@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
    • items link

getPages

List of all pages from this portal.

opendatasoft.getPages(null, context)

Input

This action has no parameters

Output

• output object
  • links array
    • items link
  • pages array
    • items object
      • links array
        • items link
      • page page

getPage

A single page's metadata from this portal

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

Input

• input object
  • slug required string: Page slug.

Output

• output object
  • links array
    • items link
  • page page

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
    • items link

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
  • aggregations array
    • items aggregation
  • links array
    • items link

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
    • items object
      • dataset dataset
      • links array
        • items link
  • links array
    • items link
  • 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

• output object
  • dataset dataset
  • links array
    • items link

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
  • aggregations array
    • items aggregation
  • links array
    • items link

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
  • attachments array
    • items attachment
  • links array
    • items link

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

• output object
  • facets array
    • items facet_enumeration

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
    • items link
  • records array
    • items object
      • links array
        • items link
      • record record
  • 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
  • links array
    • items link
  • record record

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
    • items link
  • reuses array
    • items reuse

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
  • links array
    • items link
  • reuse reuse

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
  • links array
    • items link
  • snapshots array
    • items snapshot

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

• output object
  • facets array
    • items facet_enumeration

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
    • items link

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
  • links array
    • items link
  • metadata_templates array
    • items object
      • links array
        • items link
      • metadata_template metadata_template

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

• output object
  • links array
    • items link
  • metadata_template metadata_template

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

• datasets array
  • items dataset

facet_enumeration

• facet_enumeration object
  • facets array
    • items facet_value_enumeration
  • name string

facet_value_enumeration

• facet_value_enumeration object
  • count integer
  • facets array
    • items facet_value_enumeration
  • name string
  • value string

link

• link object
  • href string
  • rel string

links

• links array
  • items link

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

• records array
  • items record

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