@datafire/opendatasoft

5.0.0 • Public • Published

@datafire/opendatasoft

Client library for opendatasoft

Installation and Usage

npm install --save @datafire/opendatasoft
let opendatasoft = require('@datafire/opendatasoft').create({
  api_key: "",
  username: "",
  password: ""
});

.then(data => {
  console.log(data);
});

Description

Actions

getRoot

API entry point

Provides links for:

  • catalog, your domain's list of datasets
  • opendatasoft, all datasets on the Opendatasoft network
opendatasoft.getRoot(null, context)

Input

This action has no parameters

Output

  • output object
    • links array

getPages

List of all pages from this portal.

opendatasoft.getPages(null, context)

Input

This action has no parameters

Output

  • output object
    • links array
    • pages array
      • items object

getPage

A single page's metadata from this portal

opendatasoft.getPage({
  "slug": ""
}, context)

Input

  • input object
    • slug required string: Page slug.

Output

  • output object

getSource

Source entry points

Provides links for the source's datasets and metadata.

opendatasoft.getSource({
  "source": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.

Output

  • output object
    • links array

aggregateDatasets

Compute aggregations from catalog and return a list of each aggregate indexed by their names.

opendatasoft.aggregateDatasets({
  "source": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • select string: A select expression can be used to add, remove or change fields to return.
    • group_by string: A group by expression defines a grouping function for an aggregation.
    • where array: An array of filters.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • order_by array: A list of field names or aggregation, followed by an order (asc | desc).
    • offset integer: Index of the first item to return (starting at 0).
    • limit integer: Number of items to return.

Output

  • output object

getDatasets

List of available datasets, each with their endpoints, paginated.

Links provided:

  • previous page
  • next page
  • last page
  • first page
opendatasoft.getDatasets({
  "source": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • where array: An array of filters.
    • search array: An array of full text search.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • limit integer: Number of items to return.
    • offset integer: Index of the first item to return (starting at 0).
    • sort array: A list of field names, each possibly prefixed with a minus (-).
    • pretty boolean: Activate pretty print
    • timezone string: Set timezone for datetime fields
    • include_app_metas boolean: Explicitely request application metas for each datasets.

Output

  • output object
    • datasets array
    • links array
    • total_count integer

getDataset

List of available endpoints for the specified dataset, with metadata and endpoints.

Will provide links for:

  • the attachments endpoint
  • the files endpoint
  • the records endpoint
  • the catalog endpoint
opendatasoft.getDataset({
  "source": "",
  "dataset_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • pretty boolean: Activate pretty print
    • timezone string: Set timezone for datetime fields
    • select string: A select expression can be used to add, remove or change fields to return.
    • include_app_metas boolean: Explicitely request application metas for each datasets.

Output

aggregateRecords

Compute aggregations from dataset records and return a list of each aggregate indexed by their names.

opendatasoft.aggregateRecords({
  "source": "",
  "dataset_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • select string: A select expression can be used to add, remove or change fields to return.
    • group_by string: A group by expression defines a grouping function for an aggregation.
    • where array: An array of filters.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • order_by array: A list of field names or aggregation, followed by an order (asc | desc).
    • limit integer: Number of items to return.
    • offset integer: Index of the first item to return (starting at 0).

Output

  • output object

getDatasetAttachements

Get list of all available attachments

opendatasoft.getDatasetAttachements({
  "source": "",
  "dataset_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.

Output

  • output object

downloadDatasetAttachement

Download attachment

opendatasoft.downloadDatasetAttachement({
  "source": "",
  "dataset_id": "",
  "attachment_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • attachment_id required string

Output

Output schema unknown

exportRecordsCSV

Export dataset in CSV format

opendatasoft.exportRecordsCSV({
  "source": "",
  "dataset_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • where array: An array of filters.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • limit integer: Number of items to return in export.
    • offset integer: Index of the first item to return (starting at 0).
    • sort array: A list of field names, each possibly prefixed with a minus (-).
    • select string: A select expression can be used to add, remove or change fields to return.
    • timezone string: Set timezone for datetime fields
    • delimiter string (values: ,, ;, |): Provide a different delimiter (default ',').

Output

  • output file

exportRecordsGEOJSON

Export dataset in GEOJSON format

opendatasoft.exportRecordsGEOJSON({
  "source": "",
  "dataset_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • where array: An array of filters.
    • search array: An array of full text search.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • limit integer: Number of items to return in export.
    • offset integer: Index of the first item to return (starting at 0).
    • sort array: A list of field names, each possibly prefixed with a minus (-).
    • select string: A select expression can be used to add, remove or change fields to return.
    • timezone string: Set timezone for datetime fields
    • pretty boolean: Activate pretty print

Output

  • output file

exportRecordsICAL

Export dataset in ICAL format

opendatasoft.exportRecordsICAL({
  "source": "",
  "dataset_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • where array: An array of filters.
    • search array: An array of full text search.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • limit integer: Number of items to return in export.
    • offset integer: Index of the first item to return (starting at 0).
    • sort array: A list of field names, each possibly prefixed with a minus (-).
    • select string: A select expression can be used to add, remove or change fields to return.
    • timezone string: Set timezone for datetime fields

Output

  • output file

exportRecordsJSON

Export dataset in JSON format

opendatasoft.exportRecordsJSON({
  "source": "",
  "dataset_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • where array: An array of filters.
    • search array: An array of full text search.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • limit integer: Number of items to return in export.
    • offset integer: Index of the first item to return (starting at 0).
    • sort array: A list of field names, each possibly prefixed with a minus (-).
    • select string: A select expression can be used to add, remove or change fields to return.
    • pretty boolean: Activate pretty print
    • timezone string: Set timezone for datetime fields

Output

  • output file

exportRecordsOV2

Export dataset in OV2 format

opendatasoft.exportRecordsOV2({
  "source": "",
  "dataset_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • where array: An array of filters.
    • search array: An array of full text search.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • limit integer: Number of items to return in export.
    • offset integer: Index of the first item to return (starting at 0).
    • sort array: A list of field names, each possibly prefixed with a minus (-).
    • select string: A select expression can be used to add, remove or change fields to return.
    • timezone string: Set timezone for datetime fields

Output

  • output file

exportRecordsSHP

Export dataset in Esri shapefile (shp) format

opendatasoft.exportRecordsSHP({
  "source": "",
  "dataset_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • where array: An array of filters.
    • search array: An array of full text search.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • limit integer: Number of items to return in export.
    • offset integer: Index of the first item to return (starting at 0).
    • sort array: A list of field names, each possibly prefixed with a minus (-).
    • select string: A select expression can be used to add, remove or change fields to return.
    • timezone string: Set timezone for datetime fields

Output

  • output file

exportRecordsXLS

Export dataset in XLS (Excel) format

opendatasoft.exportRecordsXLS({
  "source": "",
  "dataset_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • where array: An array of filters.
    • search array: An array of full text search.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • limit integer: Number of items to return in export.
    • offset integer: Index of the first item to return (starting at 0).
    • sort array: A list of field names, each possibly prefixed with a minus (-).
    • select string: A select expression can be used to add, remove or change fields to return.
    • timezone string: Set timezone for datetime fields

Output

  • output file

getRecordsFacets

Enumerate facets values for records and return a list of values for each facet. Can be used to implement guided navigation in large result sets.

Read the facets documentation for more details.

opendatasoft.getRecordsFacets({
  "source": "",
  "dataset_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • where array: An array of filters.
    • search array: An array of full text search.
    • timezone string: Set timezone for datetime fields

Output

sendDatasetFeedback

Create new feedback entry.

opendatasoft.sendDatasetFeedback({
  "source": "",
  "dataset_id": "",
  "feedback": null
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • feedback required object
      • comment string
      • newValues object: New record value
      • recordid string: Feedback entry's recordid
      • schema object: Record schema

Output

Output schema unknown

getDatasetFile

Download file

opendatasoft.getDatasetFile({
  "source": "",
  "dataset_id": "",
  "file_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • file_id required string
    • thumbnail_size string: Set the size of the thumbnail representing the resource (attachment, image or file)

Output

Output schema unknown

getRecords

Search dataset's records.

opendatasoft.getRecords({
  "source": "",
  "dataset_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • where array: An array of filters.
    • search array: An array of full text search.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • limit integer: Number of items to return.
    • offset integer: Index of the first item to return (starting at 0).
    • sort array: A list of field names, each possibly prefixed with a minus (-).
    • select string: A select expression can be used to add, remove or change fields to return.
    • pretty boolean: Activate pretty print
    • timezone string: Set timezone for datetime fields

Output

  • output object
    • links array
    • records array
      • items object
    • total_count integer

getRecord

Retrieve a single record based on its ID.

opendatasoft.getRecord({
  "source": "",
  "dataset_id": "",
  "record_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • record_id required string
    • pretty boolean: Activate pretty print
    • timezone string: Set timezone for datetime fields
    • select string: A select expression can be used to add, remove or change fields to return.

Output

  • output object

getDatasetReuses

Get list of reuses

opendatasoft.getDatasetReuses({
  "source": "",
  "dataset_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • offset integer: Index of the first item to return (starting at 0).
    • limit integer: Number of items to return.
    • timezone string: Set timezone for datetime fields

Output

  • output object
    • links array
    • reuses array

getDatasetReuse

Retrieve a single reuse based on its ID.

opendatasoft.getDatasetReuse({
  "source": "",
  "dataset_id": "",
  "reuse_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • reuse_id required string
    • timezone string: Set timezone for datetime fields

Output

  • output object

getDatasetSnapshots

List of all snapshots for this dataset.

opendatasoft.getDatasetSnapshots({
  "source": "",
  "dataset_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • timezone string: Set timezone for datetime fields

Output

  • output object

downloadDatasetSnapshot

List of all snapshots for this dataset.

opendatasoft.downloadDatasetSnapshot({
  "source": "",
  "dataset_id": "",
  "snapshot_id": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • dataset_id required string: Dataset identifier.
    • snapshot_id required string
    • timezone string: Set timezone for datetime fields

Output

Output schema unknown

exportDatasetsCSV

Export catalog (source) in CSV format

opendatasoft.exportDatasetsCSV({
  "source": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • where array: An array of filters.
    • search array: An array of full text search.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • limit integer: Number of items to return.
    • offset integer: Index of the first item to return (starting at 0).
    • timezone string: Set timezone for datetime fields
    • include_app_metas boolean: Explicitely request application metas for each datasets.
    • delimiter string (values: ,, ;, |): Provide a different delimiter (default ',').

Output

  • output file

exportDatasetsJson

Export catalog (source) in JSON format

opendatasoft.exportDatasetsJson({
  "source": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • where array: An array of filters.
    • search array: An array of full text search.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • limit integer: Number of items to return.
    • offset integer: Index of the first item to return (starting at 0).
    • pretty boolean: Activate pretty print
    • timezone string: Set timezone for datetime fields
    • include_app_metas boolean: Explicitely request application metas for each datasets.

Output

  • output file

exportDatasetsRDF

Export catalog (source) in RDF/XML format

opendatasoft.exportDatasetsRDF({
  "source": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • where array: An array of filters.
    • search array: An array of full text search.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • limit integer: Number of items to return.
    • offset integer: Index of the first item to return (starting at 0).
    • timezone string: Set timezone for datetime fields
    • include_app_metas boolean: Explicitely request application metas for each datasets.

Output

  • output file

exportDatasetsRSS

Export catalog (source) in RSS format

opendatasoft.exportDatasetsRSS({
  "source": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • where array: An array of filters.
    • search array: An array of full text search.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • limit integer: Number of items to return.
    • offset integer: Index of the first item to return (starting at 0).
    • timezone string: Set timezone for datetime fields
    • include_app_metas boolean: Explicitely request application metas for each datasets.

Output

  • output file

exportDatasetsTTL

Export catalog (source) in TTL (turtle/rdf) format

opendatasoft.exportDatasetsTTL({
  "source": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • where array: An array of filters.
    • search array: An array of full text search.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • limit integer: Number of items to return.
    • offset integer: Index of the first item to return (starting at 0).
    • timezone string: Set timezone for datetime fields
    • include_app_metas boolean: Explicitely request application metas for each datasets.

Output

  • output file

exportDatasetsXLS

Export catalog (source) in XLS (Excel) format

opendatasoft.exportDatasetsXLS({
  "source": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • where array: An array of filters.
    • search array: An array of full text search.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • limit integer: Number of items to return.
    • offset integer: Index of the first item to return (starting at 0).
    • timezone string: Set timezone for datetime fields
    • include_app_metas boolean: Explicitely request application metas for each datasets.

Output

  • output file

getDatasetsFacets

Enumerate facets values for datasets and return a list of values for each facet. Can be used to implement guided navigation in large result sets.

Read the facets documentation for more details.

opendatasoft.getDatasetsFacets({
  "source": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • facet array: A facet is a field used for simple filtering (through the parameters refine and exclude) or exploration (with the endpoint /facets).
    • refine array: An array of facet filters. For example city:Paris or modified:2019/12.
    • exclude array: An array of facet filters. For example city:Paris or modified:2019/12.
    • where array: An array of filters.
    • search array: An array of full text search.
    • timezone string: Set timezone for datetime fields

Output

getMetadataTemplatesTypes

List of available metadata templates types, each with their endpoints.

opendatasoft.getMetadataTemplatesTypes({
  "source": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.

Output

  • output object
    • links array

getMetadataTemplatesType

List of metadata templates available for this type.

opendatasoft.getMetadataTemplatesType({
  "source": "",
  "metadata_template_type": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • metadata_template_type required string (values: basic, interop, extra)

Output

  • output object

getMetadataTemplate

A single metadata_template

opendatasoft.getMetadataTemplate({
  "source": "",
  "metadata_template_type": "",
  "metadata_template_name": ""
}, context)

Input

  • input object
    • source required string (values: catalog, opendatasoft, monitoring): Each source represents a different catalog of datasets you'll be able to query.
    • metadata_template_type required string (values: basic, interop, extra)
    • metadata_template_name required string

Output

Definitions

aggregation

  • aggregation object: Result of an aggregation request.

attachment

  • attachment object
    • href string
    • metas object

dataset

  • dataset object
    • attachments array
      • items object
    • data_visible boolean
    • dataset_id string
    • features array: A map of available features for a dataset, with the fields they apply to.
      • items string
    • fields array
      • items object
        • annotations object
        • description string
        • label string
        • name string
        • type string
    • has_records boolean
    • metas object

datasets

facet_enumeration

facet_value_enumeration

link

  • link object
    • href string
    • rel string

links

  • links array

metadata_template

  • metadata_template object
    • name string
    • schema array
      • items object
    • type string

page

  • page object
    • description string
    • slug string
    • title object: A localized string (that is an object where the keys are language codes and the values translations of a same
      • en string
      • fr string

query_string

  • query_string string: Query string using the query language.

record

  • record object
    • fields object
    • id string
    • size integer
    • timestamp string

records

reuse

  • reuse object
    • created_at string: Date when the reuse was submitted.
    • id string: reuse id
    • thumbnail string: URL illustrating the work.
    • title string: Short description of the user's work.
    • url string: URL where the work can be accessed publicly.
    • user object
      • first_name string
      • last_name string
      • username string

snapshot

  • snapshot object
    • created_at string
    • description string
    • href string
    • snapshot_id string

timezone

  • timezone string: A timezone

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