radio', 'switch'].includes(value), - }, - label: { - type: String, - default: null, - }, - modelValue: { - type: [Array, String, Number, Boolean], - default: null, - }, - inputValue: { - type: [String, Number, Boolean], - required: true, - }, -}); -const emit = defineEmits(['update:modelValue']); +interface Props { + name: string; + type?: 'checkbox' | 'radio' | 'switch'; + label?: string | null; + modelValue: Array<any> | string | number | boolean | null; + inputValue: string | number | boolean; +} + +const props = defineProps<Props>(); + +const emit = defineEmits<{ (e: 'update:modelValue', value: Props['modelValue']): void }>(); + const computedValue = computed({ get: () => props.modelValue, set: (value) => { - emit('update:modelValue', value); + emit('update:modelValue', props.type === 'radio' ? [value] : value); }, }); + const inputType = computed(() => (props.type === 'radio' ? 'radio' : 'checkbox')); + +// Define isChecked for radio inputs: it's true when the current modelValue equals the inputValue +const isChecked = computed(() => { + if (Array.isArray(computedValue.value) && computedValue.value.length > 0) { + return props.type === 'radio' + ? computedValue.value[0] === props.inputValue + : computedValue.value.includes(props.inputValue); + } + return computedValue.value === props.inputValue; +}); </script> <template> - <label :class="type" class="mr-6 mb-3 last:mr-0"> - <input v-model="computedValue" :type="inputType" :name="name" :value="inputValue" /> - <span class="check" /> - <span class="pl-2">{{ label }}</span> + <label v-if="type === 'radio'" :class="[type]" + class="mr-6 mb-3 last:mr-0 inline-flex items-center cursor-pointer relative"> + <input v-model="computedValue" :type="inputType" :name="name" :value="inputValue" + class="absolute left-0 opacity-0 -z-1 focus:outline-none focus:ring-0" + :checked="isChecked" /> + <span class="check border transition-colors duration-200 dark:bg-slate-800 block w-5 h-5 rounded-full" :class="{ + 'border-gray-700': !isChecked, + 'bg-radio-checked bg-no-repeat bg-center bg-lime-600 border-lime-600 border-4': isChecked + }" /> + <span class="pl-2 control-label">{{ label }}</span> + </label> + + <label v-else-if="type === 'checkbox'" :class="[type]" + class="mr-6 mb-3 last:mr-0 inline-flex items-center cursor-pointer relative"> + <input v-model="computedValue" :type="inputType" :name="name" :value="inputValue" + class="absolute left-0 opacity-0 -z-1 focus:outline-none focus:ring-0" /> + <span class="check border transition-colors duration-200 dark:bg-slate-800 block w-5 h-5 rounded" :class="{ + 'border-gray-700': !isChecked, + 'bg-checkbox-checked bg-no-repeat bg-center bg-lime-600 border-lime-600 border-4': isChecked + }" /> + <span class="pl-2 control-label">{{ label }}</span> </label> </template> diff --git a/resources/js/Components/FormCheckRadioGroup.vue b/resources/js/Components/FormCheckRadioGroup.vue index 34f9f87..1315fec 100644 --- a/resources/js/Components/FormCheckRadioGroup.vue +++ b/resources/js/Components/FormCheckRadioGroup.vue @@ -1,9 +1,9 @@ <script setup lang="ts"> -import { computed, ref } from 'vue'; +import { computed, ref, PropType } from 'vue'; import FormCheckRadio from '@/Components/FormCheckRadio.vue'; -import BaseButton from '@/Components/BaseButton.vue'; -import FormControl from '@/Components/FormControl.vue'; -import { mdiPlusCircle } from '@mdi/js'; +// import BaseButton from '@/Components/BaseButton.vue'; +// import FormControl from '@/Components/FormControl.vue'; + const props = defineProps({ options: { type: Object, @@ -23,7 +23,7 @@ const props = defineProps({ required: true, }, type: { - type: String, + type: String as PropType<'checkbox' | 'radio' | 'switch'>, default: 'checkbox', validator: (value: string) => ['checkbox', 'radio', 'switch'].includes(value), }, @@ -47,7 +47,7 @@ const computedValue = computed({ if (props.modelValue.every((item) => typeof item === 'number')) { return props.modelValue; } else if (props.modelValue.every((item) => hasIdAttribute(item))) { - const ids = props.modelValue.map((obj) => obj.id.toString()); + const ids = props.modelValue.map((obj) => obj.id); return ids; } return props.modelValue; @@ -78,11 +78,11 @@ const addOption = () => { const inputElClass = computed(() => { const base = [ - 'px-3 py-2 max-w-full focus:ring focus:outline-none border-gray-700 rounded w-full', + 'px-3 py-2 max-w-full border-gray-700 rounded w-full', 'dark:placeholder-gray-400', 'h-12', 'border', - 'bg-transparent' + 'bg-transparent' // props.isReadOnly ? 'bg-gray-50 dark:bg-slate-600' : 'bg-white dark:bg-slate-800', ]; // if (props.icon) { @@ -108,7 +108,9 @@ const inputElClass = computed(() => { d="M12 2C6.48 2 2 6.48 2 12s4.48 10 10 10 10-4.48 10-10S17.52 2 12 2zm1 17h-2v-6H5v-2h6V5h2v6h6v2h-6v6z" /> </svg> </div> - <FormCheckRadio v-for="(value, key) in options" :key="key" v-model="computedValue" :type="type" :name="name" - :input-value="key" :label="value" :class="componentClass" /> + <!-- <FormCheckRadio v-for="(value, key) in options" :key="key" v-model="computedValue" :type="type" + :name="name" :input-value="key" :label="value" :class="componentClass" /> --> + <FormCheckRadio v-for="(value, key) in options" :key="key" v-model="computedValue" :type="type" + :name="name" :input-value="isNaN(Number(key)) ? key : Number(key)" :label="value" :class="componentClass" /> </div> </template> diff --git a/resources/js/Components/FormControl.vue b/resources/js/Components/FormControl.vue index c768b1d..f66a2b3 100644 --- a/resources/js/Components/FormControl.vue +++ b/resources/js/Components/FormControl.vue @@ -67,15 +67,28 @@ const computedValue = computed({ emit('update:modelValue', value); }, }); + +// focus:ring focus:outline-none border-gray-700 const inputElClass = computed(() => { const base = [ - 'px-3 py-2 max-w-full focus:ring focus:outline-none border-gray-700 rounded w-full', + 'px-3 py-2 max-w-full rounded w-full', 'dark:placeholder-gray-400', props.extraHigh ? 'h-80' : (computedType.value === 'textarea' ? 'h-44' : 'h-12'), props.borderless ? 'border-0' : 'border', - // props.transparent && !props.isReadOnly ? 'bg-transparent' : 'bg-white dark:bg-slate-800', - props.isReadOnly ? 'bg-gray-50 dark:bg-slate-600' : 'bg-white dark:bg-slate-800', + // // props.transparent && !props.isReadOnly ? 'bg-transparent' : 'bg-white dark:bg-slate-800', + // props.isReadOnly ? 'bg-gray-50 dark:bg-slate-600' : 'bg-white dark:bg-slate-800', ]; + + // Apply styles based on read-only state. + if (props.isReadOnly) { + // Read-only: no focus ring, grayed-out text and border, and disabled cursor. + base.push('bg-gray-50', 'dark:bg-slate-600', 'border', 'border-gray-300', 'dark:border-slate-600', 'text-gray-500', 'cursor-not-allowed', 'focus:outline-none' ,'focus:ring-0', 'focus:border-gray-300'); + } else { + // Actionable field: focus ring, white/dark background, and darker border. + base.push('bg-white dark:bg-slate-800', 'focus:ring focus:outline-none', 'border', 'border-gray-700'); + } + + if (props.icon) { base.push('pl-10', 'pr-10'); } diff --git a/resources/js/Components/Icons/IconSvg.vue b/resources/js/Components/Icons/IconSvg.vue new file mode 100644 index 0000000..b83e742 --- /dev/null +++ b/resources/js/Components/Icons/IconSvg.vue @@ -0,0 +1,74 @@ +<script setup lang="ts"> +import { computed } from 'vue'; +import { mdiLicense } from '@mdi/js'; + +const props = defineProps({ + path: { + type: String, + required: true + }, + size: { + type: Number, + default: 24 + }, + viewBox: { + type: String, + default: '0 0 24 24' + }, + color: { + type: String, + default: 'currentColor' + }, + className: { + type: String, + default: '' + } +}); + +// Define all the SVG paths we need +const svgPaths = { + // Document/File icons + document: 'M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z', + documentPlus: 'M9 13h6m-3-3v6m5 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z', + + // Communication icons + email: 'M2.003 5.884L10 9.882l7.997-3.998A2 2 0 0016 4H4a2 2 0 00-1.997 1.884z M18 8.118l-8 4-8-4V14a2 2 0 002 2h12a2 2 0 002-2V8.118z', + + // Identity/User icons + idCard: '10 2a1 1 0 00-1 1v1a1 1 0 002 0V3a1 1 0 00-1-1zM4 4h3a3 3 0 006 0h3a2 2 0 012 2v9a2 2 0 01-2 2H4a2 2 0 01-2-2V6a2 2 0 012-2zm2.5 7a1.5 1.5 0 100-3 1.5 1.5 0 000 3zm2.45 4a2.5 2.5 0 10-4.9 0h4.9zM12 9a1 1 0 100 2h3a1 1 0 100-2h-3zm-1 4a1 1 0 011-1h2a1 1 0 110 2h-2a1 1 0 01-1-1z', + + // Language/Translation icons + // language: 'M7 2a1 1 0 011 1v1h3a1 1 0 110 2H9.578a18.87 18.87 0 01-1.724 4.78c.29.354.596.696.914 1.026a1 1 0 11-1.44 1.389c-.188-.196-.373-.396-.554-.6a19.098 19.098 0 01-3.107 3.567 1 1 0 01-1.334-1.49 17.087 17.087 0 003.13-3.733 18.992 18.992 0 01-1.487-2.494 1 1 0 111.79-.89c.234.47.489.928.764 1.372.417-.934.752-1.913.997-2.927H3a1 1 0 110-2h3V3a1 1 0 011-1zm6 6a1 1 0 01.894.553l2.991 5.982a.869.869 0 01.02.037l.99 1.98a1 1 0 11-1.79.895L15.383 16h-4.764l-.724 1.447a1 1 0 11-1.788-.894l.99-1.98.019-.038 2.99-5.982A1 1 0 0113 8zm-1.382 6h2.764L13 11.236 11.618 14z', + language: 'M12 2a10 10 0 1 0 0 20a10 10 0 1 0 0-20zm0 0c2.5 0 4.5 4.5 4.5 10s-2 10-4.5 10-4.5-4.5-4.5-10 2-10 4.5-10zm0 0a10 10 0 0 1 0 20a10 10 0 0 1 0-20z', + // License/Legal icons + // license: 'M10 2a1 1 0 00-1 1v1.323l-3.954 1.582A1 1 0 004 6.32V16a1 1 0 001.555.832l3-1.2a1 1 0 01.8 0l3 1.2a1 1 0 001.555-.832V6.32a1 1 0 00-1.046-.894L9 4.877V3a1 1 0 00-1-1zm0 14.5a.5.5 0 01-.5-.5v-4a.5.5 0 011 0v4a.5.5 0 01-.5.5zm1.5-10.5a.5.5 0 11-1 0 .5.5 0 011 0z', + license: mdiLicense, + + // Building/Organization icons + building: 'M4 4a2 2 0 012-2h8a2 2 0 012 2v12a1 1 0 110 2h-3a1 1 0 01-1-1v-2a1 1 0 00-1-1H9a1 1 0 00-1 1v2a1 1 0 01-1 1H4a1 1 0 110-2V4zm3 1h2v2H7V5zm2 4H7v2h2V9zm2-4h2v2h-2V5zm2 4h-2v2h2V9z', + + // Book/Publication icons + book: 'M9 4.804A7.968 7.968 0 005.5 4c-1.255 0-2.443.29-3.5.804v10A7.969 7.969 0 015.5 14c1.669 0 3.218.51 4.5 1.385A7.962 7.962 0 0114.5 14c1.255 0 2.443.29 3.5.804v-10A7.968 7.968 0 0014.5 4c-1.255 0-2.443.29-3.5.804V12a1 1 0 11-2 0V4.804z', + + // Download icon + download: 'M4 16v1a3 3 0 003 3h10a3 3 0 003-3v-1m-4-4l-4 4m0 0l-4-4m4 4V4' +}; + +const pathData = computed(() => { + return svgPaths[props.path] || props.path; +}); + +const sizeStyle = computed(() => { + return { + width: `${props.size}px`, + height: `${props.size}px` + }; +}); +</script> + +<template> + <svg :style="sizeStyle" :class="className" :viewBox="viewBox" xmlns="http://www.w3.org/2000/svg" fill="none" + :stroke="color" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"> + <path :d="pathData" /> + </svg> +</template> \ No newline at end of file diff --git a/resources/js/Components/JustboilLogo.vue b/resources/js/Components/JustboilLogo.vue index 21e4193..d295d63 100644 --- a/resources/js/Components/JustboilLogo.vue +++ b/resources/js/Components/JustboilLogo.vue @@ -1,145 +1,11 @@ <template> - <svg version="1.1" id="Layer_1" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" x="0px" - y="0px" viewBox="0 0 626.4 224.7" style="enable-background:new 0 0 626.4 224.7;" xml:space="preserve" fill="currentColor"> - <g> - <g> - <path class="st0" - d="M215.3,69.1l-4.4,19.2h-47.1l-4.2,18h43.7l-4.5,19.2h-43.6l-5.9,25.4h47L192,170h-73.1l23.3-100.9H215.3z" /> - <path class="st0" 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+</defs> +</svg> </template> diff --git a/resources/js/Components/Map/MapComponentView.vue b/resources/js/Components/Map/MapComponentView.vue new file mode 100644 index 0000000..0dfd0aa --- /dev/null +++ b/resources/js/Components/Map/MapComponentView.vue @@ -0,0 +1,124 @@ +<script setup> +import { onMounted, ref, watch } from 'vue'; +import L from 'leaflet'; +import 'leaflet/dist/leaflet.css'; + +const DEFAULT_BASE_LAYER_NAME = 'BaseLayer'; +const DEFAULT_BASE_LAYER_ATTRIBUTION = '© <a target="_blank" href="http://osm.org/copyright">OpenStreetMap</a> contributors'; + +const props = defineProps({ + coverage: { + type: Object, + required: true + }, + height: { + type: String, + default: '250px' + }, + mapId: { + type: String, + default: 'view-map' + } +}); + +const map = ref(null); +const mapContainer = ref(null); + +onMounted(() => { + initializeMap(); +}); + +watch(() => props.coverage, (newCoverage) => { + if (map.value && newCoverage) { + updateBounds(); + } +}, { deep: true }); + +const initializeMap = () => { + // Create the map with minimal controls + map.value = L.map(mapContainer.value, { + zoomControl: false, + attributionControl: false, + dragging: false, + scrollWheelZoom: false, + doubleClickZoom: false, + boxZoom: false, + tap: false, + keyboard: false, + touchZoom: false + }); + + // // Add a simple tile layer (OpenStreetMap) + let osmGgray = new L.TileLayer.WMS('https://ows.terrestris.de/osm-gray/service', { + format: 'image/png', + attribution: DEFAULT_BASE_LAYER_ATTRIBUTION, + layers: 'OSM-WMS', + }); + let layerOptions = { + label: DEFAULT_BASE_LAYER_NAME, + visible: true, + layer: osmGgray, + }; + layerOptions.layer.addTo(map.value); + + // Add a light-colored rectangle for the coverage area + updateBounds(); +}; + +const updateBounds = () => { + if (!props.coverage || !map.value) return; + + // Clear any existing layers except the base tile layer + map.value.eachLayer(layer => { + if (layer instanceof L.Rectangle) { + map.value.removeLayer(layer); + } + }); + + // Create bounds from the coverage coordinates + const bounds = L.latLngBounds( + [props.coverage.y_min, props.coverage.x_min], + [props.coverage.y_max, props.coverage.x_max] + ); + + // Add a rectangle with emerald styling + L.rectangle(bounds, { + color: '#10b981', // emerald-500 + weight: 2, + fillColor: '#d1fae5', // emerald-100 + fillOpacity: 0.5 + }).addTo(map.value); + + // Fit the map to the bounds with some padding + map.value.fitBounds(bounds, { + padding: [20, 20] + }); +}; +</script> + +<template> + <div class="map-container bg-emerald-50 dark:bg-emerald-900/30 + rounded-lg shadow-sm overflow-hidden"> + <div :id="mapId" ref="mapContainer" :style="{ height: height }" class="w-full"></div> + </div> +</template> + +<style scoped> +/* Ensure the Leaflet container has proper styling */ +:deep(.leaflet-container) { + background-color: #f0fdf4; + /* emerald-50 */ +} + +/* Dark mode adjustments */ +@media (prefers-color-scheme: dark) { + :deep(.leaflet-container) { + background-color: rgba(6, 78, 59, 0.3); + /* emerald-900/30 */ + } + + :deep(.leaflet-tile) { + filter: brightness(0.8) contrast(1.2) grayscale(0.3); + } +} +</style> \ No newline at end of file diff --git a/resources/js/Components/NavBar.vue b/resources/js/Components/NavBar.vue index dce1325..1df8ccb 100644 --- a/resources/js/Components/NavBar.vue +++ b/resources/js/Components/NavBar.vue @@ -21,12 +21,11 @@ import { mdiFormatListGroup, mdiFormatListNumbered, mdiLogout, - mdiGithub, mdiThemeLightDark, mdiViewDashboard, - mdiMapSearch, mdiInformationVariant, mdiGlasses, + mdiXml } from '@mdi/js'; import NavBarItem from '@/Components/NavBarItem.vue'; import NavBarItemLabel from '@/Components/NavBarItemLabel.vue'; @@ -100,7 +99,8 @@ const showAbout = async () => { <FirstrunWizard ref="about"></FirstrunWizard> <div class="flex lg:items-stretch" :class="containerMaxW"> <div class="flex-1 items-stretch flex h-14"> - <NavBarItem type="flex lg:hidden" @click.prevent="layoutStore.asideMobileToggle()" v-if="props.showBurger"> + <NavBarItem type="flex lg:hidden" @click.prevent="layoutStore.asideMobileToggle()" + v-if="props.showBurger"> <BaseIcon :path="layoutStore.isAsideMobileExpanded ? mdiBackburger : mdiForwardburger" size="24" /> </NavBarItem> <NavBarItem type="hidden lg:flex xl:hidden" @click.prevent="menuOpenLg" v-if="props.showBurger"> @@ -110,9 +110,9 @@ const showAbout = async () => { <NavBarItemLabel :icon="mdiViewDashboard" label="Dashboard" size="22" is-hover-label-only route-name="apps.dashboard" /> </NavBarItem> - <NavBarItem route-name="apps.map"> + <!-- <NavBarItem route-name="apps.map"> <NavBarItemLabel :icon="mdiMapSearch" label="Map" size="22" is-hover-label-only route-name="apps.map" /> - </NavBarItem> + </NavBarItem> --> <!-- <NavBarItem> <NavBarSearch /> </NavBarItem> --> @@ -169,13 +169,10 @@ const showAbout = async () => { </NavBarItem> <NavBarItem v-if="userHasRoles(['reviewer'])" :route-name="'reviewer.dataset.list'"> <NavBarItemLabel :icon="mdiGlasses" label="Reviewer Menu" /> - </NavBarItem> - <!-- <NavBarItem> - <NavBarItemLabel :icon="mdiEmail" label="Messages" /> - </NavBarItem> --> - <NavBarItem @click="showAbout"> + </NavBarItem> + <!-- <NavBarItem @click="showAbout"> <NavBarItemLabel :icon="mdiInformationVariant" label="About" /> - </NavBarItem> + </NavBarItem> --> <BaseDivider nav-bar /> <NavBarItem @click="logout"> <NavBarItemLabel :icon="mdiLogout" label="Log Out" /> @@ -186,12 +183,15 @@ const showAbout = async () => { <NavBarItem is-desktop-icon-only @click.prevent="toggleLightDark"> <NavBarItemLabel v-bind:icon="mdiThemeLightDark" label="Light/Dark" is-desktop-icon-only /> </NavBarItem> - <NavBarItem href="https://gitea.geosphere.at/geolba/tethys.backend" target="_blank" is-desktop-icon-only> + <!-- <NavBarItem href="" target="_blank" is-desktop-icon-only> <NavBarItemLabel v-bind:icon="mdiGithub" label="GitHub" is-desktop-icon-only /> + </NavBarItem> --> + <NavBarItem href="/oai" target="_blank" is-desktop-icon-only> + <NavBarItemLabel v-bind:icon="mdiXml" label="OAI Interface" is-desktop-icon-only /> </NavBarItem> - <NavBarItem is-desktop-icon-only @click="showAbout"> + <!-- <NavBarItem is-desktop-icon-only @click="showAbout"> <NavBarItemLabel v-bind:icon="mdiInformationVariant" label="About" is-desktop-icon-only /> - </NavBarItem> + </NavBarItem> --> <NavBarItem is-desktop-icon-only @click="logout"> <NavBarItemLabel v-bind:icon="mdiLogout" label="Log out" is-desktop-icon-only /> </NavBarItem> diff --git a/resources/js/Components/SearchAutocomplete.vue b/resources/js/Components/SearchAutocomplete.vue index 553c7b5..a3b3b09 100644 --- a/resources/js/Components/SearchAutocomplete.vue +++ b/resources/js/Components/SearchAutocomplete.vue @@ -28,7 +28,7 @@ autocomplete="off" @keydown.down="onArrowDown" @keydown.up="onArrowUp" - @keydown.enter="onEnter" + @keydown.enter.prevent="onEnter" /> <svg class="w-4 h-4 absolute left-2.5 top-3.5" diff --git a/resources/js/Components/SearchCategoryAutocomplete.vue b/resources/js/Components/SearchCategoryAutocomplete.vue index 3a73641..9441055 100644 --- a/resources/js/Components/SearchCategoryAutocomplete.vue +++ b/resources/js/Components/SearchCategoryAutocomplete.vue @@ -5,7 +5,7 @@ <div class="relative" data-te-dropdown-ref> <button id="states-button" data-dropdown-toggle="dropdown-states" class="whitespace-nowrap h-12 z-10 inline-flex items-center py-2.5 px-4 text-sm font-medium text-center text-gray-500 bg-gray-100 border border-gray-300 rounded-l-lg hover:bg-gray-200 focus:ring-4 focus:outline-none focus:ring-gray-100 dark:bg-gray-700 dark:hover:bg-gray-600 dark:focus:ring-gray-700 dark:text-white dark:border-gray-600" - type="button" @click.prevent="showStates"> + type="button" :disabled="isReadOnly" @click.prevent="showStates"> <!-- <svg aria-hidden="true" class="h-3 mr-2" viewBox="0 0 15 12" fill="none" xmlns="http://www.w3.org/2000/svg"> <rect x="0.5" width="14" height="12" rx="2" fill="white" /> <mask id="mask0_12694_49953" style="mask-type: alpha" maskUnits="userSpaceOnUse" x="0" y="0" width="15" height="12"> @@ -65,7 +65,7 @@ </svg> --> <!-- eng --> {{ language }} - <svg aria-hidden="true" class="w-4 h-4 ml-1" fill="currentColor" viewBox="0 0 20 20" + <svg aria-hidden="true" class="w-4 h-4 ml-1" fill="currentColor" viewBox="0 0 20 20" v-if="!isReadOnly" xmlns="http://www.w3.org/2000/svg"> <path fill-rule="evenodd" d="M5.293 7.293a1 1 0 011.414 0L10 10.586l3.293-3.293a1 1 0 111.414 1.414l-4 4a1 1 0 01-1.414 0l-4-4a1 1 0 010-1.414z" @@ -93,7 +93,7 @@ <!-- :class="inputElClass" --> <!-- class="block p-2.5 w-full z-20 text-sm text-gray-900 bg-gray-50 rounded-r-lg border-l-gray-50 border-l-2 border border-gray-300 focus:ring-blue-500 focus:border-blue-500 dark:bg-gray-700 dark:border-l-gray-700 dark:border-gray-600 dark:placeholder-gray-400 dark:text-white dark:focus:border-blue-500" --> <input v-model="computedValue" type="text" :name="props.name" autocomplete="off" :class="inputElClass" - placeholder="Search Keywords..." required @input="handleInput" /> + placeholder="Search Keywords..." required @input="handleInput" :readonly="isReadOnly" /> <!-- v-model="data.search" --> <svg class="w-4 h-4 absolute left-2.5 top-3.5" v-show="computedValue.length < 2" xmlns="http://www.w3.org/2000/svg" fill="none" viewBox="0 0 24 24" stroke="currentColor"> @@ -101,12 +101,12 @@ d="M21 21l-6-6m2-5a7 7 0 11-14 0 7 7 0 0114 0z" /> </svg> - <svg class="w-4 h-4 absolute left-2.5 top-3.5" v-show="computedValue.length >= 2" + <svg class="w-4 h-4 absolute left-2.5 top-3.5" v-show="computedValue.length >= 2 && !isReadOnly" xmlns="http://www.w3.org/2000/svg" fill="none" viewBox="0 0 24 24" stroke="currentColor" @click="() => { computedValue = ''; data.isOpen = false; } - "> + "> <path stroke-linecap="round" stroke-linejoin="round" d="M6 18L18 6M6 6l12 12" /> </svg> </div> @@ -166,6 +166,10 @@ let props = defineProps({ type: String, default: '', }, + isReadOnly: { + type: Boolean, + default: false, + }, required: Boolean, borderless: Boolean, transparent: Boolean, @@ -190,11 +194,18 @@ const inputElClass = computed(() => { 'dark:placeholder-gray-400 dark:text-white dark:focus:border-blue-500', 'h-12', props.borderless ? 'border-0' : 'border', - props.transparent ? 'bg-transparent' : 'bg-white dark:bg-slate-800', + props.transparent && 'bg-transparent', // props.isReadOnly ? 'bg-gray-50 dark:bg-slate-600' : 'bg-white dark:bg-slate-800', ]; // if (props.icon) { base.push('pl-10'); + if (props.isReadOnly) { + // Read-only: no focus ring, grayed-out text and border, and disabled cursor. + base.push('bg-gray-50', 'dark:bg-slate-600', 'border', 'border-gray-300', 'dark:border-slate-600', 'text-gray-500', 'cursor-not-allowed', 'focus:outline-none', 'focus:ring-0', 'focus:border-gray-300'); + } else { + // Actionable field: focus ring, white/dark background, and darker border. + base.push('bg-white dark:bg-slate-800', 'focus:ring focus:outline-none', 'border', 'border-gray-700'); + } // } return base; }); diff --git a/resources/js/Components/SectionTitleLineWithButton.vue b/resources/js/Components/SectionTitleLineWithButton.vue index ca6fa30..e243946 100644 --- a/resources/js/Components/SectionTitleLineWithButton.vue +++ b/resources/js/Components/SectionTitleLineWithButton.vue @@ -15,6 +15,10 @@ defineProps({ required: true, }, main: Boolean, + showCogButton: { + type: Boolean, + default: false, + } }); const hasSlot = computed(() => useSlots().default); @@ -30,6 +34,6 @@ const hasSlot = computed(() => useSlots().default); </h1> </div> <slot v-if="hasSlot" /> - <BaseButton v-else :icon="mdiCog" small /> + <BaseButton v-else-if="showCogButton" :icon="mdiCog" small /> </section> </template> diff --git a/resources/js/Components/SimplePasswordMeter/password-meter.vue b/resources/js/Components/SimplePasswordMeter/password-meter.vue index 310cd54..e2dffd1 100644 --- a/resources/js/Components/SimplePasswordMeter/password-meter.vue +++ b/resources/js/Components/SimplePasswordMeter/password-meter.vue @@ -6,10 +6,29 @@ import FormField from '@/Components/FormField.vue'; import FormControl from '@/Components/FormControl.vue'; // Define props -const props = defineProps<{ - modelValue: string; - errors: Partial<Record<"new_password" | "old_password" | "confirm_password", string>>; -}>(); +// const props = defineProps<{ +// modelValue: string, +// errors: Partial<Record<"new_password" | "old_password" | "confirm_password", string>>, +// showRequiredMessage: boolean, +// }>(); + +const props = defineProps({ + modelValue: { + type: String, + }, + errors: { + type: Object, + default: () => ({} as Partial<Record<"new_password" | "old_password" | "confirm_password", string>>), + }, + showRequiredMessage: { + type: Boolean, + default:true, + }, + fieldLabel: { + type: String, + default: 'New password', + } +}); const emit = defineEmits(['update:modelValue', 'score']); @@ -61,8 +80,8 @@ const passwordMetrics = computed<PasswordMetrics>(() => { <template> <!-- Password input Form --> - <FormField label="New password" help="Required. New password" :class="{'text-red-400': errors.new_password }"> - <FormControl v-model="localPassword" :icon="mdiFormTextboxPassword" name="new_password" type="password" required + <FormField :label="fieldLabel" :help="showRequiredMessage ? 'Required. New password' : ''" :class="{'text-red-400': errors.new_password }"> + <FormControl v-model="localPassword" :icon="mdiFormTextboxPassword" name="new_password" type="password" :required="showRequiredMessage" :error="errors.new_password"> <!-- Secure Icon --> <template #right> @@ -84,10 +103,10 @@ const passwordMetrics = computed<PasswordMetrics>(() => { <div class="text-gray-700 text-sm"> {{ passwordMetrics.score }} / 6 points max </div> - </FormField> +</FormField> <!-- Password Strength Bar --> - <div class="po-password-strength-bar w-full h-2 rounded transition-all duration-200 mb-4" + <div v-if="passwordMetrics.score > 0"class="po-password-strength-bar w-full h-2 rounded transition-all duration-200 mb-4" :class="passwordMetrics.scoreLabel" :style="{ width: `${(passwordMetrics.score / 6) * 100}%` }" role="progressbar" :aria-valuenow="passwordMetrics.score" aria-valuemin="0" aria-valuemax="6" :aria-label="`Password strength: ${passwordMetrics.scoreLabel || 'unknown'}`"> diff --git a/resources/js/Components/TableKeywords.vue b/resources/js/Components/TableKeywords.vue index 835dd51..fbe979c 100644 --- a/resources/js/Components/TableKeywords.vue +++ b/resources/js/Components/TableKeywords.vue @@ -12,6 +12,7 @@ import { Subject } from '@/Dataset'; // import FormField from '@/Components/FormField.vue'; import FormControl from '@/Components/FormControl.vue'; import SearchCategoryAutocomplete from '@/Components/SearchCategoryAutocomplete.vue'; +import { mdiRefresh } from '@mdi/js'; const props = defineProps({ checkable: Boolean, @@ -27,6 +28,22 @@ const props = defineProps({ type: Object, default: () => ({}), }, + subjectsToDelete: { + type: Array<Subject>, + default: [], + } +}); + +const emit = defineEmits(['update:subjectsToDelete']); + +// Create a computed property for subjectsToDelete with getter and setter +const deletetSubjects = computed({ + get: () => props.subjectsToDelete, + set: (values: Array<Subject>) => { + props.subjectsToDelete.length = 0; + props.subjectsToDelete.push(...values); + emit('update:subjectsToDelete', values); + } }); const styleService = StyleService(); @@ -58,21 +75,45 @@ const pagesList = computed(() => { }); const removeItem = (key: number) => { + // items.value.splice(key, 1); + const item = items.value[key]; + + // If the item has an ID, add it to the delete list + if (item.id) { + addToDeleteList(item); + } + + // Remove from the visible list items.value.splice(key, 1); }; +// Helper function to add a subject to the delete list +const addToDeleteList = (subject: Subject) => { + if (subject.id) { + const newList = [...props.subjectsToDelete, subject]; + deletetSubjects.value = newList; + } +}; + + +// Helper function to reactivate a subject (remove from delete list) +const reactivateSubject = (index: number) => { + const newList = [...props.subjectsToDelete]; + const removedSubject = newList.splice(index, 1)[0]; + deletetSubjects.value = newList; + + // Add the subject back to the keywords list if it's not already there + if (removedSubject && !props.keywords.some(k => k.id === removedSubject.id)) { + props.keywords.push(removedSubject); + } +}; + +const isKeywordReadOnly = (item: Subject) => { + return (item.dataset_count ?? 0) > 1 || item.type !== 'uncontrolled'; +}; </script> <template> - <!-- <CardBoxModal v-model="isModalActive" title="Sample modal"> - <p>Lorem ipsum dolor sit amet <b>adipiscing elit</b></p> - <p>This is sample modal</p> - </CardBoxModal> - - <CardBoxModal v-model="isModalDangerActive" large-title="Please confirm" button="danger" has-cancel> - <p>Lorem ipsum dolor sit amet <b>adipiscing elit</b></p> - <p>This is sample modal</p> - </CardBoxModal> --> <!-- <div v-if="checkedRows.length" class="p-3 bg-gray-100/50 dark:bg-slate-800"> <span v-for="checkedRow in checkedRows" :key="checkedRow.id" @@ -87,17 +128,34 @@ const removeItem = (key: number) => { <!-- <th v-if="checkable" /> --> <!-- <th class="hidden lg:table-cell"></th> --> <th scope="col">Type</th> - <th scope="col">Value</th> + <th scope="col" class="relative"> + Value + <div class="inline-block relative ml-1 group"> + <button + class="w-4 h-4 rounded-full bg-gray-200 text-gray-600 text-xs flex items-center justify-center focus:outline-none hover:bg-gray-300"> + i + </button> + <div + class="absolute left-0 top-full mt-1 w-64 bg-white shadow-lg rounded-md p-3 text-xs text-left z-50 transform scale-0 origin-top-left transition-transform duration-100 group-hover:scale-100"> + <p class="text-gray-700"> + Keywords are only editable if they are used by a single dataset (Usage Count = 1)". + </p> + <div class="absolute -top-1 left-1 w-2 h-2 bg-white transform rotate-45"></div> + </div> + </div> + </th> <th scope="col">Language</th> - + <th scope="col">Usage Count</th> <th scope="col" /> </tr> </thead> <tbody> <tr v-for="(item, index) in itemsPaginated" :key="index"> - + <td data-label="Type" scope="row"> - <FormControl required v-model="item.type" @update:modelValue="() => {item.external_key = undefined; item.value= '';}" :type="'select'" placeholder="[Enter Language]" :options="props.subjectTypes"> + <FormControl required v-model="item.type" + @update:modelValue="() => { item.value = ''; }" :type="'select'" + placeholder="[Enter Language]" :options="props.subjectTypes"> <div class="text-red-400 text-sm" v-if="errors[`subjects.${index}.type`]"> {{ errors[`subjects.${index}.type`].join(', ') }} </div> @@ -105,22 +163,19 @@ const removeItem = (key: number) => { </td> <td data-label="Value" scope="row"> - <SearchCategoryAutocomplete - v-if="item.type !== 'uncontrolled'" - v-model="item.value" - @subject=" - (result) => { - item.language = result.language; - item.external_key = result.uri; - } - " - > + <SearchCategoryAutocomplete v-if="item.type !== 'uncontrolled'" v-model="item.value" @subject=" + (result) => { + item.language = result.language; + item.external_key = result.uri; + } + " :is-read-only="item.dataset_count > 1"> <div class="text-red-400 text-sm" v-if="errors[`subjects.${index}.value`]"> {{ errors[`subjects.${index}.value`].join(', ') }} </div> </SearchCategoryAutocomplete> - <FormControl v-else required v-model="item.value" type="text" placeholder="[enter keyword value]" :borderless="true"> + <FormControl v-else required v-model="item.value" type="text" placeholder="[enter keyword value]" + :borderless="true" :is-read-only="item.dataset_count > 1"> <div class="text-red-400 text-sm" v-if="errors[`subjects.${index}.value`]"> {{ errors[`subjects.${index}.value`].join(', ') }} </div> @@ -128,23 +183,24 @@ const removeItem = (key: number) => { </td> <td data-label="Language" scope="row"> - <FormControl - required - v-model="item.language" - :type="'select'" - placeholder="[Enter Lang]" - :options="{ de: 'de', en: 'en' }" - :is-read-only="item.type != 'uncontrolled'" - > + <FormControl required v-model="item.language" :type="'select'" placeholder="[Enter Lang]" + :options="{ de: 'de', en: 'en' }" :is-read-only="isKeywordReadOnly(item)"> <div class="text-red-400 text-sm" v-if="errors[`subjects.${index}.language`]"> {{ errors[`subjects.${index}.language`].join(', ') }} </div> </FormControl> </td> + + <td data-label="Usage Count" scope="row"> + <div class="text-center"> + {{ item.dataset_count || 1 }} + </div> + </td> + <td class="before:hidden lg:w-1 whitespace-nowrap" scope="row"> <BaseButtons type="justify-start lg:justify-end" no-wrap> <!-- <BaseButton color="info" :icon="mdiEye" small @click="isModalActive = true" /> --> - <BaseButton v-if="index > 2" color="danger" :icon="mdiTrashCan" small @click.prevent="removeItem(index)" /> + <BaseButton color="danger" :icon="mdiTrashCan" small @click.prevent="removeItem(index)" /> </BaseButtons> </td> </tr> @@ -155,15 +211,8 @@ const removeItem = (key: number) => { <div class="p-3 lg:px-6 border-t border-gray-100 dark:border-slate-800"> <BaseLevel> <BaseButtons> - <BaseButton - v-for="page in pagesList" - :key="page" - :active="page === currentPage" - :label="page + 1" - small - :outline="styleService.darkMode" - @click="currentPage = page" - /> + <BaseButton v-for="page in pagesList" :key="page" :active="page === currentPage" :label="page + 1" small + :outline="styleService.darkMode" @click="currentPage = page" /> </BaseButtons> <small>Page {{ currentPageHuman }} of {{ numPages }}</small> </BaseLevel> @@ -172,6 +221,47 @@ const removeItem = (key: number) => { <div class="text-red-400 text-sm" v-if="errors.subjects && Array.isArray(errors.subjects)"> {{ errors.subjects.join(', ') }} </div> + + <!-- Subjects to delete section --> + <div v-if="deletetSubjects.length > 0" class="mt-8"> + <h1 class="pt-8 pb-3 font-semibold sm:text-lg text-gray-900">Keywords To Delete</h1> + <ul id="deleteSubjects" tag="ul" class="flex flex-1 flex-wrap -m-1"> + <li v-for="(element, index) in deletetSubjects" :key="index" + class="block p-1 w-1/2 sm:w-1/3 md:w-1/4 lg:w-1/6 xl:w-1/8 h-32"> + <article tabindex="0" + class="bg-red-100 group w-full h-full rounded-md cursor-pointer relative shadow-sm overflow-hidden"> + <section + class="flex flex-col rounded-md text-xs break-words w-full h-full z-20 absolute top-0 py-2 px-3"> + <h1 class="flex-1 text-gray-700 group-hover:text-blue-800 font-medium text-sm mb-1">{{ + element.value }}</h1> + <div class="flex items-center justify-between mt-auto"> + <div class="flex flex-col"> + <p class="p-1 size text-xs text-gray-700"> + <span class="font-semibold">Type:</span> {{ element.type }} + </p> + <p class="p-1 size text-xs text-gray-700" v-if="element.dataset_count"> + <span class="font-semibold">Used by:</span> + <span + class="inline-flex items-center justify-center bg-gray-200 text-gray-800 rounded-full w-5 h-5 text-xs"> + {{ element.dataset_count }} + </span> datasets + </p> + </div> + <button + class="delete ml-auto focus:outline-none hover:bg-gray-300 p-1 rounded-md text-gray-800" + @click.prevent="reactivateSubject(index)"> + <svg viewBox="0 0 24 24" class="w-5 h-5"> + <path fill="currentColor" :d="mdiRefresh"></path> + </svg> + </button> + </div> + </section> + </article> + </li> + </ul> + </div> + + </template> <style scoped> diff --git a/resources/js/Pages/Admin/Mimetype/Create.vue b/resources/js/Pages/Admin/Mimetype/Create.vue index 86592c2..7480ece 100644 --- a/resources/js/Pages/Admin/Mimetype/Create.vue +++ b/resources/js/Pages/Admin/Mimetype/Create.vue @@ -1,7 +1,8 @@ <script lang="ts" setup> import { ref, reactive } from 'vue'; -import { Head, useForm } from '@inertiajs/vue3'; -import { mdiAccountKey, mdiArrowLeftBoldOutline, mdiTrashCan, mdiImageText, mdiPlus } from '@mdi/js'; +import { computed, ComputedRef } from 'vue'; +import { Head, useForm, usePage } from '@inertiajs/vue3'; +import { mdiAccountKey, mdiArrowLeftBoldOutline, mdiTrashCan, mdiImageText, mdiPlus, mdiAlertBoxOutline } from '@mdi/js'; import LayoutAuthenticated from '@/Layouts/LayoutAuthenticated.vue'; import SectionMain from '@/Components/SectionMain.vue'; import SectionTitleLineWithButton from '@/Components/SectionTitleLineWithButton.vue'; @@ -16,6 +17,7 @@ import standardTypes from 'mime/types/standard.js'; import otherTypes from 'mime/types/other.js'; import FormCheckRadioGroup from '@/Components/FormCheckRadioGroup.vue'; import MimetypeInput from '@/Components/MimetypeInput.vue'; +import NotificationBar from '@/Components/NotificationBar.vue'; defineProps({ borderless: Boolean, @@ -23,6 +25,10 @@ defineProps({ ctrlKFocus: Boolean, }); +const flash: ComputedRef<any> = computed(() => { + return usePage().props.flash; +}); + const customTypes: { [key: string]: string[] } = { 'application/vnd.opengeospatial.geopackage+sqlite3': ['gpkg'], 'text/plain': ['txt', 'asc', 'c', 'cc', 'h', 'srt'], @@ -141,6 +147,13 @@ const isValidForm = (): boolean => { <BaseButton :route-name="stardust.route('settings.mimetype.index')" :icon="mdiArrowLeftBoldOutline" label="Back" color="white" rounded-full small /> </SectionTitleLineWithButton> + + <NotificationBar v-if="flash.message" color="success" :icon="mdiAlertBoxOutline"> + {{ flash.message }} + </NotificationBar> + <!-- <FormValidationErrors v-bind:errors="errors" /> --> + + <CardBox form> <MimetypeInput @on-select-result="selectResult" @on-clear-input="clearInput" :transparent="transparent" :borderless="borderless" :mimeTypes="mimeTypes" :isValidMimeType="isValidMimeType" /> diff --git a/resources/js/Pages/Admin/User/Create.vue b/resources/js/Pages/Admin/User/Create.vue index ae29e84..17e525b 100644 --- a/resources/js/Pages/Admin/User/Create.vue +++ b/resources/js/Pages/Admin/User/Create.vue @@ -41,13 +41,28 @@ const form = useForm({ first_name: '', last_name: '', email: '', - password: '', + new_password: '', password_confirmation: '', roles: [], }); const submit = async () => { - await router.post(stardust.route('settings.user.store'), form); + // await router.post(stardust.route('settings.user.store'), form); + await form.post(stardust.route('settings.user.store'), { + preserveScroll: true, + onSuccess: () => { + form.reset(); + }, + onError: () => { + if (form.errors.new_password) { + form.reset('new_password'); + enabled.value = false; + // newPasswordInput.value.focus(); + // newPasswordInput.value?.focus(); + } + + }, + }); }; </script> @@ -109,7 +124,7 @@ const submit = async () => { </FormControl> </FormField> <password-meter :password="form.password" @score="handleScore" /> --> - <PasswordMeter v-model:password="form.password" :errors="form.errors" @score="handleScore" /> + <PasswordMeter v-model="form.new_password" :errors="form.errors" @score="handleScore" /> <FormField label="Password Confirmation" :class="{ 'text-red-400': errors.password_confirmation }"> <FormControl diff --git a/resources/js/Pages/Admin/User/Edit.vue b/resources/js/Pages/Admin/User/Edit.vue index 288af1c..ee7078a 100644 --- a/resources/js/Pages/Admin/User/Edit.vue +++ b/resources/js/Pages/Admin/User/Edit.vue @@ -42,14 +42,29 @@ const form = useForm({ first_name: props.user.first_name, last_name: props.user.last_name, email: props.user.email, - password: '', + new_password: '', password_confirmation: '', roles: props.userHasRoles, // fill actual user roles from db }); const submit = async () => { // await Inertia.post(stardust.route('user.store'), form); - await router.put(stardust.route('settings.user.update', [props.user.id]), form); + // await router.put(stardust.route('settings.user.update', [props.user.id]), form); + await form.put(stardust.route('settings.user.update', [props.user.id]), { + preserveScroll: true, + onSuccess: () => { + form.reset(); + }, + onError: () => { + if (form.errors.new_password) { + form.reset('new_password'); + enabled.value = false; + // newPasswordInput.value.focus(); + // newPasswordInput.value?.focus(); + } + + }, + }); }; const handleScore = (score: number) => { if (score >= 4){ @@ -108,15 +123,16 @@ const handleScore = (score: number) => { </FormControl> </FormField> - <FormField label="Password" :class="{ 'text-red-400': errors.password }"> + <!-- <FormField label="Password" :class="{ 'text-red-400': errors.password }"> <FormControl v-model="form.password" type="password" placeholder="Enter Password" :errors="errors.password"> <div class="text-red-400 text-sm" v-if="errors.password"> {{ errors.password }} </div> </FormControl> - </FormField> + </FormField> --> + + <PasswordMeter field-label="Reset User Password" :show-required-message="false" ref="newPasswordInput" v-model="form.new_password" :errors="form.errors" @score="handleScore" /> - <PasswordMeter v-model:password="form.password" :errors="form.errors" @score="handleScore" /> <FormField label="Password Confirmation" :class="{ 'text-red-400': errors.password_confirmation }"> <FormControl @@ -151,7 +167,7 @@ const handleScore = (score: number) => { color="info" label="Submit" :class="{ 'opacity-25': form.processing }" - :disabled="form.processing == true|| (form.password != '' && enabled == false)" + :disabled="form.processing == true|| (form.new_password != '' && enabled == false)" /> </BaseButtons> </template> diff --git a/resources/js/Pages/Auth/AccountInfo.vue b/resources/js/Pages/Auth/AccountInfo.vue index 195eace..d5f698d 100644 --- a/resources/js/Pages/Auth/AccountInfo.vue +++ b/resources/js/Pages/Auth/AccountInfo.vue @@ -1,7 +1,7 @@ <script setup lang="ts"> // import { Head, Link, useForm } from '@inertiajs/inertia-vue3'; import { ref } from 'vue'; -import { useForm } from '@inertiajs/vue3'; +import { useForm, Head } from '@inertiajs/vue3'; // import { ref } from 'vue'; // import { reactive } from 'vue'; import { @@ -126,6 +126,7 @@ const flash: Ref<any> = computed(() => { <template> <LayoutAuthenticated> + <Head title="Profile Security"></Head> <SectionMain> <SectionTitleLineWithButton :icon="mdiAccount" title="Profile" main> <BaseButton :route-name="stardust.route('dashboard')" :icon="mdiArrowLeftBoldOutline" label="Back" diff --git a/resources/js/Pages/Auth/Login.vue b/resources/js/Pages/Auth/Login.vue index d9a8451..b903c8a 100644 --- a/resources/js/Pages/Auth/Login.vue +++ b/resources/js/Pages/Auth/Login.vue @@ -6,7 +6,7 @@ <!-- <SectionFullScreen v-slot="{ cardClass }" :bg="'greenBlue'"> --> <SectionFullScreen v-slot="{ cardClass }"> <a class="text-2xl font-semibold flex justify-center items-center mb-8 lg:mb-10"> - <img src="../../logo.svg" class="h-10 mr-4" alt="Windster Logo" /> + <img src="../../logo.svg" class="h-10 mr-4 dark:invert" alt="Windster Logo" /> <!-- <span class="self-center text-2xl font-bold whitespace-nowrap">Tethys</span> --> </a> diff --git a/resources/js/Pages/Dashboard.vue b/resources/js/Pages/Dashboard.vue index 55f09d0..17e1a58 100644 --- a/resources/js/Pages/Dashboard.vue +++ b/resources/js/Pages/Dashboard.vue @@ -1,6 +1,6 @@ <script setup lang="ts"> -import { Head } from '@inertiajs/vue3'; -import { computed, onMounted } from 'vue'; +import { Head, usePage } from '@inertiajs/vue3'; +import { computed } from 'vue'; import { MainService } from '@/Stores/main'; import { mdiAccountMultiple, @@ -9,7 +9,6 @@ import { mdiFinance, mdiMonitorCellphone, mdiReload, - mdiGithub, mdiChartPie, } from '@mdi/js'; import LineChart from '@/Components/Charts/LineChart.vue'; @@ -17,18 +16,16 @@ import SectionMain from '@/Components/SectionMain.vue'; import CardBoxWidget from '@/Components/CardBoxWidget.vue'; import CardBox from '@/Components/CardBox.vue'; import TableSampleClients from '@/Components/TableSampleClients.vue'; -// import NotificationBar from '@/Components/NotificationBar.vue'; -import BaseButton from '@/Components/BaseButton.vue'; -import CardBoxClient from '@/Components/CardBoxClient.vue'; import LayoutAuthenticated from '@/Layouts/LayoutAuthenticated.vue'; import SectionTitleLineWithButton from '@/Components/SectionTitleLineWithButton.vue'; -import SectionBannerStarOnGitHub from '@/Components/SectionBannerStarOnGitea.vue'; +// import SectionBannerStarOnGitHub from '@/Components/SectionBannerStarOnGitea.vue'; import CardBoxDataset from '@/Components/CardBoxDataset.vue'; +import type { User } from '@/Dataset'; const mainService = MainService() // const chartData = ref(); const fillChartData = async () => { - await mainService.fetchChartData("2022"); + await mainService.fetchChartData(); // chartData.value = chartConfig.sampleChartData(); // chartData.value = mainService.graphData; }; @@ -46,13 +43,23 @@ const chartData = computed(() => mainService.graphData); // const clientBarItems = computed(() => mainService.clients.slice(0, 4)); // const transactionBarItems = computed(() => mainService.history); -const authorBarItems = computed(() => mainService.authors.slice(0, 5)); +mainService.fetchApi('clients'); +mainService.fetchApi('authors'); +mainService.fetchApi('datasets'); +mainService.fetchChartData(); + +// const authorBarItems = computed(() => mainService.authors.slice(0, 5)); const authors = computed(() => mainService.authors); const datasets = computed(() => mainService.datasets); const datasetBarItems = computed(() => mainService.datasets.slice(0, 5)); -// let test = datasets.value; -// console.log(test); +const submitters = computed(() => mainService.clients); +const user = computed(() => { + return usePage().props.authUser as User; +}); +const userHasRoles = (roleNames: Array<string>): boolean => { + return user.value.roles.some(role => roleNames.includes(role.name)); +}; </script> <template> @@ -61,15 +68,15 @@ const datasetBarItems = computed(() => mainService.datasets.slice(0, 5)); <SectionMain> <SectionTitleLineWithButton v-bind:icon="mdiChartTimelineVariant" title="Overview" main> - <BaseButton - href="https://gitea.geosphere.at/geolba/tethys.backend" + <!-- <BaseButton + href="" target="_blank" :icon="mdiGithub" label="Star on GeoSphere Forgejo" color="contrast" rounded-full small - /> + /> --> </SectionTitleLineWithButton> <div class="grid grid-cols-1 gap-6 lg:grid-cols-3 mb-6"> @@ -80,27 +87,25 @@ const datasetBarItems = computed(() => mainService.datasets.slice(0, 5)); :icon="mdiAccountMultiple" :number="authors.length" label="Authors" - /> - <CardBoxWidget - trend="193" + /> + <CardBoxWidget trend-type="info" color="text-blue-500" :icon="mdiDatabaseOutline" :number="datasets.length" label="Publications" - /> - <CardBoxWidget - trend="+25%" + /> + <CardBoxWidget trend-type="up" color="text-purple-500" :icon="mdiChartTimelineVariant" - :number="52" - label="Citations" + :number="submitters.length" + label="Submitters" /> </div> <div class="grid grid-cols-1 lg:grid-cols-2 gap-6 mb-6"> - <div class="flex flex-col justify-between"> + <!-- <div class="flex flex-col justify-between"> <CardBoxClient v-for="client in authorBarItems" :key="client.id" @@ -109,8 +114,9 @@ const datasetBarItems = computed(() => mainService.datasets.slice(0, 5)); :date="client.created_at" :text="client.identifier_orcid" :count="client.dataset_count" + /> - </div> + </div> --> <div class="flex flex-col justify-between"> <CardBoxDataset v-for="(dataset, index) in datasetBarItems" @@ -120,20 +126,18 @@ const datasetBarItems = computed(() => mainService.datasets.slice(0, 5)); </div> </div> - <SectionBannerStarOnGitHub /> + <!-- <SectionBannerStarOnGitHub /> --> - <SectionTitleLineWithButton :icon="mdiChartPie" title="Trends overview: Publications per month" /> + <SectionTitleLineWithButton :icon="mdiChartPie" title="Trends overview: Publications per month" ></SectionTitleLineWithButton> <CardBox title="Performance" :icon="mdiFinance" :header-icon="mdiReload" class="mb-6" @header-icon-click="fillChartData"> <div v-if="chartData"> <line-chart :data="chartData" class="h-96" /> </div> </CardBox> - <SectionTitleLineWithButton :icon="mdiAccountMultiple" title="Submitters" /> - + <SectionTitleLineWithButton v-if="userHasRoles(['administrator'])" :icon="mdiAccountMultiple" title="Submitters" /> <!-- <NotificationBar color="info" :icon="mdiMonitorCellphone"> <b>Responsive table.</b> Collapses on mobile </NotificationBar> --> - - <CardBox :icon="mdiMonitorCellphone" title="Responsive table" has-table> + <CardBox v-if="userHasRoles(['administrator'])" :icon="mdiMonitorCellphone" title="Responsive table" has-table> <TableSampleClients /> </CardBox> </SectionMain> diff --git a/resources/js/Pages/Editor/Dataset/Category.vue b/resources/js/Pages/Editor/Dataset/Category.vue new file mode 100644 index 0000000..e0fcfd9 --- /dev/null +++ b/resources/js/Pages/Editor/Dataset/Category.vue @@ -0,0 +1,377 @@ +<template> + <LayoutAuthenticated> + <Head title="Classify"></Head> + <SectionMain> + <SectionTitleLineWithButton :icon="mdiLibraryShelves" title="Library Classification" main> + <div class="bg-lime-100 shadow rounded-lg p-6 mb-6 flex items-center justify-between"> + <div> + <label for="role-select" class="block text-lg font-medium text-gray-700 mb-1"> + Select Classification Role <span class="text-red-500">*</span> + </label> + <select id="role-select" v-model="selectedCollectionRole" + class="w-full border border-gray-300 rounded-md p-2 text-gray-700 focus:ring-2 focus:ring-indigo-500" + required> + <!-- <option value="" disabled selected>Please select a role</option> --> + <option v-for="collRole in collectionRoles" :key="collRole.id" :value="collRole"> + {{ collRole.name }} + </option> + </select> + </div> + <div class="ml-4 hidden md:block"> + <span class="text-sm text-gray-600 italic">* required</span> + </div> + </div> + </SectionTitleLineWithButton> + + + <!-- Available TopLevel Collections --> + <CardBox class="mb-4 rounded-lg p-4"> + <h2 class="text-lg font-bold text-gray-800 dark:text-slate-400 mb-2">Available Toplevel-Collections + <span v-if="selectedCollectionRole && !selectedToplevelCollection" + class="text-sm text-red-500 italic">(click to + select)</span> + </h2> + <ul class="flex flex-wrap gap-2"> + <li v-for="col in collections" :key="col.id" :class="{ + 'cursor-pointer p-2 border border-gray-200 rounded hover:bg-sky-50 text-sky-700 text-sm': true, + 'bg-sky-100 border-sky-500': selectedToplevelCollection && selectedToplevelCollection.id === col.id + }" @click="onToplevelCollectionSelected(col)"> + <span class="text-sky-700">{{ col.name }}</span> + <span class="ml-2 px-2 py-0.5 bg-gray-200 text-gray-700 text-xs rounded-full">{{ col.number }}</span> + </li> + <li v-if="collections.length === 0" class="text-gray-800 dark:text-slate-400"> + No collections available. + </li> + </ul> + </CardBox> + + <!-- Collections Listing --> + <div class="grid grid-cols-1 md:grid-cols-3 gap-4 mb-4"> + + <!-- Broader Collection (Parent) --> + <CardBox v-if="selectedCollection" class="rounded-lg p-4" has-form-data> + <h2 class="text-lg font-bold text-gray-800 dark:text-slate-400 mb-2">Broader Collection</h2> + <draggable v-if="broaderCollections.length > 0" v-model="broaderCollections" + :group="{ name: 'collections' }" tag="ul" class="flex flex-wrap gap-2 max-h-60 overflow-y-auto"> + <template #item="{ element: parent }"> + <li :key="parent.id" :draggable="!parent.inUse" :class="getChildClasses(parent)" + @click="onCollectionSelected(parent)"> + <span class="text-sky-700">{{ parent.name }}</span> + <span class="ml-2 px-2 py-0.5 bg-gray-200 text-gray-700 text-xs rounded-full">{{ parent.number }}</span> + </li> + </template> + </draggable> + <ul v-else class="flex flex-wrap gap-2 max-h-60 overflow-y-auto"> + <li class="text-gray-500 text-sm"> + No broader collections available. + </li> + </ul> + </CardBox> + + <!-- Selected Collection Details --> + <CardBox v-if="selectedCollection" class="rounded-lg p-4" has-form-data> + <h3 class="text-xl font-bold text-gray-800 dark:text-slate-400 mb-2">Selected Collection</h3> + <!-- <p :class="[ + 'cursor-pointer p-2 border border-gray-200 rounded text-sm', + selectedCollection.inUse ? 'bg-gray-200 text-gray-500 drag-none' : 'bg-green-50 text-green-700 hover:bg-green-100 hover:underline cursor-move' + ]"></p> --> + <draggable v-model="selectedCollectionArray" :group="{ name: 'collections', pull: 'clone', put: false }" tag="ul" class="flex flex-wrap gap-2 max-h-60 overflow-y-auto"> + <template #item="{ element }"> + <li :key="element.id" :class="[ + 'p-2 border border-gray-200 rounded text-sm', + element.inUse ? 'bg-gray-200 text-gray-500 drag-none' : 'bg-green-50 text-green-700 hover:bg-green-100 hover:underline cursor-move' + ]"> + <span class="text-sky-700">{{ element.name }}</span> + <span class="ml-2 px-2 py-0.5 bg-gray-200 text-gray-700 text-xs rounded-full">{{ element.number }}</span> + </li> + </template> + </draggable> + </CardBox> + + <!-- Narrower Collections (Children) --> + <CardBox v-if="selectedCollection" class="rounded-lg p-4" has-form-data> + <h2 class="text-lg font-bold text-gray-800 dark:text-slate-400 mb-2">Narrower Collections</h2> + <draggable v-if="narrowerCollections.length > 0" v-model="narrowerCollections" + :group="{ name: 'collections' }" tag="ul" class="flex flex-wrap gap-2 max-h-60 overflow-y-auto"> + <template #item="{ element: child }"> + <li :key="child.id" :draggable="!child.inUse" :class="getChildClasses(child)" + @click="onCollectionSelected(child)"> + <span class="text-sky-700">{{ child.name }}</span> + <span class="ml-2 px-2 py-0.5 bg-gray-200 text-gray-700 text-xs rounded-full">{{ child.number }}</span> + </li> + </template> + </draggable> + <ul v-else class="flex flex-wrap gap-2 max-h-60 overflow-y-auto"> + <li class="text-gray-500 text-sm"> + No sub-collections available. + </li> + </ul> + </CardBox> + + </div> + + <div class="mb-4 rounded-lg"> + <div v-if="selectedCollection || selectedCollectionList.length > 0" class="bg-gray-100 shadow rounded-lg p-6 mb-6" :class="{ 'opacity-50': selectedCollection && selectedCollectionList.length === 0 }"> + <p class="mb-4 text-gray-700">Please drag your collections here to classify your previously created + dataset + according to library classification standards.</p> + <draggable v-model="selectedCollectionList" :group="{ name: 'collections' }" + class="min-h-36 border-dashed border-2 border-gray-400 p-4 text-sm flex flex-wrap gap-2 max-h-60 overflow-y-auto" + tag="ul" + :disabled="selectedCollection === null && selectedCollectionList.length > 0" + :style="{ opacity: (selectedCollection === null && selectedCollectionList.length > 0) ? 0.5 : 1, pointerEvents: (selectedCollection === null && selectedCollectionList.length > 0) ? 'none' : 'auto' }"> + <template #item="{ element }"> + <div :key="element.id" + class="p-2 m-1 bg-sky-200 text-sky-800 rounded flex items-center gap-2 h-7"> + <span class="text-sky-700">{{ element.name }}</span> + <span class="ml-2 px-2 py-0.5 bg-gray-200 text-gray-700 text-xs rounded-full">{{ element.number }}</span> + <button + @click="selectedCollectionList = selectedCollectionList.filter(item => item.id !== element.id)" + class="hover:text-sky-600 flex items-center"> + <svg xmlns="http://www.w3.org/2000/svg" class="h-4 w-4" viewBox="0 0 20 20" + fill="currentColor"> + <path fill-rule="evenodd" + d="M4.293 4.293a1 1 0 011.414 0L10 8.586l4.293-4.293a1 1 0 111.414 1.414L11.414 10l4.293 4.293a1 1 0 01-1.414 1.414L10 11.414l-4.293 4.293a1 1 0 01-1.414-1.414L8.586 10 4.293 5.707a1 1 0 010-1.414z" + clip-rule="evenodd" /> + </svg> + </button> + </div> + </template> + </draggable> + </div> + </div> + <div class="p-6 border-t border-gray-100 dark:border-slate-800"> + <BaseButtons> + <BaseButton @click.stop="syncDatasetCollections" label="Save" color="info" small + :disabled="isSaveDisabled" :style="{ opacity: isSaveDisabled ? 0.5 : 1 }"> + </BaseButton> + </BaseButtons> + </div> + </SectionMain> + </LayoutAuthenticated> +</template> + +<script setup lang="ts"> +import { ref, Ref, watch, computed } from 'vue'; +import { useForm } from '@inertiajs/vue3'; +import LayoutAuthenticated from '@/Layouts/LayoutAuthenticated.vue'; +import SectionMain from '@/Components/SectionMain.vue'; +import SectionTitleLineWithButton from '@/Components/SectionTitleLineWithButton.vue'; +import axios from 'axios'; +import { mdiLibraryShelves } from '@mdi/js'; +import draggable from 'vuedraggable'; +import BaseButton from '@/Components/BaseButton.vue'; +import BaseButtons from '@/Components/BaseButtons.vue'; +import CardBox from '@/Components/CardBox.vue'; +import { stardust } from '@eidellev/adonis-stardust/client'; +import { CollectionRole, Collection } from '@/types/models'; + +// import CollectionRoleSelector from '@/Components/Collection/CollectionRoleSelector.vue'; +// import ToplevelCollections from '@/Components/Collection/ToplevelCollections.vue'; +// import CollectionHierarchy from '@/Components/Collection/CollectionHierarchy.vue'; +// import CollectionDropZone from '@/Components/Collection/CollectionDropZone.vue'; + + + +/* -------------------------------------------------------------------------- + Props & Reactive State +-------------------------------------------------------------------------- */ +const props = defineProps({ + collectionRoles: { + type: Array, + required: true, + default: () => [] + }, + dataset: { + type: Object, + default: () => ({}), + }, + relatedCollections: { + type: Array as () => Collection[], + default: () => [] as const + } +}); + +const collectionRoles: Ref<CollectionRole[]> = ref(props.collectionRoles as CollectionRole[]); +const collections: Ref<Collection[]> = ref<Collection[]>([]); +const selectedCollectionRole = ref<CollectionRole | null>(null); +const selectedToplevelCollection = ref<Collection | null>(null); +const selectedCollection = ref<Collection | null>(null); +const narrowerCollections = ref<Collection[]>([]); +const broaderCollections = ref<Collection[]>([]); +// Reactive list that holds collections dropped by the user +const selectedCollectionList: Ref<Collection[]> = ref<Collection[]>([]); + + +// Wrap selectedCollection in an array for draggable (always expects an array) +const selectedCollectionArray = computed({ + get: () => (selectedCollection.value ? [selectedCollection.value] : []), + set: (value: Collection[]) => { + selectedCollection.value = value.length ? value[0] : null + } +}) + + +const form = useForm({ + collections: [] as number[], +}); + +// Watch for changes in dropCollections +watch( + () => selectedCollectionList.value, + () => { + if (selectedCollection.value) { + fetchCollections(selectedCollection.value.id); + } + }, + { deep: true } +); + + +/* -------------------------------------------------------------------------- + Watchers and Initial Setup +-------------------------------------------------------------------------- */ +// If the collectionRoles prop might load asynchronously (or change), you can watch for it: +watch( + () => props.collectionRoles as CollectionRole[], + (newCollectionRoles: CollectionRole[]) => { + collectionRoles.value = newCollectionRoles; + // Preselect the role with name "ccs" if it exists + const found: CollectionRole | undefined = collectionRoles.value.find( + role => role.name.toLowerCase() === 'ccs' + ); + if (found?.name === 'ccs') { + selectedCollectionRole.value = found; + } + }, + { immediate: true } +); + +// When collection role changes, update available collections and clear dependent state. +watch( + () => selectedCollectionRole.value as CollectionRole, + (newSelectedCollectionRole: CollectionRole | null) => { + if (newSelectedCollectionRole != null) { + collections.value = newSelectedCollectionRole.collections || [] + } else { + selectedToplevelCollection.value = null; + selectedCollection.value = null; + collections.value = [] + } + // Reset dependent variables when the role changes + selectedCollection.value = null + narrowerCollections.value = [] + broaderCollections.value = [] + }, + { immediate: true } +); + +/* -------------------------------------------------------------------------- + Methods +-------------------------------------------------------------------------- */ +const onToplevelCollectionSelected = (collection: Collection) => { + selectedToplevelCollection.value = collection; + selectedCollection.value = collection; + // call the API endpoint to get both. + fetchCollections(collection.id); +}; + +const onCollectionSelected = (collection: Collection) => { + selectedCollection.value = collection; + // call the API endpoint to get both. + fetchCollections(collection.id); +}; + +/** + * fetchCollections: Retrieves broader and narrower collections. + * Marks any narrower collection as inUse if it appears in selectedCollectionList. + */ +const fetchCollections = async (collectionId: number) => { + try { + const response = await axios.get(`/api/collections/${collectionId}`); + const data = response.data; + // Map each returned narrower collection + narrowerCollections.value = data.narrowerCollections.map((collection: Collection) => { + // If found, mark it as inUse. + const alreadyDropped = selectedCollectionList.value.find(dc => dc.id === collection.id); + return alreadyDropped ? { ...collection, inUse: true } : { ...collection, inUse: false }; + }); + broaderCollections.value = data.broaderCollection.map((collection: Collection) => { + const alreadyDropped = selectedCollectionList.value.find(dc => dc.id === collection.id); + return alreadyDropped ? { ...collection, inUse: true } : { ...collection, inUse: false }; + }); + // Check if selected collection is in the selected list + if (selectedCollection.value && selectedCollectionList.value.find(dc => dc.id === selectedCollection.value.id)) { + selectedCollection.value = { ...selectedCollection.value, inUse: true }; + } else if (selectedCollection.value) { + selectedCollection.value = { ...selectedCollection.value, inUse: false }; + } + } catch (error) { + console.error('Error in fetchCollections:', error); + } +}; + +const syncDatasetCollections = async () => { + // Extract the ids from the dropCollections list + form.collections = selectedCollectionList.value.map((item: Collection) => item.id); + form.put(stardust.route('editor.dataset.categorizeUpdate', [props.dataset.id]), { + preserveState: true, + onSuccess: () => { + console.log('Dataset collections synced successfully'); + }, + onError: (errors) => { + console.error('Error syncing dataset collections:', errors); + }, + }); +}; + +/** + * getChildClasses returns the Tailwind CSS classes to apply to each collection list item. + */ +const getChildClasses = (child: Collection) => { + return child.inUse + ? 'p-2 border border-gray-200 rounded bg-gray-200 text-gray-500 cursor-pointer drag-none' + : 'p-2 border border-gray-200 rounded bg-green-50 text-green-700 cursor-move hover:bg-green-100 hover:underline' +} + +// If there are related collections passed in, fill dropCollections with these. +if (props.relatedCollections && props.relatedCollections.length > 0) { + selectedCollectionList.value = props.relatedCollections; +} + +// Add a computed property for the disabled state based on dropCollections length +const isSaveDisabled = computed(() => selectedCollectionList.value.length === 0); +</script> + +<style scoped> +.btn-primary { + background-color: #4f46e5; + color: white; + border-radius: 0.25rem; +} + +.btn-primary:hover { + background-color: #4338ca; +} + +.btn-primary:focus { + outline: none; + box-shadow: 0 0 0 2px #fff, 0 0 0 4px #4f46e5; +} + +.btn-secondary { + background-color: white; + color: #374151; + border: 1px solid #d1d5db; + border-radius: 0.25rem; +} + +.btn-secondary:hover { + background-color: #f9fafb; +} + +.btn-secondary:focus { + outline: none; + box-shadow: 0 0 0 2px #fff, 0 0 0 4px #6366f1; +} +</style> diff --git a/resources/js/Pages/Editor/Dataset/Edit.vue b/resources/js/Pages/Editor/Dataset/Edit.vue new file mode 100644 index 0000000..e33e5dd --- /dev/null +++ b/resources/js/Pages/Editor/Dataset/Edit.vue @@ -0,0 +1,865 @@ +<template> + <LayoutAuthenticated> + + <Head title="Edit dataset" /> + <SectionMain> + <SectionTitleLineWithButton :icon="mdiImageText" title="Update dataset" main> + <BaseButton :route-name="stardust.route('editor.dataset.list')" :icon="mdiArrowLeftBoldOutline" + label="Back" color="white" rounded-full small /> + </SectionTitleLineWithButton> + + <NotificationBar v-if="flash.message" color="success" :icon="mdiAlertBoxOutline"> + {{ flash.message }} + </NotificationBar> + <FormValidationErrors v-bind:errors="errors" /> + + <CardBox :form="true"> + <!-- <FormValidationErrors v-bind:errors="errors" /> --> + <div class="mb-4"> + <div class="flex flex-col md:flex-row"> + <!-- (1) language field --> + <FormField label="Language *" help="required: select dataset main language" + :class="{ 'text-red-400': form.errors.language }" class="w-full flex-1"> + <FormControl required v-model="form.language" :type="'select'" + placeholder="[Enter Language]" :errors="form.errors.language" + :options="{ de: 'de', en: 'en' }"> + <div class="text-red-400 text-sm" v-if="form.errors.language"> + {{ form.errors.language.join(', ') }} + </div> + </FormControl> + </FormField> + </div> + + <!-- (2) licenses --> + <FormField label="Licenses" wrap-body :class="{ 'text-red-400': form.errors.licenses }" + class="mt-8 w-full mx-2 flex-1"> + <FormCheckRadioGroup type="radio" v-model="form.licenses" name="licenses" is-column + :options="licenses" /> + </FormField> + + <div class="flex flex-col md:flex-row"> + <!-- (3) dataset_type --> + <FormField label="Dataset Type *" help="required: dataset type" + :class="{ 'text-red-400': form.errors.type }" class="w-full mx-2 flex-1"> + <FormControl required v-model="form.type" :type="'select'" placeholder="-- select type --" + :errors="form.errors.type" :options="doctypes"> + <div class="text-red-400 text-sm" + v-if="form.errors.type && Array.isArray(form.errors.type)"> + {{ form.errors.type.join(', ') }} + </div> + </FormControl> + </FormField> + <!-- (4) creating_corporation --> + <FormField label="Creating Corporation *" + :class="{ 'text-red-400': form.errors.creating_corporation }" class="w-full mx-2 flex-1"> + <FormControl required v-model="form.creating_corporation" type="text" + placeholder="[enter creating corporation]" :is-read-only="true"> + <div class="text-red-400 text-sm" + v-if="form.errors.creating_corporation && Array.isArray(form.errors.creating_corporation)"> + {{ form.errors.creating_corporation.join(', ') }} + </div> + </FormControl> + </FormField> + </div> + + <BaseDivider /> + + <!-- (5) titles --> + <CardBox class="mb-6 shadow" :has-form-data="false" title="Titles" :icon="mdiFinance" + :header-icon="mdiPlusCircle" v-on:header-icon-click="addTitle()"> + <div class="flex flex-col md:flex-row"> + <FormField label="Main Title *" help="required: main title" + :class="{ 'text-red-400': form.errors['titles.0.value'] }" class="w-full mr-1 flex-1"> + <FormControl required v-model="form.titles[0].value" type="text" + placeholder="[enter main title]" :show-char-count="true" :max-input-length="255"> + <div class="text-red-400 text-sm" + v-if="form.errors['titles.0.value'] && Array.isArray(form.errors['titles.0.value'])"> + {{ form.errors['titles.0.value'].join(', ') }} + </div> + </FormControl> + </FormField> + <FormField label="Main Title Language*" help="required: main title language" + :class="{ 'text-red-400': form.errors['titles.0.language'] }" + class="w-full ml-1 flex-1"> + <FormControl required v-model="form.titles[0].language" type="text" + :is-read-only="true"> + <div class="text-red-400 text-sm" + v-if="form.errors['titles.0.language'] && Array.isArray(form.errors['titles.0.language'])"> + {{ form.errors['titles.0.language'].join(', ') }} + </div> + </FormControl> + </FormField> + </div> + + <label v-if="form.titles.length > 1">additional titles </label> + <!-- <BaseButton :icon="mdiPlusCircle" @click.prevent="addTitle()" color="modern" rounded-full small /> --> + <table> + <thead> + <tr> + <!-- <th v-if="checkable" /> --> + <th>Title Value</th> + <th>Title Type</th> + <th>Title Language</th> + <th /> + </tr> + </thead> + <tbody> + <template v-for="(title, index) in form.titles" :key="index"> + <tr v-if="title.type != 'Main'"> + <!-- <td scope="row">{{ index + 1 }}</td> --> + <td data-label="Title Value"> + <FormControl required v-model="form.titles[index].value" type="text" + placeholder="[enter main title]"> + <div class="text-red-400 text-sm" + v-if="form.errors[`titles.${index}.value`]"> + {{ form.errors[`titles.${index}.value`].join(', ') }} + </div> + </FormControl> + </td> + <td data-label="Title Type"> + <FormControl required v-model="form.titles[index].type" type="select" + :options="titletypes" placeholder="[select title type]"> + <div class="text-red-400 text-sm" + v-if="Array.isArray(form.errors[`titles.${index}.type`])"> + {{ form.errors[`titles.${index}.type`].join(', ') }} + </div> + </FormControl> + </td> + <td data-label="Title Language"> + <FormControl required v-model="form.titles[index].language" type="select" + :options="{ de: 'de', en: 'en' }" placeholder="[select title language]"> + <div class="text-red-400 text-sm" + v-if="form.errors[`titles.${index}.language`]"> + {{ form.errors[`titles.${index}.language`].join(', ') }} + </div> + </FormControl> + </td> + <td class="before:hidden lg:w-1 whitespace-nowrap"> + <BaseButtons type="justify-start lg:justify-end" no-wrap> + <!-- <BaseButton color="info" :icon="mdiEye" small @click="isModalActive = true" /> --> + <BaseButton color="danger" :icon="mdiTrashCan" small + v-if="title.id == undefined" @click.prevent="removeTitle(index)" /> + </BaseButtons> + </td> + </tr> + </template> + </tbody> + </table> + </CardBox> + + <!-- (6) descriptions --> + <CardBox class="mb-6 shadow" :has-form-data="false" title="Descriptions" :icon="mdiFinance" + :header-icon="mdiPlusCircle" v-on:header-icon-click="addDescription()"> + <div class="flex flex-col md:flex-row"> + <FormField label="Main Abstract *" help="required: main abstract" + :class="{ 'text-red-400': form.errors['descriptions.0.value'] }" + class="w-full mr-1 flex-1"> + <FormControl required v-model="form.descriptions[0].value" type="textarea" + placeholder="[enter main abstract]" :show-char-count="true" + :max-input-length="2500"> + <div class="text-red-400 text-sm" + v-if="form.errors['descriptions.0.value'] && Array.isArray(form.errors['descriptions.0.value'])"> + {{ form.errors['descriptions.0.value'].join(', ') }} + </div> + </FormControl> + </FormField> + <FormField label="Main Title Language*" help="required: main abstract language" + :class="{ 'text-red-400': form.errors['descriptions.0.language'] }" + class="w-full ml-1 flex-1"> + <FormControl required v-model="form.descriptions[0].language" type="text" + :is-read-only="true"> + <div class="text-red-400 text-sm" v-if="form.errors['descriptions.0.value'] && Array.isArray(form.errors['descriptions.0.language']) + "> + {{ form.errors['descriptions.0.language'].join(', ') }} + </div> + </FormControl> + </FormField> + </div> + <table> + <thead> + <tr> + <!-- <th v-if="checkable" /> --> + <th>Title Value</th> + <th>Title Type</th> + <th>Title Language</th> + <th /> + </tr> + </thead> + <tbody> + <template v-for="(item, index) in form.descriptions" :key="index"> + <tr v-if="item.type != 'Abstract'"> + <!-- <td scope="row">{{ index + 1 }}</td> --> + <td data-label="Description Value"> + <FormControl required v-model="form.descriptions[index].value" type="text" + placeholder="[enter main title]"> + <div class="text-red-400 text-sm" + v-if="form.errors[`descriptions.${index}.value`]"> + {{ form.errors[`descriptions.${index}.value`].join(', ') }} + </div> + </FormControl> + </td> + <td data-label="Description Type"> + <FormControl required v-model="form.descriptions[index].type" type="select" + :options="descriptiontypes" placeholder="[select title type]"> + <div class="text-red-400 text-sm" + v-if="Array.isArray(form.errors[`descriptions.${index}.type`])"> + {{ form.errors[`descriptions.${index}.type`].join(', ') }} + </div> + </FormControl> + </td> + <td data-label="Description Language"> + <FormControl required v-model="form.descriptions[index].language" + type="select" :options="{ de: 'de', en: 'en' }" + placeholder="[select title language]"> + <div class="text-red-400 text-sm" + v-if="form.errors[`descriptions.${index}.language`]"> + {{ form.errors[`descriptions.${index}.language`].join(', ') }} + </div> + </FormControl> + </td> + <td class="before:hidden lg:w-1 whitespace-nowrap"> + <BaseButtons type="justify-start lg:justify-end" no-wrap> + <!-- <BaseButton color="info" :icon="mdiEye" small @click="isModalActive = true" /> --> + <BaseButton color="danger" :icon="mdiTrashCan" small + v-if="item.id == undefined" + @click.prevent="removeDescription(index)" /> + </BaseButtons> + </td> + </tr> + </template> + </tbody> + </table> + </CardBox> + + <!-- (7) authors --> + <CardBox class="mb-6 shadow" has-table title="Creators" :icon="mdiBookOpenPageVariant" + :header-icon="mdiPlusCircle" v-on:header-icon-click="addNewAuthor()"> + <SearchAutocomplete source="/api/persons" :response-property="'first_name'" + placeholder="search in person table...." v-on:person="onAddAuthor"></SearchAutocomplete> + + <TablePersons :persons="form.authors" v-if="form.authors.length > 0" :relation="'authors'" /> + <div class="text-red-400 text-sm" + v-if="form.errors.authors && Array.isArray(form.errors.authors)"> + {{ form.errors.authors.join(', ') }} + </div> + </CardBox> + + + <!-- (8) contributors --> + <CardBox class="mb-6 shadow" has-table title="Contributors" :icon="mdiBookOpenPageVariant" + :header-icon="mdiPlusCircle" v-on:header-icon-click="addNewContributor()"> + <SearchAutocomplete source="/api/persons" :response-property="'first_name'" + placeholder="search in person table...." v-on:person="onAddContributor"> + </SearchAutocomplete> + + <TablePersons :persons="form.contributors" v-if="form.contributors.length > 0" + :contributortypes="contributorTypes" :errors="form.errors" :relation="'contributors'" /> + <div class="text-red-400 text-sm" + v-if="form.errors.contributors && Array.isArray(form.errors.contributors)"> + {{ form.errors.contributors.join(', ') }} + </div> + </CardBox> + + <div class="flex flex-col md:flex-row"> + <!-- (9) project_id --> + <FormField label="Project.." help="project is optional" + :class="{ 'text-red-400': form.errors.project_id }" class="w-full mx-2 flex-1"> + <FormControl required v-model="form.project_id" :type="'select'" + placeholder="[Select Project]" :errors="form.errors.project_id" :options="projects"> + <div class="text-red-400 text-sm" v-if="form.errors.project_id"> + {{ form.errors.project_id.join(', ') }} + </div> + </FormControl> + </FormField> + <!-- (10) embargo_date --> + <FormField label="Embargo Date.." help="embargo date is optional" + :class="{ 'text-red-400': form.errors.embargo_date }" class="w-full mx-2 flex-1"> + <FormControl v-model="form.embargo_date" :type="'date'" placeholder="date('y-m-d')" + :errors="form.errors.embargo_date"> + <div class="text-red-400 text-sm" v-if="form.errors.embargo_date"> + {{ form.errors.embargo_date.join(', ') }} + </div> + </FormControl> + </FormField> + </div> + + <BaseDivider /> + + <MapComponent v-if="form.coverage" :mapOptions="mapOptions" :baseMaps="baseMaps" + :fitBounds="fitBounds" :coverage="form.coverage" :mapId="mapId" + v-bind-event:onMapInitializedEvent="onMapInitialized"> + </MapComponent> + <div class="flex flex-col md:flex-row"> + <!-- x min and max --> + <FormField label="Coverage X Min" :class="{ 'text-red-400': form.errors['coverage.x_min'] }" + class="w-full mx-2 flex-1"> + <FormControl required v-model="form.coverage.x_min" type="text" placeholder="[enter x_min]"> + <div class="text-red-400 text-sm" + v-if="form.errors['coverage.x_min'] && Array.isArray(form.errors['coverage.x_min'])"> + {{ form.errors['coverage.x_min'].join(', ') }} + </div> + </FormControl> + </FormField> + <FormField label="Coverage X Max" :class="{ 'text-red-400': form.errors['coverage.x_max'] }" + class="w-full mx-2 flex-1"> + <FormControl required v-model="form.coverage.x_max" type="text" placeholder="[enter x_max]"> + <div class="text-red-400 text-sm" + v-if="form.errors['coverage.x_max'] && Array.isArray(form.errors['coverage.x_max'])"> + {{ form.errors['coverage.x_max'].join(', ') }} + </div> + </FormControl> + </FormField> + <!-- y min and max --> + <FormField label="Coverage Y Min" :class="{ 'text-red-400': form.errors['coverage.y_min'] }" + class="w-full mx-2 flex-1"> + <FormControl required v-model="form.coverage.y_min" type="text" placeholder="[enter y_min]"> + <div class="text-red-400 text-sm" + v-if="form.errors['coverage.y_min'] && Array.isArray(form.errors['coverage.y_min'])"> + {{ form.errors['coverage.y_min'].join(', ') }} + </div> + </FormControl> + </FormField> + <FormField label="Coverage Y Max" :class="{ 'text-red-400': form.errors['coverage.y_max'] }" + class="w-full mx-2 flex-1"> + <FormControl required v-model="form.coverage.y_max" type="text" placeholder="[enter y_max]"> + <div class="text-red-400 text-sm" + v-if="form.errors['coverage.y_max'] && Array.isArray(form.errors['coverage.y_max'])"> + {{ form.errors['coverage.y_max'].join(', ') }} + </div> + </FormControl> + </FormField> + </div> + + <CardBox class="mb-6 shadow" has-table title="Dataset References" :icon="mdiEarthPlus" + :header-icon="mdiPlusCircle" v-on:header-icon-click="addReference()"> + <!-- Message when no references exist --> + <div v-if="form.references.length === 0" class="text-center py-4"> + <p class="text-gray-600">No references added yet.</p> + <p class="text-gray-400">Click the plus icon above to add a new reference.</p> + </div> + <!-- Reference form --> + <table class="table-fixed border-green-900" v-if="form.references.length"> + <thead> + <tr> + <th class="w-4/12">Value</th> + <th class="w-2/12">Type</th> + <th class="w-3/12">Relation</th> + <th class="w-2/12">Label</th> + <th class="w-1/12"></th> + </tr> + </thead> + <tbody> + <tr v-for="(item, index) in form.references"> + <td data-label="Reference Value"> + <!-- <input name="Reference Value" class="form-control" + placeholder="[VALUE]" v-model="item.value" /> --> + <FormControl required v-model="item.value" :type="'text'" placeholder="[VALUE]" + :errors="form.errors.embargo_date"> + <div class="text-red-400 text-sm" + v-if="form.errors[`references.${index}.value`] && Array.isArray(form.errors[`references.${index}.value`])"> + {{ form.errors[`references.${index}.value`].join(', ') }} + </div> + </FormControl> + + </td> + <td> + <FormControl required v-model="form.references[index].type" type="select" + :options="referenceIdentifierTypes" placeholder="[type]"> + <div class="text-red-400 text-sm" + v-if="Array.isArray(form.errors[`references.${index}.type`])"> + {{ form.errors[`references.${index}.type`].join(', ') }} + </div> + </FormControl> + </td> + + <td> + <!-- {!! Form::select('Reference[Relation]', $relationTypes, null, + ['placeholder' => '[relationType]', 'v-model' => 'item.relation', + 'data-vv-scope' => 'step-2']) + !!} --> + <FormControl required v-model="form.references[index].relation" type="select" + :options="relationTypes" placeholder="[relation type]"> + <div class="text-red-400 text-sm" + v-if="Array.isArray(form.errors[`references.${index}.relation`])"> + {{ form.errors[`references.${index}.relation`].join(', ') }} + </div> + </FormControl> + </td> + <td data-label="Reference Label"> + <!-- <input name="Reference Label" class="form-control" v-model="item.label" /> --> + <FormControl required v-model="form.references[index].label" type="text" + placeholder="[reference label]"> + <div class="text-red-400 text-sm" + v-if="form.errors[`references.${index}.label`]"> + {{ form.errors[`references.${index}.label`].join(', ') }} + + </div> + </FormControl> + </td> + <td class="before:hidden lg:w-1 whitespace-nowrap"> + <!-- <BaseButton color="info" :icon="mdiEye" small @click="isModalActive = true" /> --> + <BaseButton color="danger" :icon="mdiTrashCan" small + @click.prevent="removeReference(index)" /> + </td> + </tr> + </tbody> + </table> + <!-- References to delete section --> + <div v-if="form.referencesToDelete && form.referencesToDelete.length > 0" class="mt-8"> + <h1 class="pt-8 pb-3 font-semibold sm:text-lg text-gray-900">References To Delete</h1> + <ul class="flex flex-1 flex-wrap -m-1"> + <li v-for="(element, index) in form.referencesToDelete" :key="index" + class="block p-1 w-1/2 sm:w-1/3 md:w-1/4 lg:w-1/6 xl:w-1/8 h-40"> + <article tabindex="0" + class="bg-red-100 group w-full h-full rounded-md cursor-pointer relative shadow-sm overflow-hidden"> + <section + class="flex flex-col rounded-md text-xs break-words w-full h-full z-20 absolute top-0 py-2 px-3"> + <h1 class="flex-1 text-gray-700 group-hover:text-blue-800 font-medium text-sm mb-1 truncate overflow-hidden whitespace-nowrap"> + {{ element.value }} + </h1> + <div class="flex flex-col mt-auto"> + <p class="p-1 size text-xs text-gray-700"> + <span class="font-semibold">Type:</span> {{ element.type }} + </p> + <p class="p-1 size text-xs text-gray-700"> + <span class="font-semibold">Relation:</span> {{ element.relation }} + </p> + <div class="flex justify-end mt-1"> + <button + class="restore ml-auto focus:outline-none hover:bg-gray-300 p-1 rounded-md text-gray-800" + @click.prevent="restoreReference(index)"> + <svg viewBox="0 0 24 24" class="w-5 h-5"> + <path fill="currentColor" :d="mdiRestore"></path> + </svg> + </button> + </div> + </div> + </section> + </article> + </li> + </ul> + </div> + </CardBox> + + <BaseDivider /> + + <CardBox class="mb-6 shadow" has-table title="Dataset Keywords" :icon="mdiEarthPlus" + :header-icon="mdiPlusCircle" v-on:header-icon-click="addKeyword()"> + <!-- <ul> + <li v-for="(subject, index) in form.subjects" :key="index"> + {{ subject.value }} <BaseButton color="danger" :icon="mdiTrashCan" small @click.prevent="removeKeyword(index)" /> + </li> + </ul> --> + <TableKeywords :keywords="form.subjects" :errors="form.errors" :subjectTypes="subjectTypes" v-model:subjects-to-delete="form.subjectsToDelete" + v-if="form.subjects.length > 0" /> + </CardBox> + + </div> + + <!-- download file list --> + <div class="mb-6"> + <h3 class="text-lg font-medium text-gray-700 mb-2 flex items-center"> + Files + <div class="inline-block relative ml-2 group"> + <button + class="w-5 h-5 rounded-full bg-gray-200 text-gray-600 text-xs flex items-center justify-center focus:outline-none hover:bg-gray-300"> + i + </button> + <div + class="absolute left-0 top-full mt-1 w-64 bg-white shadow-lg rounded-md p-3 text-xs text-left z-50 transform scale-0 origin-top-left transition-transform duration-100 group-hover:scale-100"> + <p class="text-gray-700"> + As a research data repository editor, you can only download the submitted files. + Files cannot be + edited or replaced at this stage. + </p> + <div class="absolute -top-1 left-1 w-2 h-2 bg-white transform rotate-45"></div> + </div> + </div> + </h3> + + <div v-if="form.files && form.files.length > 0" class="bg-white rounded-lg shadow overflow-hidden"> + <ul class="divide-y divide-gray-200"> + <li v-for="file in form.files" :key="file.id" + class="px-4 py-3 flex items-center justify-between hover:bg-gray-50"> + <div class="flex items-center space-x-3 flex-1"> + <div class="flex-shrink-0"> + <svg class="h-6 w-6 text-gray-400" xmlns="http://www.w3.org/2000/svg" + fill="none" viewBox="0 0 24 24" stroke="currentColor"> + <path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" + d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z" /> + </svg> + </div> + <div class="min-w-0 flex-1"> + <p class="text-sm font-medium text-gray-900 truncate"> + {{ file.label }} + </p> + <p class="text-xs text-gray-500 truncate"> + {{ getFileSize(file) }} + </p> + </div> + </div> + <div class="ml-2 flex-shrink-0 flex space-x-2"> + <a v-if="file.id != undefined" + :href="stardust.route('editor.file.download', [file.id])" + class="inline-flex items-center px-2.5 py-1.5 border border-transparent text-xs font-medium rounded text-blue-700 bg-blue-100 hover:bg-blue-200"> + Download + </a> + </div> + + </li> + </ul> + </div> + </div> + + <template #footer> + <BaseButtons> + <BaseButton @click.stop="submit" :disabled="form.processing" label="Save" color="info" + :class="{ 'opacity-25': form.processing }" small> + </BaseButton> + <!-- <button :disabled="form.processing" :class="{ 'opacity-25': form.processing }" + class="text-base hover:scale-110 focus:outline-none flex justify-center px-4 py-2 rounded font-bold cursor-pointer hover:bg-teal-200 bg-teal-100 text-teal-700 border duration-200 ease-in-out border-teal-600 transition" + @click.stop="submit"> + Save + </button> --> + </BaseButtons> + </template> + </CardBox> + <!-- Loading Spinner --> + <div v-if="form.processing" + class="fixed inset-0 flex items-center justify-center bg-gray-500 bg-opacity-50 z-50"> + <svg class="animate-spin h-12 w-12 text-white" xmlns="http://www.w3.org/2000/svg" fill="none" + viewBox="0 0 24 24"> + <circle class="opacity-25" cx="12" cy="12" r="10" stroke="currentColor" stroke-width="4"></circle> + <path class="opacity-75" fill="currentColor" d="M12 2a10 10 0 0110 10h-4a6 6 0 00-6-6V2z"></path> + </svg> + </div> + </SectionMain> + </LayoutAuthenticated> +</template> + +<script setup lang="ts"> +// import EditComponent from "./../EditComponent"; +// export default EditComponent; + +// import { Component, Vue, Prop, Setup, toNative } from 'vue-facing-decorator'; +// import AuthLayout from '@/Layouts/Auth.vue'; +import LayoutAuthenticated from '@/Layouts/LayoutAuthenticated.vue'; +import { useForm, Head, usePage } from '@inertiajs/vue3'; +import { computed, ComputedRef } from 'vue'; +import { Dataset, Title, Subject, Person, License } from '@/Dataset'; +import { stardust } from '@eidellev/adonis-stardust/client'; + +import FormField from '@/Components/FormField.vue'; +import FormControl from '@/Components/FormControl.vue'; +import SectionMain from '@/Components/SectionMain.vue'; +import SectionTitleLineWithButton from '@/Components/SectionTitleLineWithButton.vue'; +import FormCheckRadioGroup from '@/Components/FormCheckRadioGroup.vue'; +import BaseButton from '@/Components/BaseButton.vue'; +import BaseButtons from '@/Components/BaseButtons.vue'; +import BaseDivider from '@/Components/BaseDivider.vue'; +import CardBox from '@/Components/CardBox.vue'; +import MapComponent from '@/Components/Map/map.component.vue'; +import SearchAutocomplete from '@/Components/SearchAutocomplete.vue'; +import TablePersons from '@/Components/TablePersons.vue'; +import TableKeywords from '@/Components/TableKeywords.vue'; +import FormValidationErrors from '@/Components/FormValidationErrors.vue'; +import { MapOptions } from '@/Components/Map/MapOptions'; +import { LatLngBoundsExpression } from 'leaflet'; +import { LayerOptions } from '@/Components/Map/LayerOptions'; +import { + mdiImageText, + mdiArrowLeftBoldOutline, + mdiPlusCircle, + mdiFinance, + mdiTrashCan, + mdiBookOpenPageVariant, + mdiEarthPlus, + mdiAlertBoxOutline, + mdiRestore +} from '@mdi/js'; +import { notify } from '@/notiwind'; +import NotificationBar from '@/Components/NotificationBar.vue'; + +const props = defineProps({ + // errors: { + // type: Object, + // default: () => ({}), + // }, + licenses: { + type: Object, + default: () => ({}), + }, + languages: { + type: Object, + default: () => ({}), + }, + doctypes: { + type: Object, + default: () => ({}), + }, + titletypes: { + type: Object, + default: () => ({}), + }, + projects: { + type: Object, + default: () => ({}), + }, + descriptiontypes: { + type: Object, + default: () => ({}), + }, + contributorTypes: { + type: Object, + default: () => ({}), + }, + subjectTypes: { + type: Object, + default: () => ({}), + }, + referenceIdentifierTypes: { + type: Object, + default: () => ({}), + }, + relationTypes: { + type: Object, + default: () => ({}), + }, + dataset: { + type: Object, + default: () => ({}), + }, + + + +}); +const flash: ComputedRef<any> = computed(() => { + return usePage().props.flash; +}); +const errors: ComputedRef<any> = computed(() => { + return usePage().props.errors; +}); + +const mapOptions: MapOptions = { + center: [48.208174, 16.373819], + zoom: 3, + zoomControl: false, + attributionControl: false, +}; +const baseMaps: Map<string, LayerOptions> = new Map<string, LayerOptions>(); +const fitBounds: LatLngBoundsExpression = [ + [46.4318173285, 9.47996951665], + [49.0390742051, 16.9796667823], +]; +const mapId = 'test'; + +// const downloadFile = async (id: string): Promise<string> => { +// const response = await axios.get<Blob>(`/api/download/${id}`, { +// responseType: 'blob', +// }); +// const url = URL.createObjectURL(response.data); +// setTimeout(() => { +// URL.revokeObjectURL(url); +// }, 1000); +// return url; +// }; + +// for (const file of props.dataset.files) { +// // console.log(`${file.name} path is ${file.filePath} here.`); +// file.fileSrc = ref(""); +// // downloadFile(file.id).then((value: string) => { +// // file.fileSrc = ref(value); +// // form = useForm<Dataset>(props.dataset as Dataset); +// // }); +// } + +// props.dataset.filesToDelete = []; +props.dataset.subjectsToDelete = []; +props.dataset.referencesToDelete = []; +let form = useForm<Dataset>(props.dataset as Dataset); + +// const mainService = MainService(); +// mainService.fetchfiles(props.dataset); + + +const submit = async (): Promise<void> => { + let route = stardust.route('editor.dataset.update', [props.dataset.id]); + // await Inertia.post('/app/register', this.form); + // await router.post('/app/register', this.form); + + + let licenses = form.licenses.map((obj) => { + if (hasIdAttribute(obj)) { + return obj.id.toString() + } else { + return obj; + } + }); + + await form + .transform((data) => ({ + ...data, + licenses: licenses, + rights: 'true', + })) + // .put(route); + .put(route, { + onSuccess: () => { + // console.log(form.data()); + // mainService.setDataset(form.data()); + // formStep.value++; + // form.filesToDelete = []; + // Clear the array using splice + form.subjectsToDelete?.splice(0, form.subjectsToDelete.length); + form.referencesToDelete?.splice(0, form.referencesToDelete.length); + }, + }); +}; + +const hasIdAttribute = (obj: License | number): obj is License => { + return typeof obj === 'object' && 'id' in obj; +}; + +const addTitle = () => { + let newTitle: Title = { value: '', language: '', type: '' }; + form.titles.push(newTitle); +}; +const removeTitle = (key: any) => { + form.titles.splice(key, 1); +}; + +const addDescription = () => { + let newDescription = { value: '', language: '', type: '' }; + form.descriptions.push(newDescription); +}; +const removeDescription = (key: any) => { + form.descriptions.splice(key, 1); +}; + +const addNewAuthor = () => { + let newAuthor = { status: false, first_name: '', last_name: '', email: '', academic_title: '', identifier_orcid: '', name_type: 'Personal' }; + form.authors.push(newAuthor); +}; + +const onAddAuthor = (person: Person) => { + if (form.authors.filter((e) => e.id === person.id).length > 0) { + notify({ type: 'warning', title: 'Warning', text: 'person is already defined as author' }, 4000); + } else if (form.contributors.filter((e) => e.id === person.id).length > 0) { + notify({ type: 'warning', title: 'Warning', text: 'person is already defined as contributor' }); + } else { + form.authors.push(person); + notify({ type: 'info', text: 'person has been successfully added as author' }); + } +}; + +const addNewContributor = () => { + let newContributor = { status: false, first_name: '', last_name: '', email: '', academic_title: '', identifier_orcid: '', name_type: 'Personal', pivot: { contributor_type: '' } }; + form.contributors.push(newContributor); +}; + +const onAddContributor = (person: Person) => { + if (form.contributors.filter((e) => e.id === person.id).length > 0) { + notify({ type: 'warning', title: 'Warning', text: 'person is already defined as contributor' }, 4000); + } else if (form.authors.filter((e) => e.id === person.id).length > 0) { + notify({ type: 'warning', title: 'Warning', text: 'person is already defined as author' }, 4000); + } else { + // person.pivot = { contributor_type: '' }; + // // person.pivot = { name_type: '', contributor_type: '' }; + form.contributors.push(person); + notify({ type: 'info', text: 'person has been successfully added as contributor' }, 4000); + } +}; + +const addKeyword = () => { + let newSubject: Subject = { value: '', language: '', type: 'uncontrolled' }; + //this.dataset.files.push(uploadedFiles[i]); + form.subjects.push(newSubject); +}; + +const addReference = () => { + let newReference = { value: '', label: '', relation: '', type: '' }; + //this.dataset.files.push(uploadedFiles[i]); + form.references.push(newReference); +}; + + +const removeReference = (key: any) => { + const reference = form.references[key]; + + // If the reference has an ID, it exists in the database + // and should be added to referencesToDelete + if (reference.id) { + // Initialize referencesToDelete array if it doesn't exist + if (!form.referencesToDelete) { + form.referencesToDelete = []; + } + + // Add to referencesToDelete + form.referencesToDelete.push(reference); + } + + // Remove from form.references array + form.references.splice(key, 1); +}; + +const restoreReference = (index: number) => { + // Get the reference from referencesToDelete + const reference = form.referencesToDelete[index]; + + // Add it back to form.references + form.references.push(reference); + + // Remove it from referencesToDelete + form.referencesToDelete.splice(index, 1); +}; + +const onMapInitialized = (newItem: any) => { + console.log(newItem); +}; + +const getFileSize = (file: File) => { + if (file.size > 1024) { + if (file.size > 1048576) { + return Math.round(file.size / 1048576) + 'mb'; + } else { + return Math.round(file.size / 1024) + 'kb'; + } + } else { + return file.size + 'b'; + } +} +</script> + +<style scoped> +.max-w-2xl { + max-width: 2xl; +} + +.text-2xl { + font-size: 2xl; +} + +.font-bold { + font-weight: bold; +} + +.mb-4 { + margin-bottom: 1rem; +} + +.block { + display: block; +} + +.text-gray-700 { + color: #4b5563; +} + +.shadow { + box-shadow: + 0 0 0 1px rgba(66, 72, 78, 0.05), + 0 1px 2px 0 rgba(66, 72, 78, 0.08), + 0 2px 4px 0 rgba(66, 72, 78, 0.12), + 0 4px 8px 0 rgba(66, 72, 78, 0.16); +} +</style> \ No newline at end of file diff --git a/resources/js/Pages/Editor/Dataset/Index.vue b/resources/js/Pages/Editor/Dataset/Index.vue index ef6156b..e154d48 100644 --- a/resources/js/Pages/Editor/Dataset/Index.vue +++ b/resources/js/Pages/Editor/Dataset/Index.vue @@ -2,7 +2,7 @@ // import { Head, Link, useForm, usePage } from '@inertiajs/inertia-vue3'; import { Head, usePage } from '@inertiajs/vue3'; import { ComputedRef } from 'vue'; -import { mdiSquareEditOutline, mdiAlertBoxOutline, mdiShareVariant, mdiBookEdit, mdiUndo } from '@mdi/js'; +import { mdiSquareEditOutline, mdiAlertBoxOutline, mdiShareVariant, mdiBookEdit, mdiUndo, mdiLibraryShelves } from '@mdi/js'; import { computed } from 'vue'; import LayoutAuthenticated from '@/Layouts/LayoutAuthenticated.vue'; import SectionMain from '@/Components/SectionMain.vue'; @@ -96,8 +96,8 @@ const formatServerState = (state: string) => { <Head title="Editor Datasets" /> <SectionMain> - - + + <NotificationBar v-if="flash.message" color="success" :icon="mdiAlertBoxOutline"> {{ flash.message }} </NotificationBar> @@ -108,31 +108,30 @@ const formatServerState = (state: string) => { {{ flash.error }} </NotificationBar> + <!-- table --> <CardBox class="mb-6" has-table> <div v-if="props.datasets.data.length > 0"> <table> <thead> <tr> - <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider"> + <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider dark:text-white"> <!-- <Sort label="Dataset Title" attribute="title" :search="form.search" /> --> Title </th> - <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider"> + <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider dark:text-white"> Submitter </th> - <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider"> - <!-- <Sort label="Email" attribute="email" :search="form.search" /> --> + <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider dark:text-white"> State </th> - - <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider"> + <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider dark:text-white"> Editor </th> - <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider"> + <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider dark:text-white"> Date of last modification </th> - <th scope="col" class="relative px-6 py-3" v-if="can.edit || can.delete"> + <th scope="col" class="relative px-6 py-3 dark:text-white" v-if="can.edit || can.delete"> <span class="sr-only">Actions</span> </th> </tr> @@ -141,70 +140,110 @@ const formatServerState = (state: string) => { <tbody class="bg-white divide-y divide-gray-200"> <tr v-for="dataset in props.datasets.data" :key="dataset.id" :class="[getRowClass(dataset)]"> - <td data-label="Login" class="py-4 whitespace-nowrap text-gray-700 dark:text-white"> - <!-- <Link v-bind:href="stardust.route('user.show', [user.id])" + <td data-label="Login" + class="py-4 whitespace-nowrap text-gray-700 table-title"> + <!-- <Link v-bind:href="stardust.route('settings.user.show', [user.id])" class="no-underline hover:underline text-cyan-600 dark:text-cyan-400"> {{ user.login }} </Link> --> - <div class="text-sm font-medium">{{ dataset.main_title }}</div> + <!-- {{ user.id }} --> + {{ dataset.main_title }} </td> - <td class="py-4 whitespace-nowrap text-gray-700 dark:text-white"> + <td class="py-4 whitespace-nowrap text-gray-700"> <div class="text-sm">{{ dataset.user.login }}</div> </td> - <td class="py-4 whitespace-nowrap text-gray-700 dark:text-white"> + <td class="py-4 whitespace-nowrap text-gray-700"> <div class="text-sm"> {{ formatServerState(dataset.server_state) }}</div> + <div v-if="dataset.server_state === 'rejected_reviewer' && dataset.reject_reviewer_note" + class="inline-block relative ml-2 group"> + <button + class="w-5 h-5 rounded-full bg-gray-200 text-gray-600 text-xs flex items-center justify-center focus:outline-none hover:bg-gray-300"> + i + </button> + <div + class="absolute left-0 top-full mt-1 w-64 bg-white shadow-lg rounded-md p-3 text-xs text-left z-50 transform scale-0 origin-top-left transition-transform duration-100 group-hover:scale-100"> + <p class="text-gray-700 max-h-40 overflow-y-auto overflow-x-hidden whitespace-normal break-words"> + {{ dataset.reject_reviewer_note }} + </p> + <div class="absolute -top-1 left-1 w-2 h-2 bg-white transform rotate-45"> + </div> + </div> + </div> </td> - <td class="py-4 whitespace-nowrap text-gray-700 dark:text-white" + <td class="py-4 whitespace-nowrap text-gray-700" v-if="dataset.server_state === 'released'"> <div class="text-sm" :title="dataset.server_date_modified"> Preferred reviewer: {{ dataset.preferred_reviewer }} </div> </td> - <td class="py-4 whitespace-nowrap text-gray-700 dark:text-white" + <td class="py-4 whitespace-nowrap text-gray-700" v-else-if="dataset.server_state === 'editor_accepted' || dataset.server_state === 'rejected_reviewer'"> <div class="text-sm" :title="dataset.server_date_modified"> In approval by: {{ dataset.editor?.login }} </div> </td> - <td class="py-4 whitespace-nowrap text-gray-700 dark:text-white" v-else> + <td class="py-4 whitespace-nowrap text-gray-700" v-else> <div class="text-sm">{{ dataset.editor?.login }}</div> </td> - <td data-label="modified" class="py-4 whitespace-nowrap text-gray-700 dark:text-white"> + <td data-label="modified" class="py-4 whitespace-nowrap text-gray-700"> <div class="text-sm" :title="dataset.server_date_modified"> {{ dataset.server_date_modified }} </div> </td> <td class="py-4 whitespace-nowrap text-right text-sm font-medium text-gray-700 dark:text-white"> - <BaseButtons type="justify-start lg:justify-end" no-wrap> + <div type="justify-start lg:justify-end" class="grid grid-cols-2 gap-x-2 gap-y-2" + no-wrap> + <BaseButton v-if="can.receive && (dataset.server_state == 'released')" :route-name="stardust.route('editor.dataset.receive', [dataset.id])" - color="info" :icon="mdiSquareEditOutline" :label="'Receive edit task'" - small /> + color="info" :icon="mdiSquareEditOutline" :label="'Receive edit task'" small + class="col-span-1" /> <BaseButton v-if="can.approve && (dataset.server_state == 'editor_accepted' || dataset.server_state == 'rejected_reviewer')" :route-name="stardust.route('editor.dataset.approve', [dataset.id])" - color="info" :icon="mdiShareVariant" :label="'Approve'" small /> + color="info" :icon="mdiShareVariant" :label="'Approve'" small + class="col-span-1" /> <BaseButton v-if="can.approve && (dataset.server_state == 'editor_accepted' || dataset.server_state == 'rejected_reviewer')" - :route-name="stardust.route('editor.dataset.reject', [dataset.id])" - color="info" :icon="mdiUndo" label="Reject" small> + :route-name="stardust.route('editor.dataset.reject', [dataset.id])" + color="info" :icon="mdiUndo" label="Reject" small class="col-span-1"> </BaseButton> + <BaseButton + v-if="can.edit && (dataset.server_state == 'editor_accepted' || dataset.server_state == 'rejected_reviewer')" + :route-name="stardust.route('editor.dataset.edit', [Number(dataset.id)])" + color="info" :icon="mdiSquareEditOutline" :label="'Edit'" small + class="col-span-1"> + </BaseButton> + + <BaseButton + v-if="can.edit && (dataset.server_state == 'editor_accepted' || dataset.server_state == 'rejected_reviewer')" + :route-name="stardust.route('editor.dataset.categorize', [dataset.id])" + color="info" :icon="mdiLibraryShelves" :label="'Classify'" small + class="col-span-1"> + </BaseButton> + + <BaseButton v-if="can.publish && (dataset.server_state == 'reviewed')" + :route-name="stardust.route('editor.dataset.rejectToReviewer', [dataset.id])" + color="info" :icon="mdiUndo" :label="'Reject To Reviewer'" small + class="col-span-1" /> <BaseButton v-if="can.publish && (dataset.server_state == 'reviewed')" :route-name="stardust.route('editor.dataset.publish', [dataset.id])" - color="info" :icon="mdiBookEdit" :label="'Publish'" small /> + color="info" :icon="mdiBookEdit" :label="'Publish'" small + class="col-span-1" /> <BaseButton v-if="can.publish && (dataset.server_state == 'published' && !dataset.identifier)" :route-name="stardust.route('editor.dataset.doi', [dataset.id])" - color="info" :icon="mdiBookEdit" :label="'Mint DOI'" small /> + color="info" :icon="mdiBookEdit" :label="'Mint DOI'" small + class="col-span-1 last-in-row" /> - </BaseButtons> + </div> </td> </tr> </tbody> @@ -231,3 +270,17 @@ const formatServerState = (state: string) => { </SectionMain> </LayoutAuthenticated> </template> + + +<style scoped lang="css"> +.table-title { + max-width: 200px; + /* set a maximum width */ + overflow: hidden; + /* hide overflow */ + text-overflow: ellipsis; + /* show ellipsis for overflowed text */ + white-space: nowrap; + /* prevent wrapping */ +} +</style> \ No newline at end of file diff --git a/resources/js/Pages/Editor/Dataset/Publish.vue b/resources/js/Pages/Editor/Dataset/Publish.vue index d6929d2..5df3958 100644 --- a/resources/js/Pages/Editor/Dataset/Publish.vue +++ b/resources/js/Pages/Editor/Dataset/Publish.vue @@ -10,7 +10,7 @@ import FormControl from '@/Components/FormControl.vue'; import BaseButton from '@/Components/BaseButton.vue'; import BaseButtons from '@/Components/BaseButtons.vue'; import { stardust } from '@eidellev/adonis-stardust/client'; -import { mdiArrowLeftBoldOutline, mdiReiterate } from '@mdi/js'; +import { mdiArrowLeftBoldOutline, mdiReiterate, mdiBookEdit, mdiUndo } from '@mdi/js'; import FormValidationErrors from '@/Components/FormValidationErrors.vue'; const props = defineProps({ @@ -18,6 +18,10 @@ const props = defineProps({ type: Object, default: () => ({}), }, + can: { + type: Object, + default: () => ({}), + }, }); const flash: Ref<any> = computed(() => { @@ -93,7 +97,11 @@ const handleSubmit = async (e) => { </p> <BaseButtons> <BaseButton type="submit" color="info" label="Set published" - :class="{ 'opacity-25': form.processing }" :disabled="form.processing" /> + :class="{ 'opacity-25': form.processing }" :disabled="form.processing" :icon="mdiBookEdit" small /> + <BaseButton v-if="can.reject && (dataset.server_state == 'reviewed')" + :route-name="stardust.route('editor.dataset.rejectToReviewer', [dataset.id])" + color="info" :icon="mdiUndo" :label="'Reject To Reviewer'" small + class="col-span-1" /> </BaseButtons> </template> </CardBox> diff --git a/resources/js/Pages/Editor/Dataset/RejectToReviewer.vue b/resources/js/Pages/Editor/Dataset/RejectToReviewer.vue new file mode 100644 index 0000000..7889c2c --- /dev/null +++ b/resources/js/Pages/Editor/Dataset/RejectToReviewer.vue @@ -0,0 +1,117 @@ +<script setup lang="ts"> +import LayoutAuthenticated from '@/Layouts/LayoutAuthenticated.vue'; +import SectionMain from '@/Components/SectionMain.vue'; +import SectionTitleLineWithButton from '@/Components/SectionTitleLineWithButton.vue'; +import { useForm, Head, usePage } from '@inertiajs/vue3'; +import { computed, Ref } from 'vue'; +import CardBox from '@/Components/CardBox.vue'; +import FormField from '@/Components/FormField.vue'; +import FormControl from '@/Components/FormControl.vue'; +import BaseButton from '@/Components/BaseButton.vue'; +import BaseButtons from '@/Components/BaseButtons.vue'; +import { stardust } from '@eidellev/adonis-stardust/client'; +import { mdiArrowLeftBoldOutline, mdiReiterate } from '@mdi/js'; +import FormValidationErrors from '@/Components/FormValidationErrors.vue'; + +const props = defineProps({ + dataset: { + type: Object, + default: () => ({}), + }, +}); + +// Define the computed property for the label +const computedLabel = computed(() => { + return `Reject to reviewer: ${props.dataset.reviewer?.login || 'Unknown User'}`; +}); +const computedEmailLabel = computed(() => { + return props.dataset.reviewer?.email || ''; +}); + + +const flash: Ref<any> = computed(() => { + return usePage().props.flash; +}); +const errors: Ref<any> = computed(() => { + return usePage().props.errors; +}); + +const form = useForm({ + server_state: 'rejected_to_reviewer', + reject_editor_note: '', + send_email: false, +}); + +const handleSubmit = async (e: SubmitEvent) => { + e.preventDefault(); + await form.put(stardust.route('editor.dataset.rejectToReviewerUpdate', [props.dataset.id])); + // await form.put(stardust.route('editor.dataset.update', [props.dataset.id])); +}; +</script> + +<template> + <LayoutAuthenticated> + + <Head title="Reject reviewed dataset" /> + <SectionMain> + <SectionTitleLineWithButton :icon="mdiReiterate" title="Reject reviewed dataset to reviewer" main> + <BaseButton :route-name="stardust.route('editor.dataset.list')" :icon="mdiArrowLeftBoldOutline" + label="Back" color="white" rounded-full small /> + </SectionTitleLineWithButton> + + <CardBox form @submit.prevent="handleSubmit"> + <FormValidationErrors v-bind:errors="errors" /> + + + <FormField label="server state" :class="{ 'text-red-400': form.errors.server_state }"> + <FormControl v-model="form.server_state" type="text" placeholder="-- server state --" + :is-read-only="true" :error="form.errors.server_state"> + <div class="text-red-400 text-sm" v-if="form.errors.server_state"> + {{ form.errors.server_state }} + </div> + </FormControl> + </FormField> + <FormField label="reject note" :class="{ 'text-red-400': form.errors.reject_editor_note }"> + <FormControl v-model="form.reject_editor_note" type="textarea" + placeholder="-- reject note for reviewer --" :error="form.errors.reject_editor_note"> + <div class="text-red-400 text-sm" v-if="form.errors.reject_editor_note"> + {{ form.errors.reject_editor_note }} + </div> + </FormControl> + </FormField> + + <!-- <FormControl + type="checkbox" + v-model="form.send_email" + :error="form.errors.send_email"> + </FormControl> --> + + <FormField label="Email Notification"> + <label for="send_email" class="flex items-center mr-6 mb-3"> + <input type="checkbox" id="send_email" v-model="form.send_email" class="mr-2" /> + <span class="check"></span> + <a class="pl-2 " target="_blank">send email to reviewer + <span class="text-blue-600 hover:underline"> + {{ computedEmailLabel }} + </span> + </a> + </label> + </FormField> + + <div v-if="flash && flash.warning" class="flex flex-col mt-6 animate-fade-in"> + <div class="bg-yellow-500 border-l-4 border-orange-400 text-white p-4" role="alert"> + <p class="font-bold">Be Warned</p> + <p>{{ flash.warning }}</p> + </div> + </div> + + <template #footer> + <BaseButtons> + <BaseButton type="submit" color="info" :label="computedLabel" + :class="{ 'opacity-25': form.processing }" :disabled="form.processing" /> + </BaseButtons> + </template> + </CardBox> + </SectionMain> + </LayoutAuthenticated> +</template> diff --git a/resources/js/Pages/Errors/ServerError.vue b/resources/js/Pages/Errors/ServerError.vue index 5d97ede..74bcdc0 100644 --- a/resources/js/Pages/Errors/ServerError.vue +++ b/resources/js/Pages/Errors/ServerError.vue @@ -20,11 +20,13 @@ import SectionTitleLineWithButton from '@/Components/SectionTitleLineWithButton. import BaseButton from '@/Components/BaseButton.vue'; import { mdiLightbulbAlert, mdiArrowLeftBoldOutline } from '@mdi/js'; import { stardust } from '@eidellev/adonis-stardust/client'; - -@Component({ - // options: { - // layout: DefaultLayout, - // }, +import LayoutGuest from '@/Layouts/LayoutGuest.vue'; + + + @Component({ + options: { + layout: LayoutGuest, + }, name: 'AppComponent', components: { diff --git a/resources/js/Pages/Errors/postgres_error.vue b/resources/js/Pages/Errors/postgres_error.vue new file mode 100644 index 0000000..ed5dd59 --- /dev/null +++ b/resources/js/Pages/Errors/postgres_error.vue @@ -0,0 +1,71 @@ +<template> + <div class="min-h-screen flex items-center justify-center bg-gray-100"> + <div class="max-w-md w-full p-6 bg-white rounded-md shadow-md"> + <h1 class="text-2xl font-bold text-red-500 mb-4">{{ status }}</h1> + <p class="text-gray-700 mb-4">{{ message }}</p> + <div class="text-sm text-gray-500 mb-4"> + <p>Error Code: {{ details.code }}</p> + <p>Type: {{ details.type }}</p> + <div v-for="(port, index) in details.ports" :key="index"> + <p>Connection attempt {{ index + 1 }}: {{ port.address }}:{{ port.port }}</p> + </div> + </div> + <SectionTitleLineWithButton :icon="mdiLightbulbAlert" :title="'Database Error'" :main="true"> + <BaseButton @click.prevent="handleAction" :icon="mdiArrowLeftBoldOutline" label="Dashboard" + color="white" rounded-full small /> + </SectionTitleLineWithButton> + </div> + </div> +</template> + +<script lang="ts"> +import { Component, Vue, Prop } from 'vue-facing-decorator'; +import { Link, router } from '@inertiajs/vue3'; +import SectionTitleLineWithButton from '@/Components/SectionTitleLineWithButton.vue'; +import BaseButton from '@/Components/BaseButton.vue'; +import { mdiLightbulbAlert, mdiArrowLeftBoldOutline } from '@mdi/js'; +import { stardust } from '@eidellev/adonis-stardust/client'; +import LayoutGuest from '@/Layouts/LayoutGuest.vue'; + +@Component({ + options: { + layout: LayoutGuest, + }, + name: 'PostgresError', + components: { + Link, + BaseButton, + SectionTitleLineWithButton, + }, +}) +export default class AppComponent extends Vue { + @Prop({ + type: String, + default: '', + }) + status: string; + + @Prop({ + type: String, + default: '', + }) + message: string; + + @Prop({ + type: Object, + default: () => ({}), + }) + details: { + code: string; + type: string; + ports: Array<{ port: number; address: string }>; + }; + + mdiLightbulbAlert = mdiLightbulbAlert; + mdiArrowLeftBoldOutline = mdiArrowLeftBoldOutline; + + public async handleAction() { + await router.get(stardust.route('dashboard')); + } +} +</script> diff --git a/resources/js/Pages/Reviewer/Dataset/Index.vue b/resources/js/Pages/Reviewer/Dataset/Index.vue index 84d56e7..36d2351 100644 --- a/resources/js/Pages/Reviewer/Dataset/Index.vue +++ b/resources/js/Pages/Reviewer/Dataset/Index.vue @@ -51,6 +51,8 @@ const getRowClass = (dataset) => { rowclass = 'bg-released'; } else if (dataset.server_state == 'published') { rowclass = 'bg-published'; + } else if (dataset.server_state == 'rejected_to_reviewer') { + rowclass = 'bg-rejected-reviewer'; } else { rowclass = ''; } @@ -96,14 +98,14 @@ const formatServerState = (state: string) => { <table> <thead> <tr> - <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider"> + <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider dark:text-white"> <!-- <Sort label="Dataset Title" attribute="title" :search="form.search" /> --> Title </th> - <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider"> + <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider dark:text-white"> ID </th> - <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider"> + <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider dark:text-white"> <!-- <Sort label="Email" attribute="email" :search="form.search" /> --> State </th> @@ -111,10 +113,10 @@ const formatServerState = (state: string) => { <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider"> Editor </th> - <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider"> + <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider dark:text-white"> Remaining Time </th> - <th scope="col" class="relative px-6 py-3" v-if="can.edit || can.delete"> + <th scope="col" class="relative px-6 py-3 dark:text-white" v-if="can.edit || can.delete"> <span class="sr-only">Actions</span> </th> </tr> @@ -122,39 +124,52 @@ const formatServerState = (state: string) => { <tbody> <tr v-for="dataset in props.datasets.data" :key="dataset.id" :class="[getRowClass(dataset)]"> - <td data-label="Login" class="py-4 whitespace-nowrap text-gray-700 dark:text-white"> - <!-- <Link v-bind:href="stardust.route('user.show', [user.id])" - class="no-underline hover:underline text-cyan-600 dark:text-cyan-400"> - {{ user.login }} - </Link> --> - <div class="text-sm font-medium">{{ dataset.main_title }}</div> + <td data-label="Login" + class="py-4 whitespace-nowrap text-gray-700"> + <div class="text-sm table-title">{{ dataset.main_title }}</div> </td> - <td class="py-4 whitespace-nowrap text-gray-700 dark:text-white"> + <td class="py-4 whitespace-nowrap text-gray-700"> <div class="text-sm">{{ dataset.id }}</div> </td> - <td class="py-4 whitespace-nowrap text-gray-700 dark:text-white"> + <td class="py-4 whitespace-nowrap text-gray-700"> <div class="text-sm">{{ formatServerState(dataset.server_state) }}</div> + <div v-if="dataset.server_state === 'rejected_to_reviewer' && dataset.reject_editor_note" + class="inline-block relative ml-2 group"> + <button + class="w-5 h-5 rounded-full bg-gray-200 text-gray-600 text-xs flex items-center justify-center focus:outline-none hover:bg-gray-300"> + i + </button> + <div + class="absolute left-0 top-full mt-1 w-64 bg-white shadow-lg rounded-md p-3 text-xs text-left z-50 transform scale-0 origin-top-left transition-transform duration-100 group-hover:scale-100"> + <p class="text-gray-700 max-h-40 overflow-y-auto overflow-x-hidden whitespace-normal break-words"> + {{ dataset.reject_editor_note }} + </p> + <div class="absolute -top-1 left-1 w-2 h-2 bg-white transform rotate-45"> + </div> + </div> + </div> </td> - <td class="py-4 whitespace-nowrap text-gray-700 dark:text-white"> + <td class="py-4 whitespace-nowrap text-gray-700"> <div class="text-sm">{{ dataset.editor?.login }}</div> </td> - <td data-label="modified" class="py-4 whitespace-nowrap text-gray-700 dark:text-white"> + <td data-label="modified" class="py-4 whitespace-nowrap text-gray-700"> <div class="text-sm" :title="dataset.remaining_time"> {{ dataset.remaining_time + ' days' }} </div> </td> <td - class="py-4 whitespace-nowrap text-right text-sm font-medium text-gray-700 dark:text-white"> + class="py-4 whitespace-nowrap text-right text-sm font-medium text-gray-700"> <BaseButtons type="justify-start lg:justify-end" no-wrap> - <BaseButton v-if="can.review && (dataset.server_state == 'approved')" + <BaseButton + v-if="can.reject && (dataset.server_state == 'approved' || dataset.server_state == 'rejected_to_reviewer')" :route-name="stardust.route('reviewer.dataset.review', [dataset.id])" - color="info" :icon="mdiGlasses" :label="'Review'" small /> + color="info" :icon="mdiGlasses" :label="'View'" small /> <BaseButton - v-if="can.reject && (dataset.server_state == 'approved')" + v-if="can.reject && (dataset.server_state == 'approved' || dataset.server_state == 'rejected_to_reviewer')" :route-name="stardust.route('reviewer.dataset.reject', [dataset.id])" color="info" :icon="mdiReiterate" :label="'Reject'" small /> </BaseButtons> @@ -185,3 +200,16 @@ const formatServerState = (state: string) => { </LayoutAuthenticated> </template> +<style scoped lang="css"> +.table-title { + max-width: 200px; + /* set a maximum width */ + overflow: hidden; + /* hide overflow */ + text-overflow: ellipsis; + /* show ellipsis for overflowed text */ + white-space: nowrap; + /* prevent wrapping */ +} + +</style> \ No newline at end of file diff --git a/resources/js/Pages/Reviewer/Dataset/Review.vue b/resources/js/Pages/Reviewer/Dataset/Review.vue index 4213bc2..b33500b 100644 --- a/resources/js/Pages/Reviewer/Dataset/Review.vue +++ b/resources/js/Pages/Reviewer/Dataset/Review.vue @@ -10,15 +10,23 @@ import BaseButtons from '@/Components/BaseButtons.vue'; import { stardust } from '@eidellev/adonis-stardust/client'; import { mdiArrowLeftBoldOutline, mdiGlasses } from '@mdi/js'; import FormValidationErrors from '@/Components/FormValidationErrors.vue'; +import { mdiReiterate, mdiBookOpenPageVariant, mdiFinance } from '@mdi/js'; +import MapComponentView from '@/Components/Map/MapComponentView.vue'; +import IconSvg from '@/Components/Icons/IconSvg.vue'; +import CardBoxSimple from '@/Components/CardBoxSimple.vue'; const props = defineProps({ dataset: { type: Object, default: () => ({}), }, - fields: { + // fields: { + // type: Object, + // required: true, + // }, + can: { type: Object, - required: true, + default: () => ({}), }, }); @@ -29,18 +37,6 @@ const errors: Ref<any> = computed(() => { return usePage().props.errors; }); -// const form = useForm({ -// preferred_reviewer: '', -// preferred_reviewer_email: '', -// preferation: 'yes_preferation', - -// // preferation: '', -// // isPreferationRequired: false, -// }); - - -// const isPreferationRequired = computed(() => form.preferation === 'yes_preferation'); - const handleSubmit = async (e) => { e.preventDefault(); @@ -48,6 +44,19 @@ const handleSubmit = async (e) => { // await form.put(stardust.route('dataset.releaseUpdate', [props.dataset.id])); // // await form.put(stardust.route('editor.dataset.update', [props.dataset.id])); }; + + +const getFileSize = (file: File) => { + if (file.size > 1024) { + if (file.size > 1048576) { + return Math.round(file.size / 1048576) + 'mb'; + } else { + return Math.round(file.size / 1024) + 'kb'; + } + } else { + return file.size + 'b'; + } +} </script> <template> @@ -56,10 +65,10 @@ const handleSubmit = async (e) => { <Head title="Review dataset" /> <SectionMain> <SectionTitleLineWithButton :icon="mdiGlasses" title="Review approved dataset" main> - <BaseButton :route-name="stardust.route('reviewer.dataset.list')" :icon="mdiArrowLeftBoldOutline" label="Back" - color="white" rounded-full small /> + <BaseButton :route-name="stardust.route('reviewer.dataset.list')" :icon="mdiArrowLeftBoldOutline" + label="Back" color="white" rounded-full small /> </SectionTitleLineWithButton> - <CardBox form @submit.prevent="handleSubmit"> + <component is="form" form @submit.prevent="handleSubmit"> <FormValidationErrors v-bind:errors="errors" /> <div v-if="flash && flash.warning" class="flex flex-col mt-6 animate-fade-in"> @@ -70,26 +79,545 @@ const handleSubmit = async (e) => { </div> - <div class="flex flex-col"> - <div class="flex flex-row items-center justify-between dark:bg-slate-900 bg-gray-200 p-2 mb-2" - v-for="(fieldValue, field) in fields" :key="field"> + <!-- <div class="mb-4"> --> - <label :for="field" class="font-bold h-6 mt-3 text-xs leading-8 uppercase">{{ field }}</label> - <span class="text-sm text-gray-600" v-html="fieldValue"></span> + <CardBoxSimple> + <div class="mb-6"> + <h4 class="text-sm font-medium text-gray-700 dark:text-gray-300 mb-2">Language</h4> + <div class="bg-emerald-50 dark:bg-emerald-900/30 border border-emerald-200 dark:border-emerald-800 + rounded-lg p-3 shadow-sm"> + <div class="flex items-center"> + <IconSvg path="language" :size="20" + className="mr-2 text-emerald-600 dark:text-emerald-400" /> + <span class="text-emerald-700 dark:text-emerald-300 font-medium"> + {{ dataset.language || 'Not specified' }} + </span> + </div> + </div> </div> - </div> + + <!-- Licenses --> + <div class="mb-6"> + <h4 class="text-sm font-medium text-gray-700 dark:text-gray-300 mb-3">Licenses</h4> + <div v-if="dataset.licenses && dataset.licenses.length > 0" class="space-y-2"> + <div v-for="license in dataset.licenses" :key="license.id" class="bg-emerald-50 dark:bg-emerald-900/30 border border-emerald-200 dark:border-emerald-800 + rounded-lg p-3 shadow-sm hover:bg-emerald-100 dark:hover:bg-emerald-900/50 transition-colors"> + <div class="flex items-center"> + <IconSvg path="license" :size="20" + className="mr-2 text-emerald-600 dark:text-emerald-400" /> + <span class="text-emerald-700 dark:text-emerald-300"> + {{ license.name }} + </span> + </div> + </div> + </div> + <div v-else class="text-center py-4"> + <p class="text-gray-500 dark:text-gray-400 italic">No licenses specified</p> + </div> + <div v-if="dataset.licenses && dataset.licenses.length > 0" + class="mt-3 text-xs text-gray-500 dark:text-gray-400"> + Total licenses: {{ dataset.licenses.length }} + </div> + </div> + + <div class="flex flex-col md:flex-row gap-4 mb-6"> + <!-- (3) dataset_type --> + <div class="w-full mx-2 flex-1"> + <h4 class="text-sm font-medium text-gray-700 dark:text-gray-300 mb-2">Dataset Type</h4> + <div class="bg-emerald-50 dark:bg-emerald-900/30 border border-emerald-200 dark:border-emerald-800 + rounded-lg p-3 shadow-sm"> + <div class="flex items-center"> + <IconSvg path="book" :size="20" + className="mr-2 text-emerald-600 dark:text-emerald-400" /> + <span class="text-emerald-700 dark:text-emerald-300 font-medium"> + {{ dataset.type || 'Not specified' }} + </span> + </div> + </div> + </div> + + <!-- (4) creating_corporation --> + <div class="w-full mx-2 flex-1"> + <h4 class="text-sm font-medium text-gray-700 dark:text-gray-300 mb-2">Creating + Corporation + </h4> + <div class="bg-emerald-50 dark:bg-emerald-900/30 border border-emerald-200 dark:border-emerald-800 + rounded-lg p-3 shadow-sm"> + <div class="flex items-center"> + <IconSvg path="building" :size="20" + className="mr-2 text-emerald-600 dark:text-emerald-400" /> + <span class="text-emerald-700 dark:text-emerald-300 font-medium"> + {{ dataset.creating_corporation || 'Not specified' }} + </span> + </div> + </div> + </div> + </div> + + <div class="flex flex-col md:flex-row gap-4 mb-6"> + <!-- (9) project_id --> + <div class="w-full mx-2 flex-1"> + <h4 class="text-sm font-medium text-gray-700 dark:text-gray-300 mb-2">Project</h4> + <div class="bg-emerald-50 dark:bg-emerald-900/30 border border-emerald-200 dark:border-emerald-800 + rounded-lg p-3 shadow-sm"> + <span class="text-emerald-700 dark:text-emerald-300"> + {{ dataset.project?.label || 'Not specified' }} + </span> + </div> + </div> + <!-- (10) embargo_date --> + <div class="w-full mx-2 flex-1"> + <h4 class="text-sm font-medium text-gray-700 dark:text-gray-300 mb-2">Embargo Date</h4> + <div class="bg-emerald-50 dark:bg-emerald-900/30 border border-emerald-200 dark:border-emerald-800 + rounded-lg p-3 shadow-sm"> + <span v-if="dataset.embargo_date" class="text-emerald-700 dark:text-emerald-300"> + {{ dataset.embargo_date }} + </span> + <span v-else class="text-gray-500 dark:text-gray-400 italic"> + No embargo date set + </span> + </div> + </div> + </div> + + </CardBoxSimple> + + <!-- (5) titles --> + <CardBox class="mb-6 shadow" :has-form-data="false" title="Titles" :icon="mdiFinance" + :show-header-icon="false"> + <div class="p-4"> + <!-- Main Title (highlighted) --> + <h4 class="text-sm font-medium text-gray-700 dark:text-gray-300 mb-3">Main Title</h4> + <div class="bg-emerald-50 dark:bg-emerald-900/30 border-l-4 border border-emerald-300 dark:border-emerald-700 + rounded-lg p-4 shadow-sm mb-4"> + <div class="flex justify-between items-start mb-2"> + <span class="inline-flex items-center px-2.5 py-0.5 rounded-full text-xs font-medium bg-emerald-200 + dark:bg-emerald-800 text-emerald-800 dark:text-emerald-200"> + {{ dataset.titles[0].language }} + </span> + <span class="inline-flex items-center px-2.5 py-0.5 rounded-full text-xs font-medium bg-emerald-200 + dark:bg-emerald-800 text-emerald-800 dark:text-emerald-200"> + Main + </span> + </div> + <h3 + class="text-lg font-medium text-emerald-800 dark:text-emerald-200 whitespace-pre-line break-words overflow-wrap-anywhere"> + {{ dataset.titles[0].value }} + </h3> + </div> + + <!-- Additional titles --> + <div v-if="dataset.titles.length > 1"> + <h4 class="text-sm font-medium text-gray-700 dark:text-gray-300 mb-3">Additional Titles + </h4> + <div class="grid gap-3"> + <template v-for="(title, index) in dataset.titles" :key="index"> + <div v-if="title.type != 'Main'" + class="bg-emerald-50/70 dark:bg-emerald-900/20 border border-emerald-200 dark:border-emerald-800 + rounded-lg p-3 shadow-sm hover:bg-emerald-50 dark:hover:bg-emerald-900/30 transition-colors"> + <div class="flex justify-between items-start mb-2"> + <span class="inline-flex items-center px-2.5 py-0.5 rounded-full text-xs font-medium + bg-emerald-100 dark:bg-emerald-800/70 text-emerald-700 dark:text-emerald-300"> + {{ title.language }} + </span> + <span class="inline-flex items-center px-2.5 py-0.5 rounded-full text-xs font-medium + bg-emerald-100 dark:bg-emerald-800/70 text-emerald-700 dark:text-emerald-300"> + {{ title.type }} + </span> + </div> + <p + class="text-emerald-700 dark:text-emerald-300 font-medium whitespace-pre-line break-words overflow-wrap-anywhere"> + {{ title.value }} + </p> + </div> + </template> + </div> + </div> + <div class="mt-3 text-xs text-gray-500 dark:text-gray-400"> + Total titles: {{ dataset.titles.length }} + </div> + </div> + </CardBox> + + <!-- (6) descriptions --> + <CardBox class="mb-6 shadow" :has-form-data="false" title="Descriptions" :icon="mdiFinance" + :show-header-icon="false"> + <!-- Main Abstract (highlighted) --> + <div class="p-4"> + <h4 class="text-sm font-medium text-gray-700 dark:text-gray-300 mb-3">Main Abstract</h4> + <div class="bg-emerald-50 dark:bg-emerald-900/30 border-l-4 border border-emerald-300 dark:border-emerald-700 + rounded-lg p-4 shadow-sm mb-4"> + <div class="flex justify-between items-start mb-2"> + <span class="inline-flex items-center px-2.5 py-0.5 rounded-full text-xs font-medium bg-emerald-200 + dark:bg-emerald-800 text-emerald-800 dark:text-emerald-200"> + {{ dataset.descriptions[0].language }} + </span> + <span class="inline-flex items-center px-2.5 py-0.5 rounded-full text-xs font-medium bg-emerald-200 + dark:bg-emerald-800 text-emerald-800 dark:text-emerald-200"> + Abstract + </span> + </div> + <div class="prose prose-emerald dark:prose-invert max-w-none"> + <p + class="text-emerald-800 dark:text-emerald-200 whitespace-pre-line break-words overflow-wrap-anywhere"> + {{ dataset.descriptions[0].value }} + </p> + </div> + </div> + <!-- Additional descriptions --> + <div v-if="dataset.descriptions.length > 1"> + <h4 class="text-sm font-medium text-gray-700 dark:text-gray-300 mb-3">Additional + Descriptions</h4> + <div class="grid gap-3"> + <div v-for="(item, index) in dataset.descriptions" :key="index"> + <div v-if="item.type != 'Abstract'" class="bg-emerald-50/70 dark:bg-emerald-900/20 border border-emerald-200 + dark:border-emerald-800 + rounded-lg p-3 shadow-sm hover:bg-emerald-50 dark:hover:bg-emerald-900/30 + transition-colors"> + <div class="flex justify-between items-start mb-2"> + <span class="inline-flex items-center px-2.5 py-0.5 rounded-full text-xs font-medium + bg-emerald-100 dark:bg-emerald-800/70 text-emerald-700 dark:text-emerald-300"> + {{ item.language }} + </span> + <span class="inline-flex items-center px-2.5 py-0.5 rounded-full text-xs font-medium + bg-emerald-100 dark:bg-emerald-800/70 text-emerald-700 dark:text-emerald-300"> + {{ item.type }} + </span> + </div> + <p + class="text-emerald-700 dark:text-emerald-300 text-sm whitespace-pre-line break-words overflow-wrap-anywhere"> + {{ item.value }} + </p> + </div> + </div> + </div> + </div> + <div class="mt-3 text-xs text-gray-500 dark:text-gray-400"> + Total descriptions: {{ dataset.descriptions.length }} + </div> + </div> + </CardBox> - + <!-- (7) authors --> + <CardBox class="mb-6 shadow" has-table title="Creators" :icon="mdiBookOpenPageVariant" + :show-header-icon="false"> + <div v-if="dataset.authors.length === 0" class="text-center py-6"> + <p class="text-gray-500 dark:text-gray-400 italic">No authors defined</p> + </div> + <div v-else class="p-4"> + <!-- <h4 class="text-sm font-medium text-gray-700 dark:text-gray-300 mb-3">Dataset Authors:</h4> --> + <div class="grid gap-3"> + <div v-for="(author, index) in dataset.authors" :key="index" class="bg-emerald-50 dark:bg-emerald-900/30 border border-emerald-200 dark:border-emerald-800 + rounded-lg p-3 shadow-sm hover:bg-emerald-100 dark:hover:bg-emerald-900/50 transition-colors"> + <div class="flex flex-col md:flex-row md:items-center"> + <div class="flex-1"> + <p class="font-medium text-emerald-700 dark:text-emerald-300"> + {{ author.academic_title }} {{ author.first_name }} {{ author.last_name + }} + </p> + <div class="mt-2 grid grid-cols-1 md:grid-cols-2 gap-2"> + <div v-if="author.email" class="flex items-center text-sm"> + <IconSvg path="email" :size="16" + className="mr-1 text-emerald-600 dark:text-emerald-400" /> + <span class="text-emerald-600 dark:text-emerald-400">{{ author.email + }}</span> + </div> + <div v-if="author.identifier_orcid" class="flex items-center text-sm"> + <IconSvg path="idCard" :size="16" + className="mr-1 text-emerald-600 dark:text-emerald-400"> + </IconSvg> + <span class="text-emerald-600 dark:text-emerald-400">ORCID: {{ + author.identifier_orcid + }}</span> + </div> + </div> + </div> + <div v-if="author.academic_title" class="mt-2 md:mt-0 md:ml-4"> + <span class="bg-emerald-200 dark:bg-emerald-800 text-emerald-800 dark:text-emerald-200 + text-xs px-2 py-1 rounded-full"> + {{ author.academic_title }} + </span> + </div> + </div> + </div> + </div> + <div v-if="dataset.authors.length > 0" class="mt-3 text-xs text-gray-500 dark:text-gray-400"> + Total authors: {{ dataset.authors.length }} + </div> + </div> + </CardBox> - <template #footer> - <BaseButtons> - <!-- <BaseButton type="submit" color="info" label="Receive" + <!-- (8) contributors --> + <CardBox class="mb-6 shadow" has-table title="Contributors" :icon="mdiBookOpenPageVariant" + :show-header-icon="false"> + <div v-if="dataset.contributors.length === 0" class="text-center py-6"> + <p class="text-gray-500 dark:text-gray-400 italic">No contributors defined</p> + </div> + <div v-else class="p-4"> + <!-- <h4 class="text-sm font-medium text-gray-700 dark:text-gray-300 mb-3">Dataset Contributors: + </h4> --> + <div class="grid gap-3"> + <div v-for="(contributor, index) in dataset.contributors" :key="index" class="bg-emerald-50 dark:bg-emerald-900/30 border border-emerald-200 dark:border-emerald-800 + rounded-lg p-3 shadow-sm hover:bg-emerald-100 dark:hover:bg-emerald-900/50 transition-colors"> + <div class="flex flex-col md:flex-row md:items-center"> + <div class="flex-1"> + <div class="flex flex-wrap items-center gap-2"> + <p class="font-medium text-emerald-700 dark:text-emerald-300"> + {{ contributor.academic_title }} {{ contributor.first_name }} {{ + contributor.last_name + }} + </p> + <span v-if="contributor.pivot_contributor_type" class="bg-emerald-200 dark:bg-emerald-800 text-emerald-800 dark:text-emerald-200 + text-xs px-2 py-1 rounded-full"> + {{ contributor.pivot_contributor_type }} + </span> + </div> + <div class="mt-2 grid grid-cols-1 md:grid-cols-2 gap-2"> + <div v-if="contributor.email" class="flex items-center text-sm"> + <IconSvg path="email" :size="16" + className="mr-1 text-emerald-600 dark:text-emerald-400" /> + <span class="text-emerald-600 dark:text-emerald-400">{{ + contributor.email }}</span> + </div> + <div v-if="contributor.identifier_orcid" class="flex items-center text-sm"> + <IconSvg path="idCard" :size="16" + className="mr-1 text-emerald-600 dark:text-emerald-400"> + </IconSvg> + <span class="text-emerald-600 dark:text-emerald-400">ORCID: {{ + contributor.identifier_orcid }}</span> + </div> + </div> + </div> + <div v-if="contributor.academic_title" class="mt-2 md:mt-0 md:ml-4"> + <span class="bg-emerald-200 dark:bg-emerald-800 text-emerald-800 dark:text-emerald-200 + text-xs px-2 py-1 rounded-full"> + {{ contributor.academic_title }} + </span> + </div> + </div> + </div> + </div> + <div v-if="dataset.contributors.length > 0" + class="mt-3 text-xs text-gray-500 dark:text-gray-400"> + Total contributors: {{ dataset.contributors.length }} + </div> + </div> + </CardBox> + + + <!-- Map component --> + <CardBoxSimple> + <h4 class="text-sm font-medium text-gray-700 dark:text-gray-300 mb-3">Geographic Coverage</h4> + <!-- Map container with emerald styling --> + <div class="bg-emerald-50 dark:bg-emerald-900/30 border border-emerald-200 dark:border-emerald-800 + rounded-lg shadow-sm overflow-hidden"> + <!-- The actual map component --> + <div class="h-64 rounded-md overflow-hidden"> + <!-- Use the simplified map component --> + <MapComponentView v-if="dataset.coverage" :coverage="dataset.coverage" height="250px" + :mapId="'dataset-review-map'" /> + </div> + <!-- Optional: Add a caption or description --> + <div class="mt-2 text-xs text-emerald-600 dark:text-emerald-400 text-center"> + Geographic extent of the dataset + </div> + </div> + <!-- Coordinates display below the map --> + <div class="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-4 gap-3 mt-3"> + <!-- x min --> + <div> + <label class="block text-xs font-medium text-gray-600 dark:text-gray-400 mb-1">X Min + (Longitude)</label> + <div class="bg-emerald-50 dark:bg-emerald-900/30 border border-emerald-200 dark:border-emerald-800 + rounded-lg p-2.5 shadow-sm"> + <span class="text-emerald-700 dark:text-emerald-300"> + {{ dataset.coverage.x_min }} + </span> + </div> + </div> + + <!-- x max --> + <div> + <label class="block text-xs font-medium text-gray-600 dark:text-gray-400 mb-1">X Max + (Longitude)</label> + <div class="bg-emerald-50 dark:bg-emerald-900/30 border border-emerald-200 dark:border-emerald-800 + rounded-lg p-2.5 shadow-sm"> + <span class="text-emerald-700 dark:text-emerald-300"> + {{ dataset.coverage.x_max }} + </span> + </div> + </div> + + <!-- y min --> + <div> + <label class="block text-xs font-medium text-gray-600 dark:text-gray-400 mb-1">Y Min + (Latitude)</label> + <div class="bg-emerald-50 dark:bg-emerald-900/30 border border-emerald-200 dark:border-emerald-800 + rounded-lg p-2.5 shadow-sm"> + <span class="text-emerald-700 dark:text-emerald-300"> + {{ dataset.coverage.y_min }} + </span> + </div> + </div> + + <!-- y max --> + <div> + <label class="block text-xs font-medium text-gray-600 dark:text-gray-400 mb-1">Y Max + (Latitude)</label> + <div class="bg-emerald-50 dark:bg-emerald-900/30 border border-emerald-200 dark:border-emerald-800 + rounded-lg p-2.5 shadow-sm"> + <span class="text-emerald-700 dark:text-emerald-300"> + {{ dataset.coverage.y_max }} + </span> + </div> + </div> + </div> + </CardBoxSimple> + + <!-- References --> + <CardBoxSimple> + <div v-if="dataset.references.length === 0" class="text-center py-6"> + <p class="text-gray-500 dark:text-gray-400 italic">No references added.</p> + </div> + <div v-else class="p-4"> + <h4 class="text-sm font-medium text-gray-700 dark:text-gray-300 mb-3">Dataset References: + </h4> + <div class="grid gap-3"> + <div v-for="(item, index) in dataset.references" :key="index" class="bg-emerald-50 dark:bg-emerald-900/30 border border-emerald-200 dark:border-emerald-800 + rounded-lg p-3 shadow-sm hover:bg-emerald-100 dark:hover:bg-emerald-900/50 transition-colors"> + <div class="flex flex-col md:flex-row md:items-center md:justify-between"> + <div class="flex-1"> + <p class="font-medium text-emerald-700 dark:text-emerald-300">{{ item.value + }}</p> + <p class="text-sm text-emerald-600 dark:text-emerald-400 mt-1">{{ item.label + }}</p> + </div> + <div class="flex mt-2 md:mt-0 space-x-2"> + <span class="bg-emerald-200 dark:bg-emerald-800 text-emerald-800 dark:text-emerald-200 + text-xs px-2 py-1 rounded-full"> + {{ item.type }} + </span> + <span class="bg-emerald-200 dark:bg-emerald-800 text-emerald-800 dark:text-emerald-200 + text-xs px-2 py-1 rounded-full"> + {{ item.relation }} + </span> + </div> + </div> + </div> + </div> + <div v-if="dataset.references.length > 0" class="mt-3 text-xs text-gray-500 dark:text-gray-400"> + Total references: {{ dataset.references.length }} + </div> + </div> + </CardBoxSimple> + + + + <!-- Keywords --> + <CardBoxSimple> + <div v-if="dataset.subjects.length === 0" class="text-center py-6"> + <p class="text-gray-500 dark:text-gray-400 italic">No keywords added.</p> + </div> + <div v-else class="p-4"> + <h4 class="text-sm font-medium text-gray-700 dark:text-gray-300 mb-3">Keywords/Subjects: + </h4> + <div class="flex flex-wrap gap-2"> + <div v-for="(subject, index) in dataset.subjects" :key="index" class="bg-emerald-50 dark:bg-emerald-900/30 text-emerald-700 dark:text-emerald-300 + px-3 py-1.5 rounded-full text-sm font-medium border border-emerald-200 + dark:border-emerald-800 shadow-sm hover:bg-emerald-100 + dark:hover:bg-emerald-900/50 transition-colors"> + <span>{{ subject.value }}</span> + <span class="ml-1 text-xs text-emerald-600 dark:text-emerald-400">({{ subject.type + }})</span> + </div> + </div> + <div v-if="dataset.subjects.length > 0" class="mt-3 text-xs text-gray-500 dark:text-gray-400"> + Total keywords: {{ dataset.subjects.length }} + </div> + </div> + </CardBoxSimple> + + + <!-- download file list --> + <CardBoxSimple> + <h4 class="text-sm font-medium text-gray-700 dark:text-gray-300 mb-3">Dataset Files</h4> + <div v-if="dataset.files && dataset.files.length > 0" class="space-y-2"> + <div v-for="file in dataset.files" :key="file.id" class="bg-emerald-50 dark:bg-emerald-900/30 border border-emerald-200 dark:border-emerald-800 + rounded-lg p-3 shadow-sm hover:bg-emerald-100 dark:hover:bg-emerald-900/50 transition-colors"> + <div class="flex items-center justify-between"> + <div class="flex items-center space-x-3 flex-1"> + <div class="flex-shrink-0"> + <svg class="h-6 w-6 text-emerald-600 dark:text-emerald-400" + xmlns="http://www.w3.org/2000/svg" fill="none" viewBox="0 0 24 24" + stroke="currentColor"> + <path stroke-linecap="round" stroke-linejoin="round" stroke-width="2" + d="M9 12h6m-6 4h6m2 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z" /> + </svg> + </div> + <div class="min-w-0 flex-1"> + <p class="text-sm font-medium text-emerald-700 dark:text-emerald-300 truncate"> + {{ file.label }} + </p> + <p class="text-xs text-emerald-600/70 dark:text-emerald-400/70 truncate"> + {{ getFileSize(file) }} + </p> + </div> + </div> + <div class="ml-2 flex-shrink-0"> + <a v-if="file.id != undefined" + :href="stardust.route('reviewer.file.download', [file.id])" class="inline-flex items-center px-3 py-1.5 border border-emerald-300 dark:border-emerald-700 + text-xs font-medium rounded-full text-emerald-700 bg-emerald-100 + dark:text-emerald-200 dark:bg-emerald-800/70 hover:bg-emerald-200 + dark:hover:bg-emerald-800 transition-colors"> + <IconSvg path="download" :size="20" className="mr-1" /> + Download + </a> + </div> + </div> + </div> + </div> + <div v-else + class="text-center py-6 bg-emerald-50/50 dark:bg-emerald-900/10 rounded-lg border border-emerald-100 dark:border-emerald-900/30"> + <svg xmlns="http://www.w3.org/2000/svg" + class="h-12 w-12 mx-auto text-emerald-300 dark:text-emerald-700" fill="none" + viewBox="0 0 24 24" stroke="currentColor"> + <path stroke-linecap="round" stroke-linejoin="round" stroke-width="1.5" + d="M9 13h6m-3-3v6m5 5H7a2 2 0 01-2-2V5a2 2 0 012-2h5.586a1 1 0 01.707.293l5.414 5.414a1 1 0 01.293.707V19a2 2 0 01-2 2z" /> + </svg> + <p class="mt-2 text-emerald-600 dark:text-emerald-400 italic">No files attached to this dataset + </p> + </div> + <div v-if="dataset.files && dataset.files.length > 0" + class="mt-3 text-xs text-gray-500 dark:text-gray-400"> + Total files: {{ dataset.files.length }} + </div> + </CardBoxSimple> + + + + <BaseButtons> + <!-- <BaseButton type="submit" color="info" label="Receive" :class="{ 'opacity-25': router.processing }" :disabled="form.processing" /> --> - <BaseButton type="submit" color="info" label="Review" /> - </BaseButtons> - </template> - </CardBox> + <BaseButton v-if="can.reject && (dataset.server_state == 'approved' || dataset.server_state == 'rejected_to_reviewer')" type="submit" color="info" label="Accept" small /> + + <BaseButton + v-if="can.reject && (dataset.server_state == 'approved' || dataset.server_state == 'rejected_to_reviewer')" + :route-name="stardust.route('reviewer.dataset.reject', [dataset.id])" color="info" + :icon="mdiReiterate" :label="'Reject'" small /> + </BaseButtons> + + </component> </SectionMain> </LayoutAuthenticated> </template> + +<style scoped> +.break-words { + word-break: break-word; +} + +.overflow-wrap-anywhere { + overflow-wrap: anywhere; +} +</style> \ No newline at end of file diff --git a/resources/js/Pages/Submitter/Dataset/Category.vue b/resources/js/Pages/Submitter/Dataset/Category.vue index 9b3e6b1..d9957fb 100644 --- a/resources/js/Pages/Submitter/Dataset/Category.vue +++ b/resources/js/Pages/Submitter/Dataset/Category.vue @@ -1,6 +1,7 @@ <template> <LayoutAuthenticated> - <Head title="Collections"></Head> + + <Head title="Classify"></Head> <SectionMain> <SectionTitleLineWithButton :icon="mdiLibraryShelves" title="Library Classification" main> <div class="bg-lime-100 shadow rounded-lg p-6 mb-6 flex items-center justify-between"> @@ -33,29 +34,30 @@ </h2> <ul class="flex flex-wrap gap-2"> <li v-for="col in collections" :key="col.id" :class="{ - 'cursor-pointer p-2 border border-gray-200 rounded hover:bg-sky-50 text-sky-700 text-sm': true, + 'cursor-pointer p-2 border border-gray-200 rounded hover:bg-sky-50 flex items-center': true, 'bg-sky-100 border-sky-500': selectedToplevelCollection && selectedToplevelCollection.id === col.id }" @click="onToplevelCollectionSelected(col)"> - {{ `${col.name} (${col.number})` }} + <span class="text-sky-700">{{ col.name }}</span> + <span class="ml-2 px-2 py-0.5 bg-gray-200 text-gray-700 text-xs rounded-full">{{ col.number }}</span> </li> <li v-if="collections.length === 0" class="text-gray-800 dark:text-slate-400"> No collections available. </li> </ul> </CardBox> - <!-- Collections Listing --> <div class="grid grid-cols-1 md:grid-cols-3 gap-4 mb-4"> <!-- Broader Collection (Parent) --> <CardBox v-if="selectedCollection" class="rounded-lg p-4" has-form-data> - <h2 class="text-lg font-bold text-gray-800 dark:text-slate-400 mb-2">Broader Collection</h2> + <h2 class="text-lg font-bold text-gray-800 dark:text-slate-400 mb-2">Broader Collection</h2> <draggable v-if="broaderCollections.length > 0" v-model="broaderCollections" :group="{ name: 'collections' }" tag="ul" class="flex flex-wrap gap-2 max-h-60 overflow-y-auto"> <template #item="{ element: parent }"> <li :key="parent.id" :draggable="!parent.inUse" :class="getChildClasses(parent)" @click="onCollectionSelected(parent)"> - {{ `${parent.name} (${parent.number})` }} + <span class="text-sky-700">{{ parent.name }}</span> + <span class="ml-2 px-2 py-0.5 bg-gray-200 text-gray-700 text-xs rounded-full">{{ parent.number }}</span> </li> </template> </draggable> @@ -69,23 +71,35 @@ <!-- Selected Collection Details --> <CardBox v-if="selectedCollection" class="rounded-lg p-4" has-form-data> <h3 class="text-xl font-bold text-gray-800 dark:text-slate-400 mb-2">Selected Collection</h3> - <p :class="[ + <!-- <p :class="[ 'cursor-pointer p-2 border border-gray-200 rounded text-sm', selectedCollection.inUse ? 'bg-gray-200 text-gray-500 drag-none' : 'bg-green-50 text-green-700 hover:bg-green-100 hover:underline cursor-move' - ]"> - {{ `${selectedCollection.name} (${selectedCollection.number})` }} - </p> + ]"></p> --> + <draggable v-model="selectedCollectionArray" + :group="{ name: 'collections', pull: 'clone', put: false }" tag="ul" + class="flex flex-wrap gap-2 max-h-60 overflow-y-auto"> + <template #item="{ element }"> + <li :key="element.id" :class="[ + 'p-2 border border-gray-200 rounded text-sm', + element.inUse ? 'bg-gray-200 text-gray-500 drag-none' : 'bg-green-50 text-green-700 hover:bg-green-100 hover:underline cursor-move' + ]"> + <span class="text-sky-700">{{ element.name }}</span> + <span class="ml-2 px-2 py-0.5 bg-gray-200 text-gray-700 text-xs rounded-full">{{ element.number }}</span> + </li> + </template> + </draggable> </CardBox> - + <!-- Narrower Collections (Children) --> <CardBox v-if="selectedCollection" class="rounded-lg p-4" has-form-data> - <h2 class="text-lg font-bold text-gray-800 dark:text-slate-400 mb-2">Narrower Collections</h2> + <h2 class="text-lg font-bold text-gray-800 dark:text-slate-400 mb-2">Narrower Collections</h2> <draggable v-if="narrowerCollections.length > 0" v-model="narrowerCollections" :group="{ name: 'collections' }" tag="ul" class="flex flex-wrap gap-2 max-h-60 overflow-y-auto"> <template #item="{ element: child }"> <li :key="child.id" :draggable="!child.inUse" :class="getChildClasses(child)" @click="onCollectionSelected(child)"> - {{ `${child.name} (${child.number})` }} + <span class="text-sky-700">{{ child.name }}</span> + <span class="ml-2 px-2 py-0.5 bg-gray-200 text-gray-700 text-xs rounded-full">{{ child.number }}</span> </li> </template> </draggable> @@ -99,19 +113,21 @@ </div> <div class="mb-4 rounded-lg"> - <div v-if="selectedCollection || selectedCollectionList.length > 0" class="bg-gray-100 shadow rounded-lg p-6 mb-6" :class="{ 'opacity-50': selectedCollection && selectedCollectionList.length === 0 }"> + <div v-if="selectedCollection || selectedCollectionList.length > 0" + class="bg-gray-100 shadow rounded-lg p-6 mb-6" + :class="{ 'opacity-50': selectedCollection && selectedCollectionList.length === 0 }"> <p class="mb-4 text-gray-700">Please drag your collections here to classify your previously created dataset according to library classification standards.</p> <draggable v-model="selectedCollectionList" :group="{ name: 'collections' }" class="min-h-36 border-dashed border-2 border-gray-400 p-4 text-sm flex flex-wrap gap-2 max-h-60 overflow-y-auto" - tag="ul" - :disabled="selectedCollection === null && selectedCollectionList.length > 0" + tag="ul" :disabled="selectedCollection === null && selectedCollectionList.length > 0" :style="{ opacity: (selectedCollection === null && selectedCollectionList.length > 0) ? 0.5 : 1, pointerEvents: (selectedCollection === null && selectedCollectionList.length > 0) ? 'none' : 'auto' }"> <template #item="{ element }"> <div :key="element.id" class="p-2 m-1 bg-sky-200 text-sky-800 rounded flex items-center gap-2 h-7"> - <span>{{ element.name }} ({{ element.number }})</span> + <span class="text-sky-700">{{ element.name }}</span> + <span class="ml-2 px-2 py-0.5 bg-gray-200 text-gray-700 text-xs rounded-full">{{ element.number }}</span> <button @click="selectedCollectionList = selectedCollectionList.filter(item => item.id !== element.id)" class="hover:text-sky-600 flex items-center"> @@ -124,7 +140,7 @@ </button> </div> </template> - </draggable> + </draggable> </div> </div> <div class="p-6 border-t border-gray-100 dark:border-slate-800"> @@ -189,6 +205,16 @@ const broaderCollections = ref<Collection[]>([]); // Reactive list that holds collections dropped by the user const selectedCollectionList: Ref<Collection[]> = ref<Collection[]>([]); + +// Wrap selectedCollection in an array for draggable (always expects an array) +const selectedCollectionArray = computed({ + get: () => (selectedCollection.value ? [selectedCollection.value] : []), + set: (value: Collection[]) => { + selectedCollection.value = value.length ? value[0] : null + } +}) + + const form = useForm({ collections: [] as number[], }); @@ -277,6 +303,12 @@ const fetchCollections = async (collectionId: number) => { const alreadyDropped = selectedCollectionList.value.find(dc => dc.id === collection.id); return alreadyDropped ? { ...collection, inUse: true } : { ...collection, inUse: false }; }); + // Check if selected collection is in the selected list + if (selectedCollection.value && selectedCollectionList.value.find(dc => dc.id === selectedCollection.value?.id)) { + selectedCollection.value = { ...selectedCollection.value, inUse: true }; + } else if (selectedCollection.value) { + selectedCollection.value = { ...selectedCollection.value, inUse: false }; + } } catch (error) { console.error('Error in fetchCollections:', error); } diff --git a/resources/js/Pages/Submitter/Dataset/Create.vue b/resources/js/Pages/Submitter/Dataset/Create.vue index 934c320..40c25ab 100644 --- a/resources/js/Pages/Submitter/Dataset/Create.vue +++ b/resources/js/Pages/Submitter/Dataset/Create.vue @@ -24,7 +24,6 @@ import FormControl from '@/Components/FormControl.vue'; import FormCheckRadioGroup from '@/Components/FormCheckRadioGroup.vue'; import BaseButton from '@/Components/BaseButton.vue'; import { stardust } from '@eidellev/adonis-stardust/client'; -// import { Inertia } from '@inertiajs/inertia'; import CardBoxModal from '@/Components/CardBoxModal.vue'; import BaseIcon from '@/Components/BaseIcon.vue'; @@ -98,23 +97,23 @@ const flash: ComputedRef<any> = computed(() => { // Computed property to determine the placeholder based on the selected option const getPlaceholder = computed(() => (type: string) => { - + switch (type) { - case 'DOI': - return 'https://doi.org/10.24341/tethys.236'; - case 'Handle': - return '20.500.12345/67890'; - case 'ISBN': - return '978-3-85316-076-3'; - case 'ISSN': - return '1234-5678'; - case 'URL': - return 'https://example.com'; - case 'URN': - return 'urn:nbn:de:1234-5678'; - default: - return '[VALUE]'; - } + case 'DOI': + return 'https://doi.org/10.24341/tethys.236'; + case 'Handle': + return '20.500.12345/67890'; + case 'ISBN': + return '978-3-85316-076-3'; + case 'ISSN': + return '1234-5678'; + case 'URL': + return 'https://example.com'; + case 'URN': + return 'urn:nbn:de:1234-5678'; + default: + return '[VALUE]'; + } }); const mainService = MainService(); @@ -221,15 +220,6 @@ if (Object.keys(mainService.dataset).length == 0) { // descriptions: [{ value: '', type: 'Abstract', language: language }], // }); let form = useForm<Dataset>(dataset as Dataset); -// form.defaults(); - -// const emit = defineEmits(['update:modelValue', 'setRef']); -// computed({ -// get: () => form.rights, -// set: (value) => { -// emit('update:modelValue', value); -// }, -// }); watch(language, (currentValue) => { if (currentValue != "") { @@ -320,12 +310,17 @@ const nextStep = async () => { } else if (formStep.value == 3) { route = stardust.route('dataset.third.step'); } - // formStep.value++; + // When posting in steps 1-3, remove any file uploads from the data. await form - .transform((data) => ({ - ...data, - rights: form.rights && form.rights == true ? 'true' : 'false', - })) + .transform((data: Dataset) => { + // Create payload and set rights (transforming to a string if needed) + const payload: any = { ...data, rights: data.rights ? 'true' : 'false' }; + // Remove the files property so that the partial update is done without files + if (payload.files) { + delete payload.files; + } + return payload; + }) .post(route, { onSuccess: () => { // console.log(form.data()); @@ -334,7 +329,6 @@ const nextStep = async () => { }, }); }; - const prevStep = () => { formStep.value--; }; @@ -343,7 +337,7 @@ const submit = async () => { let route = stardust.route('dataset.submit'); const files = form.files.map((obj) => { - return new File([obj.blob], obj.label, { type: obj.type, lastModified: obj.lastModified }); + return new File([obj.blob], obj.label, { type: obj.type, lastModified: obj.lastModified, sort_order: obj.sort_order }); }); // formStep.value++; @@ -440,6 +434,12 @@ const onAddAuthor = (person: Person) => { notify({ type: 'info', text: 'person has been successfully added as author' }); } }; + +const addNewContributor = () => { + let newContributor = { status: false, first_name: '', last_name: '', email: '', academic_title: '', identifier_orcid: '', name_type: 'Personal', pivot: { contributor_type: '' } }; + form.contributors.push(newContributor); +}; + const onAddContributor = (person: Person) => { if (form.contributors.filter((e) => e.id === person.id).length > 0) { notify({ type: 'warning', title: 'Warning', text: 'person is already defined as contributor' }, 4000); @@ -462,7 +462,7 @@ const onMapInitialized = (newItem: any) => { adds a new Keyword */ const addKeyword = () => { - let newSubject: Subject = { value: 'test', language: '', type: 'uncontrolled' }; + let newSubject: Subject = { value: '', language: '', type: 'uncontrolled' }; //this.dataset.files.push(uploadedFiles[i]); form.subjects.push(newSubject); }; @@ -499,16 +499,25 @@ Removes a selected keyword <template> <CardBoxModal v-model="isModalActive" title="Einverständniserklärung *"> - Mit dem Setzen des Hakens bestätige ich hiermit - <ul class="list-decimal"> + <p class="mb-4 text-gray-700"> + Mit dem Setzen des Hakens bestätige ich hiermit folgende Punkte: + </p> + <ul class="list-decimal pl-6 space-y-2 text-sm text-gray-600"> <li> - die Data Policy von Tethys RDR sowie die Terms & Conditions von Tethys gelesen und verstanden zu haben - (<a href="/docs/HandbuchTethys.pdf" target="_blank">siehe hier</a>) + die Data Policy von Tethys RDR sowie die + <a href="/docs/HandbuchTethys.pdf" target="_blank" + class="font-medium text-blue-600 hover:text-blue-800 transition-colors underline"> + Terms & Conditions + </a> + von Tethys gelesen und verstanden zu haben. </li> - <li>das Einverständnis aller Co-Autoren über die bevorstehende Datenpublikation schriftlich eingeholt zu - haben + <li> + das Einverständnis aller Co-Autoren über die bevorstehende Datenpublikation schriftlich eingeholt zu + haben. + </li> + <li> + sowohl mit der Data Policy als auch mit den Terms & Conditions einverstanden zu sein. </li> - <li>sowohl mit der Data Policy als auch mit den Terms & Conditions einverstanden zu sein</li> </ul> </CardBoxModal> @@ -531,15 +540,15 @@ Removes a selected keyword <div class="flex items-center"> <!-- <label>{{ form.titles[0].language }}</label> <label>{{ form.language }}</label> --> - <icon-wizard :is-current="formStep == 1" :is-checked="formStep > 1" :label="'Language'"> + <icon-wizard :is-current="formStep == 1" :is-checked="formStep > 1" :label="'Step 1'"> <icon-language></icon-language> </icon-wizard> - <icon-wizard :is-current="formStep == 2" :is-checked="formStep > 2" :label="'Mandatory'"> + <icon-wizard :is-current="formStep == 2" :is-checked="formStep > 2" :label="'Step 2'"> <icon-mandatory></icon-mandatory> </icon-wizard> - <icon-wizard :is-current="formStep == 3" :is-checked="formStep > 3" :label="'Recommended'"> + <icon-wizard :is-current="formStep == 3" :is-checked="formStep > 3" :label="'Step 3'"> <icon-recommendet></icon-recommendet> </icon-wizard> @@ -567,7 +576,7 @@ Removes a selected keyword <FormField label="Licenses" wrap-body :class="{ 'text-red-400': form.errors.licenses }" class="mt-8 w-full mx-2 flex-1"> - <FormCheckRadioGroup v-model="form.licenses" name="roles" is-column + <FormCheckRadioGroup type="radio" v-model="form.licenses" name="licenses" is-column :options="props.licenses" /> </FormField> @@ -575,8 +584,10 @@ Removes a selected keyword <input class="form-checkbox" name="rights" id="rights" type="checkbox" v-model="dataset.rights" /> terms and conditions </label> --> - <FormField label="Rights" help="You must agree to continue" wrap-body - :class="{ 'text-red-400': form.errors.rights }" class="mt-8 w-full mx-2 flex-1 flex-col"> + <FormField label="Rights" + help="You must agree that you have read the Terms and Conditions. Please click on the 'i' icon to find a read the policy" + wrap-body :class="{ 'text-red-400': form.errors.rights }" + class="mt-8 w-full mx-2 flex-1 flex-col"> <label for="rights" class="checkbox mr-6 mb-3 last:mr-0"> <input type="checkbox" id="rights" required v-model="form.rights" /> <span class="check" /> @@ -662,7 +673,7 @@ Removes a selected keyword <FormField label="Title Value *" :class="{ 'text-red-400': form.errors[`titles.${index}.value`] }" class="w-full mx-2 flex-1"> - <FormControl required v-model="form.titles[index].value" type="text" + <FormControl required v-model="form.titles[index].value" type="textarea" placeholder="[enter main title]"> <div class="text-red-400 text-sm" v-if="form.errors[`titles.${index}.value`]"> @@ -738,7 +749,7 @@ Removes a selected keyword <FormField label="Description Value *" :class="{ 'text-red-400': form.errors[`descriptions.${index}.value`] }" class="w-full mx-2 flex-1"> - <FormControl required v-model="form.descriptions[index].value" type="text" + <FormControl required v-model="form.descriptions[index].value" type="textarea" placeholder="[enter additional description]" :show-char-count="true" :max-input-length="2500"> <div class="text-red-400 text-sm" v-if="form.errors[`descriptions.${index}.value`] && @@ -778,14 +789,14 @@ Removes a selected keyword </CardBox> <!-- authors --> - <CardBox class="mb-6 shadow" has-table title="Creators" :icon="mdiBookOpenPageVariant"> + <CardBox class="mb-6 shadow" has-table title="Creators" :icon="mdiBookOpenPageVariant" :show-header-icon="false"> <SearchAutocomplete source="/api/persons" :response-property="'first_name'" placeholder="search in person table...." v-on:person="onAddAuthor"></SearchAutocomplete> <TablePersons :errors="form.errors" :persons="form.authors" :relation="'authors'" v-if="form.authors.length > 0" /> - <div class="text-red-400 text-sm" v-if="errors.authors && Array.isArray(errors.authors)"> - {{ errors.authors.join(', ') }} + <div class="text-red-400 text-sm" v-if="form.errors.authors && Array.isArray(form.errors.authors)"> + {{ form.errors.authors.join(', ') }} </div> <div class="w-full md:w-1/2"> <label class="block" for="additionalCreators">Add additional creator(s) if creator is @@ -796,7 +807,7 @@ Removes a selected keyword </CardBox> <!-- contributors --> - <CardBox class="mb-6 shadow" has-table title="Contributors" :icon="mdiBookOpenPageVariant"> + <CardBox class="mb-6 shadow" has-table title="Contributors" :icon="mdiBookOpenPageVariant" :show-header-icon="false"> <SearchAutocomplete source="/api/persons" :response-property="'first_name'" placeholder="search in person table...." v-on:person="onAddContributor"> </SearchAutocomplete> @@ -808,6 +819,12 @@ Removes a selected keyword v-if="form.errors.contributors && Array.isArray(form.errors.contributors)"> {{ form.errors.contributors.join(', ') }} </div> + <div class="w-full md:w-1/2"> + <label class="block" for="additionalCreators">Add additional contributor(s) if + contributor is not in database</label> + <button class="bg-blue-500 text-white py-2 px-4 rounded-sm" + @click.prevent="addNewContributor()">+</button> + </div> </CardBox> </div> @@ -834,7 +851,7 @@ Removes a selected keyword </FormControl> </FormField> </div> - <CardBox class="mb-6 shadow" has-table title="Geo Location" :icon="mdiEarthPlus"> + <CardBox class="mb-6 shadow" has-table title="Geo Location" :icon="mdiEarthPlus" :show-header-icon="false"> <!-- @onMapInitialized="onMapInitialized" --> <!-- v-bind-event="{ mapId, name: mapId }" --> <MapComponent :mapOptions="mapOptions" :baseMaps="baseMaps" :fitBounds="fitBounds" @@ -892,9 +909,9 @@ Removes a selected keyword </div> </CardBox> - <CardBox class="mb-6 shadow" has-table title="Coverage Information" :icon="mdiEarthPlus"> + <CardBox class="mb-6 shadow" has-table title="Coverage Information" :icon="mdiEarthPlus" :show-header-icon="false"> <!-- elevation menu --> - <div class="flex flex-col md:flex-row mb-3 space-y-2 md:space-y-0 md:space-x-4"> + <div class="flex flex-col md:flex-row mb-3 space-y-2 md:space-y-0 md:space-x-4"> <label for="elevation-option-one" class="pure-radio mb-2 md:mb-0"> <input id="elevation-option-one" type="radio" v-model="elevation" value="absolut" /> absolut elevation (m) @@ -1071,7 +1088,8 @@ Removes a selected keyword <!-- <input name="Reference Value" class="form-control" placeholder="[VALUE]" v-model="item.value" /> --> <FormControl required v-model="item.value" :type="'text'" - :placeholder="getPlaceholder(form.references[index].type)" :errors="form.errors.embargo_date"> + :placeholder="getPlaceholder(form.references[index].type)" + :errors="form.errors.embargo_date"> <div class="text-red-400 text-sm" v-if="form.errors[`references.${index}.value`] && Array.isArray(form.errors[`references.${index}.value`])"> {{ form.errors[`references.${index}.value`].join(', ') }} diff --git a/resources/js/Pages/Submitter/Dataset/Edit.vue b/resources/js/Pages/Submitter/Dataset/Edit.vue index 9f3c395..ff885c1 100644 --- a/resources/js/Pages/Submitter/Dataset/Edit.vue +++ b/resources/js/Pages/Submitter/Dataset/Edit.vue @@ -42,7 +42,8 @@ <!-- (2) licenses --> <FormField label="Licenses" wrap-body :class="{ 'text-red-400': form.errors.licenses }" class="mt-8 w-full mx-2 flex-1"> - <FormCheckRadioGroup v-model="form.licenses" name="licenses" is-column :options="licenses" /> + <FormCheckRadioGroup type="radio" v-model="form.licenses" name="licenses" is-column + :options="licenses" /> </FormField> <div class="flex flex-col md:flex-row"> @@ -78,7 +79,7 @@ <div class="flex flex-col md:flex-row"> <FormField label="Main Title *" help="required: main title" :class="{ 'text-red-400': form.errors['titles.0.value'] }" class="w-full mr-1 flex-1"> - <FormControl required v-model="form.titles[0].value" type="text" + <FormControl required v-model="form.titles[0].value" type="textarea" placeholder="[enter main title]" :show-char-count="true" :max-input-length="255"> <div class="text-red-400 text-sm" v-if="form.errors['titles.0.value'] && Array.isArray(form.errors['titles.0.value'])"> @@ -116,7 +117,7 @@ <tr v-if="title.type != 'Main'"> <!-- <td scope="row">{{ index + 1 }}</td> --> <td data-label="Title Value"> - <FormControl required v-model="form.titles[index].value" type="text" + <FormControl required v-model="form.titles[index].value" type="textarea" placeholder="[enter main title]"> <div class="text-red-400 text-sm" v-if="form.errors[`titles.${index}.value`]"> @@ -163,7 +164,8 @@ :class="{ 'text-red-400': form.errors['descriptions.0.value'] }" class="w-full mr-1 flex-1"> <FormControl required v-model="form.descriptions[0].value" type="textarea" - placeholder="[enter main abstract]" :show-char-count="true" :max-input-length="2500"> + placeholder="[enter main abstract]" :show-char-count="true" + :max-input-length="2500"> <div class="text-red-400 text-sm" v-if="form.errors['descriptions.0.value'] && Array.isArray(form.errors['descriptions.0.value'])"> {{ form.errors['descriptions.0.value'].join(', ') }} @@ -176,7 +178,7 @@ <FormControl required v-model="form.descriptions[0].language" type="text" :is-read-only="true"> <div class="text-red-400 text-sm" v-if="form.errors['descriptions.0.value'] && Array.isArray(form.errors['descriptions.0.language']) - "> + "> {{ form.errors['descriptions.0.language'].join(', ') }} </div> </FormControl> @@ -197,7 +199,7 @@ <tr v-if="item.type != 'Abstract'"> <!-- <td scope="row">{{ index + 1 }}</td> --> <td data-label="Description Value"> - <FormControl required v-model="form.descriptions[index].value" type="text" + <FormControl required v-model="form.descriptions[index].value" type="textarea" placeholder="[enter main title]"> <div class="text-red-400 text-sm" v-if="form.errors[`descriptions.${index}.value`]"> @@ -239,19 +241,23 @@ </CardBox> <!-- (7) authors --> - <CardBox class="mb-6 shadow" has-table title="Creators" :icon="mdiBookOpenPageVariant"> + <CardBox class="mb-6 shadow" has-table title="Creators" :icon="mdiBookOpenPageVariant" + :header-icon="mdiPlusCircle" v-on:header-icon-click="addNewAuthor()"> <SearchAutocomplete source="/api/persons" :response-property="'first_name'" placeholder="search in person table...." v-on:person="onAddAuthor"></SearchAutocomplete> - <TablePersons :persons="form.authors" v-if="form.authors.length > 0" :relation="'authors'"/> - <div class="text-red-400 text-sm" v-if="form.errors.authors && Array.isArray(form.errors.authors)"> + <TablePersons :persons="form.authors" v-if="form.authors.length > 0" :errors="form.errors" + :relation="'authors'" /> + <div class="text-red-400 text-sm" + v-if="form.errors.authors && Array.isArray(form.errors.authors)"> {{ form.errors.authors.join(', ') }} </div> </CardBox> <!-- (8) contributors --> - <CardBox class="mb-6 shadow" has-table title="Contributors" :icon="mdiBookOpenPageVariant"> + <CardBox class="mb-6 shadow" has-table title="Contributors" :icon="mdiBookOpenPageVariant" + :header-icon="mdiPlusCircle" v-on:header-icon-click="addNewContributor()"> <SearchAutocomplete source="/api/persons" :response-property="'first_name'" placeholder="search in person table...." v-on:person="onAddContributor"> </SearchAutocomplete> @@ -334,8 +340,8 @@ </FormField> </div> - <CardBox class="mb-6 shadow" has-table title="Dataset References" :icon="mdiEarthPlus" :header-icon="mdiPlusCircle" - v-on:header-icon-click="addReference"> + <CardBox class="mb-6 shadow" has-table title="Dataset References" :icon="mdiEarthPlus" + :header-icon="mdiPlusCircle" v-on:header-icon-click="addReference"> <!-- Message when no references exist --> <div v-if="form.references.length === 0" class="text-center py-4"> <p class="text-gray-600">No references added yet.</p> @@ -408,6 +414,43 @@ </tr> </tbody> </table> + + <!-- References to delete section --> + <div v-if="form.referencesToDelete && form.referencesToDelete.length > 0" class="mt-8"> + <h1 class="pt-8 pb-3 font-semibold sm:text-lg text-gray-900">References To Delete</h1> + <ul class="flex flex-1 flex-wrap -m-1"> + <li v-for="(element, index) in form.referencesToDelete" :key="index" + class="block p-1 w-1/2 sm:w-1/3 md:w-1/4 lg:w-1/6 xl:w-1/8 h-40"> + <article tabindex="0" + class="bg-red-100 group w-full h-full rounded-md cursor-pointer relative shadow-sm overflow-hidden"> + <section + class="flex flex-col rounded-md text-xs break-words w-full h-full z-20 absolute top-0 py-2 px-3"> + <h1 + class="flex-1 text-gray-700 group-hover:text-blue-800 font-medium text-sm mb-1 truncate overflow-hidden whitespace-nowrap"> + {{ element.value }} + </h1> + <div class="flex flex-col mt-auto"> + <p class="p-1 size text-xs text-gray-700"> + <span class="font-semibold">Type:</span> {{ element.type }} + </p> + <p class="p-1 size text-xs text-gray-700"> + <span class="font-semibold">Relation:</span> {{ element.relation }} + </p> + <div class="flex justify-end mt-1"> + <button + class="restore ml-auto focus:outline-none hover:bg-gray-300 p-1 rounded-md text-gray-800" + @click.prevent="restoreReference(index)"> + <svg viewBox="0 0 24 24" class="w-5 h-5"> + <path fill="currentColor" :d="mdiRestore"></path> + </svg> + </button> + </div> + </div> + </section> + </article> + </li> + </ul> + </div> </CardBox> <BaseDivider /> @@ -420,20 +463,11 @@ </li> </ul> --> <TableKeywords :keywords="form.subjects" :errors="form.errors" :subjectTypes="subjectTypes" - v-if="form.subjects.length > 0" /> + v-model:subjects-to-delete="form.subjectsToDelete" v-if="form.subjects.length > 0" /> </CardBox> </div> - <!-- <div class="mb-4"> - <label for="description" class="block text-gray-700 font-bold mb-2">Description:</label> - <textarea id="description" - class="shadow appearance-none border rounded w-full py-2 px-3 text-gray-700 leading-tight focus:outline-none focus:shadow-outline" - v-model="form.type"></textarea> - </div> --> - - - <div class="mb-4"> <!-- <label for="project" class="block text-gray-700 font-bold mb-2">Project:</label> <select @@ -447,36 +481,28 @@ </select> --> </div> - <FileUploadComponent v-model:files="form.files" v-model:filesToDelete="form.filesToDelete"></FileUploadComponent> + <FileUploadComponent v-model:files="form.files" v-model:filesToDelete="form.filesToDelete" + :showClearButton="false"> + </FileUploadComponent> <div class="text-red-400 text-sm" v-if="form.errors['file'] && Array.isArray(form.errors['files'])"> {{ form.errors['files'].join(', ') }} </div> - - <!-- Add more input fields for the other properties of the dataset --> - <!-- <button - type="submit" - class="bg-blue-500 hover:bg-blue-700 text-white font-bold py-2 px-4 rounded focus:outline-none focus:shadow-outline" - > - Save - </button> --> - <template #footer> <BaseButtons> - <BaseButton @click.stop="submit" :disabled="form.processing" label="Save" color="info" - :class="{ 'opacity-25': form.processing }" small> + <BaseButton v-if="can.edit" @click.stop="submit" :disabled="form.processing" label="Save" + color="info" :icon="mdiDisc" :class="{ 'opacity-25': form.processing }" small> </BaseButton> - <!-- <button :disabled="form.processing" :class="{ 'opacity-25': form.processing }" - class="text-base hover:scale-110 focus:outline-none flex justify-center px-4 py-2 rounded font-bold cursor-pointer hover:bg-teal-200 bg-teal-100 text-teal-700 border duration-200 ease-in-out border-teal-600 transition" - @click.stop="submit"> - Save - </button> --> + <BaseButton v-if="can.edit" :route-name="stardust.route('dataset.release', [dataset.id])" + color="info" :icon="mdiLockOpen" :label="'Release'" small + :disabled="form.processing" + :class="{ 'opacity-25': form.processing }" /> </BaseButtons> </template> </CardBox> - <!-- Loading Spinner --> - <div v-if="form.processing" + <!-- Loading Spinner --> + <div v-if="form.processing" class="fixed inset-0 flex items-center justify-center bg-gray-500 bg-opacity-50 z-50"> <svg class="animate-spin h-12 w-12 text-white" xmlns="http://www.w3.org/2000/svg" fill="none" viewBox="0 0 24 24"> @@ -492,8 +518,6 @@ // import EditComponent from "./../EditComponent"; // export default EditComponent; -// import { Component, Vue, Prop, Setup, toNative } from 'vue-facing-decorator'; -// import AuthLayout from '@/Layouts/Auth.vue'; import LayoutAuthenticated from '@/Layouts/LayoutAuthenticated.vue'; import { useForm, Head, usePage } from '@inertiajs/vue3'; import { computed, ComputedRef } from 'vue'; @@ -527,6 +551,9 @@ import { mdiBookOpenPageVariant, mdiEarthPlus, mdiAlertBoxOutline, + mdiRestore, + mdiLockOpen, + mdiDisc } from '@mdi/js'; import { notify } from '@/notiwind'; import NotificationBar from '@/Components/NotificationBar.vue'; @@ -580,8 +607,10 @@ const props = defineProps({ type: Object, default: () => ({}), }, - - + can: { + type: Object, + default: () => ({}), + }, }); const flash: ComputedRef<any> = computed(() => { @@ -592,12 +621,6 @@ const flash: ComputedRef<any> = computed(() => { const errors: ComputedRef<any> = computed(() => { return usePage().props.errors; }); -// const errors: ComputedRef<any> = computed(() => { -// return usePage().props.errors; -// }); - -// const projects = reactive([]); -// const licenses = reactive([]); const mapOptions: MapOptions = { center: [48.208174, 16.373819], @@ -612,67 +635,72 @@ const fitBounds: LatLngBoundsExpression = [ ]; const mapId = 'test'; -// const downloadFile = async (id: string): Promise<string> => { -// const response = await axios.get<Blob>(`/api/download/${id}`, { -// responseType: 'blob', -// }); -// const url = URL.createObjectURL(response.data); -// setTimeout(() => { -// URL.revokeObjectURL(url); -// }, 1000); -// return url; -// }; - -// for (const file of props.dataset.files) { -// // console.log(`${file.name} path is ${file.filePath} here.`); -// file.fileSrc = ref(""); -// // downloadFile(file.id).then((value: string) => { -// // file.fileSrc = ref(value); -// // form = useForm<Dataset>(props.dataset as Dataset); -// // }); -// } props.dataset.filesToDelete = []; +props.dataset.subjectsToDelete = []; +props.dataset.referencesToDelete = []; let form = useForm<Dataset>(props.dataset as Dataset); -// const mainService = MainService(); -// mainService.fetchfiles(props.dataset); +// Add this computed property to the script section +const hasUnsavedChanges = computed(() => { + // Check if form is processing + if (form.processing) return true; + // Compare current form state with original dataset + // Check basic properties + if (form.language !== props.dataset.language) return true; + if (form.type !== props.dataset.type) return true; + if (form.project_id !== props.dataset.project_id) return true; + if (form.embargo_date !== props.dataset.embargo_date) return true; + // Check if licenses have changed + const originalLicenses = Array.isArray(props.dataset.licenses) + ? props.dataset.licenses.map(l => typeof l === 'object' ? l.id.toString() : l) + : []; + const currentLicenses = Array.isArray(form.licenses) + ? form.licenses.map(l => typeof l === 'object' ? l.id.toString() : l) + : []; + if (JSON.stringify(currentLicenses) !== JSON.stringify(originalLicenses)) return true; + // Check if titles have changed + if (JSON.stringify(form.titles) !== JSON.stringify(props.dataset.titles)) return true; + // Check if descriptions have changed + if (JSON.stringify(form.descriptions) !== JSON.stringify(props.dataset.descriptions)) return true; + // Check if authors have changed + if (JSON.stringify(form.authors) !== JSON.stringify(props.dataset.authors)) return true; -// const files = computed(() => props.dataset.file); + // Check if contributors have changed + if (JSON.stringify(form.contributors) !== JSON.stringify(props.dataset.contributors)) return true; + // Check if subjects have changed + // if (JSON.stringify(form.subjects) !== JSON.stringify(props.dataset.subjects)) return true; + let test = JSON.stringify(form.subjects); + let test2 = JSON.stringify(props.dataset.subjects); + if (test !== test2) { + return true; + } + // Check if references have changed + if (JSON.stringify(form.references) !== JSON.stringify(props.dataset.references)) return true; -// let form = useForm<Dataset>(props.dataset as Dataset); + // Check if coverage has changed + if (JSON.stringify(form.coverage) !== JSON.stringify(props.dataset.coverage)) return true; -// const form = useForm({ -// _method: 'put', -// login: props.user.login, -// email: props.user.email, -// password: '', -// password_confirmation: '', -// roles: props.userHasRoles, // fill actual user roles from db -// }); - -// async created() { -// // Fetch the list of projects and licenses from the server -// const response = await fetch('/api/datasets/edit/' + this.dataset.id); -// const data = await response.json(); -// this.projects = data.projects; -// this.licenses = data.licenses; -// } + // Check if files have changed + if (form.files?.length !== props.dataset.files?.length) return true; + if (form.filesToDelete?.length > 0) return true; + // Check if there are new files to upload + if (form.files?.some(file => !file.id)) return true; + // No changes detected + return false; +}); const submit = async (): Promise<void> => { let route = stardust.route('dataset.update', [props.dataset.id]); - // await Inertia.post('/app/register', this.form); - // await router.post('/app/register', this.form); - let licenses = form.licenses.map((obj) => { if (hasIdAttribute(obj)) { @@ -682,12 +710,6 @@ const submit = async (): Promise<void> => { } }); - - - // const files = form.files.map((obj) => { - // return new File([obj.blob], obj.label, { type: obj.type, lastModified: obj.lastModified }); - // }); - const [fileUploads, fileInputs] = form.files?.reduce( ([fileUploads, fileInputs], obj) => { if (!obj.id) { @@ -700,11 +722,11 @@ const submit = async (): Promise<void> => { // const file = new File([obj.blob], `${obj.label}?sortOrder=${obj.sort_order}`, options); // const metadata = JSON.stringify({ sort_order: obj.sort_order }); // const metadataBlob = new Blob([metadata + '\n'], { type: 'application/json' }); - const file = new File([obj.blob], `${obj.label}`, options,); - + const file = new File([obj.blob], `${obj.label}?sortorder=${obj.sort_order}`, options,); + // const file = new File([obj.blob], `${obj.label}`, options); - - + + // fileUploads[obj.sort_order] = file; fileUploads.push(file); } else { @@ -744,7 +766,9 @@ const submit = async (): Promise<void> => { // formStep.value++; // form.filesToDelete = []; // Clear the array using splice - form.filesToDelete?.splice(0, form.filesToDelete.length); + form.filesToDelete?.splice(0, form.filesToDelete.length); + form.subjectsToDelete?.splice(0, form.subjectsToDelete.length); + form.referencesToDelete?.splice(0, form.referencesToDelete.length); }, }); }; @@ -769,6 +793,11 @@ const removeDescription = (key: any) => { form.descriptions.splice(key, 1); }; +const addNewAuthor = () => { + let newAuthor = { status: false, first_name: '', last_name: '', email: '', academic_title: '', identifier_orcid: '', name_type: 'Personal' }; + form.authors.push(newAuthor); +}; + const onAddAuthor = (person: Person) => { if (form.authors.filter((e) => e.id === person.id).length > 0) { notify({ type: 'warning', title: 'Warning', text: 'person is already defined as author' }, 4000); @@ -780,6 +809,11 @@ const onAddAuthor = (person: Person) => { } }; +const addNewContributor = () => { + let newContributor = { status: false, first_name: '', last_name: '', email: '', academic_title: '', identifier_orcid: '', name_type: 'Personal', pivot: { contributor_type: '' } }; + form.contributors.push(newContributor); +}; + const onAddContributor = (person: Person) => { if (form.contributors.filter((e) => e.id === person.id).length > 0) { notify({ type: 'warning', title: 'Warning', text: 'person is already defined as contributor' }, 4000); @@ -794,7 +828,7 @@ const onAddContributor = (person: Person) => { }; const addKeyword = () => { - let newSubject: Subject = { value: 'test', language: '', type: 'uncontrolled', dataset_count: 0 }; + let newSubject: Subject = { value: '', language: '', type: 'uncontrolled' }; //this.dataset.files.push(uploadedFiles[i]); form.subjects.push(newSubject); }; @@ -806,9 +840,35 @@ const addReference = () => { }; const removeReference = (key: any) => { + const reference = form.references[key]; + + // If the reference has an ID, it exists in the database + // and should be added to referencesToDelete + if (reference.id) { + // Initialize referencesToDelete array if it doesn't exist + if (!form.referencesToDelete) { + form.referencesToDelete = []; + } + + // Add to referencesToDelete + form.referencesToDelete.push(reference); + } + + // Remove from form.references array form.references.splice(key, 1); }; +const restoreReference = (index: number) => { + // Get the reference from referencesToDelete + const reference = form.referencesToDelete[index]; + + // Add it back to form.references + form.references.push(reference); + + // Remove it from referencesToDelete + form.referencesToDelete.splice(index, 1); +}; + const onMapInitialized = (newItem: any) => { console.log(newItem); }; diff --git a/resources/js/Pages/Submitter/Dataset/Index.vue b/resources/js/Pages/Submitter/Dataset/Index.vue index 65ab0b1..5b01370 100644 --- a/resources/js/Pages/Submitter/Dataset/Index.vue +++ b/resources/js/Pages/Submitter/Dataset/Index.vue @@ -95,18 +95,18 @@ const formatServerState = (state: string) => { <table class="w-full table-fixed"> <thead> <tr> - <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider"> + <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider dark:text-white"> <!-- <Sort label="Dataset Title" attribute="title" :search="form.search" /> --> Dataset Title - </th> - <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider"> + </th> + <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider dark:text-white"> <!-- <Sort label="Email" attribute="email" :search="form.search" /> --> Server State </th> - <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider"> + <th scope="col" class="py-3 text-left text-xs font-medium uppercase tracking-wider dark:text-white"> Date of last modification </th> - <th scope="col" class="relative px-6 py-3" v-if="can.edit || can.delete"> + <th scope="col" class="relative px-6 py-3 dark:text-white" v-if="can.edit || can.delete"> <span class="sr-only">Actions</span> </th> </tr> @@ -114,35 +114,54 @@ const formatServerState = (state: string) => { <tbody class="bg-white divide-y divide-gray-200"> <tr v-for="dataset in props.datasets.data" :key="dataset.id" :class="getRowClass(dataset)"> - <td data-label="Login" class="py-4 whitespace-nowrap text-gray-700 dark:text-white table-title"> + <td data-label="Login" + class="py-4 whitespace-nowrap text-gray-700 table-title"> <!-- <Link v-bind:href="stardust.route('settings.user.show', [user.id])" class="no-underline hover:underline text-cyan-600 dark:text-cyan-400"> {{ user.login }} </Link> --> <!-- {{ user.id }} --> - {{ dataset.main_title }} + {{ dataset.main_title }} </td> - <td class="py-4 whitespace-nowrap text-gray-700 dark:text-white"> + <td class="py-4 whitespace-nowrap text-gray-700"> {{ formatServerState(dataset.server_state) }} + <div v-if="dataset.server_state === 'rejected_editor' && dataset.reject_editor_note" + class="inline-block relative ml-2 group"> + <button + class="w-5 h-5 rounded-full bg-gray-200 text-gray-600 text-xs flex items-center justify-center focus:outline-none hover:bg-gray-300"> + i + </button> + <div + class="absolute left-0 top-full mt-1 w-64 bg-white shadow-lg rounded-md p-3 text-xs text-left z-50 transform scale-0 origin-top-left transition-transform duration-100 group-hover:scale-100"> + <p + class="text-gray-700 max-h-40 overflow-y-auto overflow-x-hidden whitespace-normal break-words"> + {{ dataset.reject_editor_note }} + </p> + <div class="absolute -top-1 left-1 w-2 h-2 bg-white transform rotate-45"> + </div> + </div> + </div> </td> - <td data-label="modified" class="py-4 whitespace-nowrap text-gray-700 dark:text-white"> + <td data-label="modified" class="py-4 whitespace-nowrap text-gray-700"> <div class="text-sm" :title="dataset.server_date_modified"> {{ dataset.server_date_modified }} </div> </td> - <td class="py-4 whitespace-nowrap text-right text-sm font-medium text-gray-700 dark:text-white"> + <td + class="py-4 whitespace-nowrap text-right text-sm font-medium text-gray-700"> <BaseButtons v-if="validStates.includes(dataset.server_state)" type="justify-start lg:justify-end" no-wrap> <!-- release created dataset --> <BaseButton v-if="can.edit" :route-name="stardust.route('dataset.release', [dataset.id])" color="info" :icon="mdiLockOpen" :label="'Release'" small /> - <BaseButton v-if="can.edit" :route-name="stardust.route('dataset.edit', [dataset.id])" - color="info" :icon="mdiSquareEditOutline" :label="'Edit'" small /> + <BaseButton v-if="can.edit" + :route-name="stardust.route('dataset.edit', [dataset.id])" color="info" + :icon="mdiSquareEditOutline" :label="'Edit'" small /> <BaseButton v-if="can.edit" :route-name="stardust.route('dataset.categorize', [dataset.id])" color="info" - :icon="mdiLibraryShelves" :label="'Library'" small /> + :icon="mdiLibraryShelves" :label="'Classify'" small /> <BaseButton v-if="can.delete" color="danger" :route-name="stardust.route('dataset.delete', [dataset.id])" :icon="mdiTrashCan" small /> @@ -152,7 +171,7 @@ const formatServerState = (state: string) => { </tbody> </table> <div class="py-4"> - <Pagination v-bind:data="datasets.meta" /> + <Pagination v-bind:data="datasets.meta" /> </div> </CardBox> </SectionMain> @@ -160,13 +179,17 @@ const formatServerState = (state: string) => { </template> <style scoped lang="css"> - .table-title { - max-width: 200px; /* set a maximum width */ - overflow: hidden; /* hide overflow */ - text-overflow: ellipsis; /* show ellipsis for overflowed text */ - white-space: nowrap; /* prevent wrapping */ + max-width: 200px; + /* set a maximum width */ + overflow: hidden; + /* hide overflow */ + text-overflow: ellipsis; + /* show ellipsis for overflowed text */ + white-space: nowrap; + /* prevent wrapping */ } + .table-fixed { table-layout: fixed; } @@ -208,6 +231,4 @@ const formatServerState = (state: string) => { color: whitesmoke; }*/ - - -</style> +</style> diff --git a/resources/js/Pages/profile/partials/update-profile-information-form.vue b/resources/js/Pages/profile/partials/update-profile-information-form.vue index e15d13c..5a5fdff 100644 --- a/resources/js/Pages/profile/partials/update-profile-information-form.vue +++ b/resources/js/Pages/profile/partials/update-profile-information-form.vue @@ -105,7 +105,7 @@ const updateProfileInformation = () => { <FormField label="Username" :class="{ 'text-red-400': form.errors.login }"> <FormControl id="username" label="Username" v-model="form.login" class="w-full" - :is-read-only="!user.is_admin"> + :is-read-only="true"> <div class="text-red-400 text-sm" v-if="errors.login && Array.isArray(errors.login)"> {{ errors.login.join(', ') }} </div> @@ -115,7 +115,7 @@ const updateProfileInformation = () => { <FormField label="Enter Email"> <FormControl v-model="form.email" type="text" placeholder="Email" :errors="form.errors.email" - :is-read-only="!user.is_admin"> + :is-read-only="true"> <div class="text-red-400 text-sm" v-if="errors.email && Array.isArray(errors.email)"> {{ errors.email.join(', ') }} </div> diff --git a/resources/js/Stores/main.ts b/resources/js/Stores/main.ts index 39ca0c0..3a31057 100644 --- a/resources/js/Stores/main.ts +++ b/resources/js/Stores/main.ts @@ -198,7 +198,8 @@ export const MainService = defineStore('main', { } }) .catch((error) => { - alert(error.message); + // alert(error.message); + throw error; }); }, @@ -236,17 +237,18 @@ export const MainService = defineStore('main', { this.totpState = state; }, - fetchChartData(year: string) { + fetchChartData() { // sampleDataKey= authors or datasets axios - .get(`/api/statistic/${year}`) + .get(`/api/statistic`) .then((r) => { if (r.data) { this.graphData = r.data; } }) .catch((error) => { - alert(error.message); + // alert(error.message); + throw error; }); }, diff --git a/resources/js/app.ts b/resources/js/app.ts index e98664d..5931472 100644 --- a/resources/js/app.ts +++ b/resources/js/app.ts @@ -81,7 +81,7 @@ const layoutService = LayoutService(pinia); const localeService = LocaleStore(pinia); localeService.initializeLocale(); -const mainService = MainService(pinia); +// const mainService = MainService(pinia); // mainService.setUser(user); /* App style */ @@ -91,12 +91,11 @@ styleService.setStyle(localStorage[styleKey] ?? 'basic'); if ((!localStorage[darkModeKey] && window.matchMedia('(prefers-color-scheme: dark)').matches) || localStorage[darkModeKey] === '1') { styleService.setDarkMode(true); } -// mainService.fetch('clients'); -// mainService.fetch('history'); -mainService.fetchApi('clients'); -mainService.fetchApi('authors'); -mainService.fetchApi('datasets'); -mainService.fetchChartData("2022"); + +// mainService.fetchApi('clients'); +// mainService.fetchApi('authors'); +// mainService.fetchApi('datasets'); +// mainService.fetchChartData(); /* Collapse mobile aside menu on route change */ Inertia.on('navigate', () => { diff --git a/resources/js/logo.svg b/resources/js/logo.svg index 1786dcf..c0b62d6 100644 --- a/resources/js/logo.svg +++ b/resources/js/logo.svg @@ -1,183 +1,9 @@ -<!-- <svg width="60" height="59" viewBox="0 0 60 59" fill="none" xmlns="http://www.w3.org/2000/svg"> - <path - d="M22.0604 27.0103C29.7333 23.0893 35.8474 16.6142 39.6254 8.51905C40.1123 7.47585 39.871 6.25371 39.3648 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+</defs> +</svg> diff --git a/resources/js/menu.ts b/resources/js/menu.ts index 544b0cb..16d08d7 100644 --- a/resources/js/menu.ts +++ b/resources/js/menu.ts @@ -156,18 +156,13 @@ export default [ // label: 'Create Dataset', // }, ], - }, + }, // { - // route: 'dataset.create', - // icon: mdiDatabasePlus, - // label: 'Create Dataset', + // href: '', + // icon: mdiGithub, + // label: 'Forgejo', + // target: '_blank', // }, - { - href: 'https://gitea.geosphere.at/geolba/tethys.backend', - icon: mdiGithub, - label: 'Forgejo', - target: '_blank', - }, { href: '/oai', icon: mdiAccountEye, diff --git a/resources/views/app.edge b/resources/views/app.edge index 48bb1f8..7020953 100644 --- a/resources/views/app.edge +++ b/resources/views/app.edge @@ -7,6 +7,12 @@ <meta name="msapplication-TileColor" content="#da532c"> <meta name="theme-color" content="#ffffff"> + <link rel="icon" type="image/svg+xml" href="/favicon.svg"> + <link rel="apple-touch-icon" sizes="180x180" href="/apple-touch-icon.png"> + <link rel="icon" type="image/png" sizes="32x32" href="/favicon-32x32.png"> + <link rel="icon" type="image/png" sizes="16x16" href="/favicon-16x16.png"> + <link rel="manifest" href="/site.webmanifest"> + <!-- <link rel="icon" href="/apps/theming/favicon/settings?v=ad28c447"> --> <input type="hidden" id="initial-state-firstrunwizard-desktop" value="Imh0dHBzOi8vZ2l0ZWEuZ2VvbG9naWUuYWMuYXQvZ2VvbGJhL3RldGh5cy5iYWNrZW5kIg=="> diff --git a/start/routes.ts b/start/routes.ts index fc24e3a..ad28a87 100644 --- a/start/routes.ts +++ b/start/routes.ts @@ -106,7 +106,14 @@ router // Auth routes router - .get('/app/login', ({ inertia }: HttpContext) => { + .get('/app/login', async ({ inertia }: HttpContext) => { + try { + await db.connection().rawQuery('SELECT 1'); + } catch (error) { + if (error.code === 'ECONNREFUSED') { + throw error; + } + } return inertia.render('Auth/Login'); }) .as('app.login.show'); @@ -246,18 +253,11 @@ router.get('/settings/user/security', [UserController, 'accountInfo']).as('setti router.post('/settings/user/store', [UserController, 'accountInfoStore']).as('account.password.store').use(middleware.auth()); router.get('/settings/profile/edit', [UserController, 'profile']).as('settings.profile.edit').use(middleware.auth()); router -.put('/settings/profile/:id/update', [UserController, 'profileUpdate']) -.as('settings.profile.update') -.where('id', router.matchers.number()) -.use(middleware.auth()); -router -.put('/settings/password/update', [UserController, 'passwordUpdate']) -.as('settings.password.update') -.use(middleware.auth()); - - - - + .put('/settings/profile/:id/update', [UserController, 'profileUpdate']) + .as('settings.profile.update') + .where('id', router.matchers.number()) + .use(middleware.auth()); +router.put('/settings/password/update', [UserController, 'passwordUpdate']).as('settings.password.update').use(middleware.auth()); // Submitter routes router @@ -364,6 +364,44 @@ router .as('editor.dataset.rejectUpdate') .where('id', router.matchers.number()) .use([middleware.auth(), middleware.can(['dataset-editor-reject'])]); + + router + .get('/dataset/:id/edit', [EditorDatasetController, 'edit']) + .as('editor.dataset.edit') + // .where('id', router.matchers.number()) + .use([middleware.auth(), middleware.can(['dataset-editor-update'])]); + router + .put('/dataset/:id/update', [EditorDatasetController, 'update']) + .as('editor.dataset.update') + .where('id', router.matchers.number()) + .use([middleware.auth(), middleware.can(['dataset-editor-update'])]); + + router + .get('/dataset/:id/categorize', [EditorDatasetController, 'categorize']) + .as('editor.dataset.categorize') + .where('id', router.matchers.number()) + .use([middleware.auth(), middleware.can(['dataset-editor-update'])]); + router + .put('/dataset/:id/categorizeUpdate', [EditorDatasetController, 'categorizeUpdate']) + .as('editor.dataset.categorizeUpdate') + .where('id', router.matchers.number()) + .use([middleware.auth(), middleware.can(['dataset-editor-update'])]); + + router + .get('/file/download/:id', [EditorDatasetController, 'download']) + .as('editor.file.download') + .where('id', router.matchers.number()) + .use([middleware.auth(), middleware.can(['dataset-editor-update'])]); + router + .get('dataset/:id/rejectToReviewer', [EditorDatasetController, 'rejectToReviewer']) + .as('editor.dataset.rejectToReviewer') + .where('id', router.matchers.number()) + .use([middleware.auth(), middleware.can(['dataset-editor-reject'])]); + router + .put('dataset/:id/rejectToReviewer', [EditorDatasetController, 'rejectToReviewerUpdate']) + .as('editor.dataset.rejectToReviewerUpdate') + .where('id', router.matchers.number()) + .use([middleware.auth(), middleware.can(['dataset-editor-reject'])]); router .get('dataset/:id/publish', [EditorDatasetController, 'publish']) .as('editor.dataset.publish') @@ -384,10 +422,10 @@ router .as('editor.dataset.doiStore') .where('id', router.matchers.number()) .use([middleware.auth(), middleware.can(['dataset-publish'])]); - router - .put('/dataset/:id/update', [EditorDatasetController, 'update']) - .as('editor.dataset.update') - .use([middleware.auth(), middleware.can(['dataset-editor-edit'])]); + // router + // .put('/dataset/:id/update', [EditorDatasetController, 'update']) + // .as('editor.dataset.update') + // .use([middleware.auth(), middleware.can(['dataset-editor-edit'])]); }) .prefix('editor'); @@ -408,6 +446,11 @@ router .as('reviewer.dataset.reviewUpdate') .where('id', router.matchers.number()) .use([middleware.auth(), middleware.can(['dataset-review'])]); + router + .get('/file/download/:id', [ReviewerDatasetController, 'download']) + .as('reviewer.file.download') + .where('id', router.matchers.number()) + .use([middleware.auth(), middleware.can(['dataset-review'])]); router .get('dataset/:id/reject', [ReviewerDatasetController, 'reject']) .as('reviewer.dataset.reject') diff --git a/start/routes/api.ts b/start/routes/api.ts index 32bc6c2..55fccc5 100644 --- a/start/routes/api.ts +++ b/start/routes/api.ts @@ -11,8 +11,8 @@ import { middleware } from '../kernel.js'; // API router .group(() => { - router.get('clients', [UserController, 'getSubmitters']).as('client.index'); - router.get('authors', [AuthorsController, 'index']).as('author.index'); + router.get('clients', [UserController, 'getSubmitters']).as('client.index').use(middleware.auth());; + router.get('authors', [AuthorsController, 'index']).as('author.index').use(middleware.auth());; router.get('datasets', [DatasetController, 'index']).as('dataset.index'); router.get('persons', [AuthorsController, 'persons']).as('author.persons'); @@ -20,9 +20,9 @@ router router.get('/dataset/:publish_id', [DatasetController, 'findOne']).as('dataset.findOne'); router.get('/sitelinks/:year', [HomeController, 'findDocumentsPerYear']); router.get('/years', [HomeController, 'findYears']); - router.get('/statistic/:year', [HomeController, 'findPublicationsPerMonth']); + router.get('/statistic', [HomeController, 'findPublicationsPerMonth']); - router.get('/download/:id', [FileController, 'findOne']).as('file.findOne'); + router.get('/file/download/:id', [FileController, 'findOne']).as('file.findOne'); router.get('/avatar/:name/:background?/:textColor?/:size?', [AvatarController, 'generateAvatar']); diff --git a/start/rules/array_contains_types.ts b/start/rules/array_contains_types.ts new file mode 100644 index 0000000..1fe5994 --- /dev/null +++ b/start/rules/array_contains_types.ts @@ -0,0 +1,80 @@ +import { FieldContext } from '@vinejs/vine/types'; +import vine, { VineArray } from '@vinejs/vine'; +import { SchemaTypes } from '@vinejs/vine/types'; + +type Options = { + typeA: string; + typeB: string; +}; + +/** + * Custom rule to validate an array of titles contains at least one title + * with type 'main' and one with type 'translated'. + * + * This rule expects the validated value to be an array of objects, + * where each object has a "type" property. + */ +async function arrayContainsTypes(value: unknown, options: Options, field: FieldContext) { + if (!Array.isArray(value)) { + field.report(`The {{field}} must be an array of titles.`, 'array.titlesContainsMainAndTranslated', field); + return false; + } + + const typeAExpected = options.typeA.toLowerCase(); + const typeBExpected = options.typeB.toLowerCase(); + + // const hasMain = value.some((title: any) => { + // return typeof title === 'object' && title !== null && String(title.type).toLowerCase() === 'main'; + // }); + + // const hasTranslated = value.some((title: any) => { + // return typeof title === 'object' && title !== null && String(title.type).toLowerCase() === 'translated'; + // }); + const hasTypeA = value.some((item: any) => { + return typeof item === 'object' && item !== null && String(item.type).toLowerCase() === typeAExpected; + }); + + const hasTypeB = value.some((item: any) => { + return typeof item === 'object' && item !== null && String(item.type).toLowerCase() === typeBExpected; + }); + if (!hasTypeA || !hasTypeB) { + let errorMessage = `The ${field.getFieldPath()} array must have at least one '${options.typeA}' item and one '${options.typeB}' item.`; + + // Check for specific field names to produce a more readable message. + if (field.getFieldPath() === 'titles') { + // For titles we expect one main and minimum one translated title. + if (!hasTypeA && !hasTypeB) { + errorMessage = 'For titles, define at least one main title and at least one Translated title as MAIN TITLE.'; + } else if (!hasTypeA) { + errorMessage = 'For titles, define at least one main title.'; + } else if (!hasTypeB) { + errorMessage = 'For Titles, define at least one Translated title as MAIN TITLE.'; + } + } else if (field.getFieldPath() === 'descriptions') { + // For descriptions we expect one abstracts description and minimum one translated description. + if (!hasTypeA && !hasTypeB) { + errorMessage = 'For descriptions, define at least one abstract and at least one Translated description as MAIN ABSTRACT.'; + } else if (!hasTypeA) { + errorMessage = 'For descriptions, define at least one abstract.'; + } else if (!hasTypeB) { + errorMessage = 'For Descriptions, define at least one Translated description as MAIN ABSTRACT.'; + } + } + + field.report(errorMessage, 'array.containsTypes', field, options); + return false; + } + return true; +} + +export const arrayContainsMainAndTranslatedRule = vine.createRule(arrayContainsTypes); + +declare module '@vinejs/vine' { + interface VineArray<Schema extends SchemaTypes> { + arrayContainsTypes(options: Options): this; + } +} + +VineArray.macro('arrayContainsTypes', function <Schema extends SchemaTypes>(this: VineArray<Schema>, options: Options) { + return this.use(arrayContainsMainAndTranslatedRule(options)); +}); diff --git a/tailwind.config.js b/tailwind.config.js index 692176b..e41b62d 100644 --- a/tailwind.config.js +++ b/tailwind.config.js @@ -12,6 +12,10 @@ module.exports = { gray: 'gray', }, extend: { + backgroundImage: { + 'radio-checked': "url(\"data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 24 24'%3E%3Cpath fill='%23fff' d='M12,2A10,10 0 0,0 2,12A10,10 0 0,0 12,22A10,10 0 0,0 22,12A10,10 0 0,0 12,2Z' /%3E%3C/svg%3E\")", + 'checkbox-checked': "url(\"data:image/svg+xml,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 1 1'%3E%3Cpath style='fill:%23fff' d='M 0.04038059,0.6267767 0.14644661,0.52071068 0.42928932,0.80355339 0.3232233,0.90961941 z M 0.21715729,0.80355339 0.85355339,0.16715729 0.95961941,0.2732233 0.3232233,0.90961941 z'%3E%3C/path%3E%3C/svg%3E\")", + }, colors: { 'primary': '#22C55E', 'inprogress': 'rgb(94 234 212)',