The Dataverse Software exposes most of its GUI functionality via a REST-based API. This section describes that functionality. Most API endpoints require an API token that can be passed as the X-Dataverse-key
HTTP header or in the URL as the key
query parameter.
Note
CORS Some API endpoint allow CORS (cross-origin resource sharing), which makes them usable from scripts running in web browsers. These endpoints are marked with a CORS badge.
Note
Bash environment variables shown below. The idea is that you can “export” these environment variables before copying and pasting the commands that use them. For example, you can set $SERVER_URL
by running export SERVER_URL="https://demo.dataverse.org"
in your Bash shell. To check if the environment variable was set properly, you can “echo” it (e.g. echo $SERVER_URL
). See also curl Examples and Environment Variables.
Warning
The Dataverse Software’s API is versioned at the URI - all API calls may include the version number like so: http://server-address/api/v1/...
. Omitting the v1
part would default to the latest API version (currently 1). When writing scripts/applications that will be used for a long time, make sure to specify the API version, so they don’t break when the API is upgraded.
Contents:
A Dataverse collection is a container for datasets and other Dataverse collections as explained in the Dataverse Collection Management section of the User Guide.
The steps for creating a Dataverse collection are:
Download dataverse-complete.json
file and modify it to suit your needs. The fields name
, alias
, and dataverseContacts
are required. The controlled vocabulary for dataverseType
is the following:
DEPARTMENT
JOURNALS
LABORATORY
ORGANIZATIONS_INSTITUTIONS
RESEARCHERS
RESEARCH_GROUP
RESEARCH_PROJECTS
TEACHING_COURSES
UNCATEGORIZED
{
"name": "Scientific Research",
"alias": "science",
"dataverseContacts": [
{
"contactEmail": "pi@example.edu"
},
{
"contactEmail": "student@example.edu"
}
],
"affiliation": "Scientific Research University",
"description": "We do all the science.",
"dataverseType": "LABORATORY"
}
The curl command below assumes you have kept the name “dataverse-complete.json” and that this file is in your current working directory.
Next you need to figure out the alias or database id of the “parent” Dataverse collection into which you will be creating your new Dataverse collection. Out of the box the top level Dataverse collection has an alias of “root” and a database id of “1” but your installation may vary. The easiest way to determine the alias of your root Dataverse collection is to click “Advanced Search” and look at the URL. You may also choose a parent under the root.
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export
below.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PARENT=root
curl -H X-Dataverse-key:$API_TOKEN -X POST $SERVER_URL/api/dataverses/$PARENT --upload-file dataverse-complete.json
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X POST https://demo.dataverse.org/api/dataverses/root --upload-file dataverse-complete.json
You should expect an HTTP 200 response and JSON beginning with “status”:”OK” followed by a representation of the newly-created Dataverse collection.
CORS
View a JSON representation of the Dataverse collection identified by $id
. $id
can be the database ID of the Dataverse collection, its alias, or the special value :root
for the root Dataverse collection.
To view a published Dataverse collection:
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl $SERVER_URL/api/dataverses/$ID
The fully expanded example above (without environment variables) looks like this:
curl https://demo.dataverse.org/api/dataverses/root
To view an unpublished Dataverse collection:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl -H X-Dataverse-key:$API_TOKEN $SERVER_URL/api/dataverses/$ID
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx https://demo.dataverse.org/api/dataverses/root
Before you may delete a Dataverse collection you must first delete or move all of its contents elsewhere.
Deletes the Dataverse collection whose database ID or alias is given:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl -H X-Dataverse-key:$API_TOKEN -X DELETE $SERVER_URL/api/dataverses/$ID
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X DELETE https://demo.dataverse.org/api/dataverses/root
CORS Lists all the Dataverse collections and datasets directly under a Dataverse collection (direct children only, not recursive) specified by database id or alias. If you pass your API token and have access, unpublished Dataverse collections and datasets will be included in the response. The list will be ordered by database id within type of object. That is, all Dataverse collections will be listed first and ordered by database id, then all datasets will be listed ordered by database id.
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export
below.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl -H X-Dataverse-key:$API_TOKEN $SERVER_URL/api/dataverses/$ID/contents
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx https://demo.dataverse.org/api/dataverses/root/contents
Shows the combined size in bytes of all the files uploaded into the Dataverse collection id
:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl -H X-Dataverse-key:$API_TOKEN $SERVER_URL/api/dataverses/$ID/storagesize
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx https://demo.dataverse.org/api/dataverses/root/storagesize
The size of published and unpublished files will be summed both in the Dataverse collection specified and beneath all its sub-collections, recursively.
By default, only the archival files are counted - i.e., the files uploaded by users (plus the tab-delimited versions generated for tabular data files on ingest). If the optional argument includeCached=true
is specified, the API will also add the sizes of all the extra files generated and cached by the Dataverse installation - the resized thumbnail versions for image files, the metadata exports for published datasets, etc.
All the roles defined directly in the Dataverse collection identified by id
:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl -H X-Dataverse-key:$API_TOKEN $SERVER_URL/api/dataverses/$ID/roles
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx https://demo.dataverse.org/api/dataverses/root/roles
CORS
List all the facets for a given Dataverse collection id
:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl -H X-Dataverse-key:$API_TOKEN $SERVER_URL/api/dataverses/$ID/facets
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx https://demo.dataverse.org/api/dataverses/root/facets
Assign search facets for a given Dataverse collection identified by id
:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl -H X-Dataverse-key:$API_TOKEN" -X POST $SERVER_URL/api/dataverses/$ID/facets --upload-file facets.json
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X POST https://demo.dataverse.org/api/dataverses/root/facets --upload-file facets.json
Where facets.json
contains a JSON encoded list of metadata keys (e.g. ["authorName","authorAffiliation"]
).
Creates a new role under Dataverse collection id
. Needs a json file with the role description:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl -H X-Dataverse-key:$API_TOKEN -X POST $SERVER_URL/api/dataverses/$ID/roles --upload-file roles.json
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X POST -H "Content-type:application/json" https://demo.dataverse.org/api/dataverses/root/roles --upload-file roles.json
Where roles.json
looks like this:
{
"alias": "sys1",
"name": “Restricted System Role”,
"description": “A person who may only add datasets.”,
"permissions": [
"AddDataset"
]
}
Note
Only a Dataverse installation account with superuser permissions is allowed to create roles in a Dataverse Collection.
List all the role assignments at the given Dataverse collection:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl -H X-Dataverse-key:$API_TOKEN $SERVER_URL/api/dataverses/$ID/assignments
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx https://demo.dataverse.org/api/dataverses/root/assignments
Assign a default role to a user creating a dataset in a Dataverse collection id
where roleAlias
is the database alias of the role to be assigned:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
export ROLE_ALIAS=curator
curl -H X-Dataverse-key:$API_TOKEN -X PUT $SERVER_URL/api/dataverses/$ID/defaultContributorRole/$ROLE_ALIAS
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X PUT https://demo.dataverse.org/api/dataverses/root/defaultContributorRole/curator
Note: You may use “none” as the ROLE_ALIAS
. This will prevent a user who creates a dataset from having any role on that dataset. It is not recommended for Dataverse collections with human contributors.
Assigns a new role, based on the POSTed JSON:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl -H X-Dataverse-key:$API_TOKEN -X POST -H "Content-Type: application/json" $SERVER_URL/api/dataverses/$ID/assignments --upload-file role.json
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X POST -H "Content-Type: application/json" https://demo.dataverse.org/api/dataverses/root/assignments --upload-file role.json
POSTed JSON example (the content of role.json
file):
{
"assignee": "@uma",
"role": "curator"
}
Delete the assignment whose id is $id
:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
export ASSIGNMENT_ID=6
curl -H X-Dataverse-key:$API_TOKEN -X DELETE $SERVER_URL/api/dataverses/$ID/assignments/$ASSIGNMENT_ID
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X DELETE https://demo.dataverse.org/api/dataverses/root/assignments/6
CORS Get the metadata blocks defined on a Dataverse collection which determine which field are available to authors when they create and edit datasets within that Dataverse collection. This feature is described in General Information section of Dataverse Collection Management of the User Guide.
Please note that an API token is only required if the Dataverse collection has not been published.
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export
below.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl -H X-Dataverse-key:$API_TOKEN $SERVER_URL/api/dataverses/$ID/metadatablocks
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx https://demo.dataverse.org/api/dataverses/root/metadatablocks
You can define the metadata blocks available to authors within a Dataverse collection.
The metadata blocks that are available with a default Dataverse installation are in define-metadatablocks.json
(also shown below) and you should download this file and edit it to meet your needs. Please note that the “citation” metadata block is required. You must have “EditDataverse” permission on the Dataverse collection.
[
"citation",
"geospatial",
"socialscience",
"astrophysics",
"biomedical",
"journal"
]
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export
below.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl -H X-Dataverse-key:$API_TOKEN -X POST $SERVER_URL/api/dataverses/$ID/metadatablocks -H \"Content-type:application/json\" --upload-file define-metadatablocks.json
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X POST -H "Content-type:application/json" --upload-file define-metadatablocks.json https://demo.dataverse.org/api/dataverses/root/metadatablocks
Get whether the Dataverse collection is a metadata block root, or does it uses its parent blocks:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl -H X-Dataverse-key:$API_TOKEN $SERVER_URL/api/dataverses/$ID/metadatablocks/isRoot
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx https://demo.dataverse.org/api/dataverses/root/metadatablocks/isRoot
Set whether the Dataverse collection is a metadata block root, or does it uses its parent blocks. Possible
values are true
and false
(both are valid JSON expressions):
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl -H X-Dataverse-key:$API_TOKEN -X PUT $SERVER_URL/api/dataverses/$ID/metadatablocks/isRoot
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X PUT https://demo.dataverse.org/api/dataverses/root/metadatablocks/isRoot
Note
Previous endpoints $SERVER/api/dataverses/$id/metadatablocks/:isRoot
and POST http://$SERVER/api/dataverses/$id/metadatablocks/:isRoot?key=$apiKey
are deprecated, but supported.
A dataset is a container for files as explained in the Dataset + File Management section of the User Guide.
To create a dataset, you must supply a JSON file that contains at least the following required metadata fields:
As a starting point, you can download dataset-finch1.json
and modify it to meet your needs. (In addition to this minimal example, you can download dataset-create-new-all-default-fields.json
which populates all of the metadata fields that ship with a Dataverse installation.)
The curl command below assumes you have kept the name “dataset-finch1.json” and that this file is in your current working directory.
Next you need to figure out the alias or database id of the “parent” Dataverse collection into which you will be creating your new dataset. Out of the box the top level Dataverse collection has an alias of “root” and a database id of “1” but your installation may vary. The easiest way to determine the alias of your root Dataverse collection is to click “Advanced Search” and look at the URL. You may also choose a parent Dataverse collection under the root Dataverse collection.
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export
below.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export PARENT=root
export SERVER_URL=https://demo.dataverse.org
curl -H X-Dataverse-key:$API_TOKEN -X POST "$SERVER_URL/api/dataverses/$PARENT/datasets" --upload-file dataset-finch1.json
The fully expanded example above (without the environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST "https://demo.dataverse.org/api/dataverses/root/datasets" --upload-file "dataset-finch1.json"
You should expect an HTTP 200 (“OK”) response and JSON indicating the database ID and Persistent ID (PID such as DOI or Handle) that has been assigned to your newly created dataset.
Note
Only a Dataverse installation account with superuser permissions is allowed to include files when creating a dataset via this API. Adding files this way only adds their file metadata to the database, you will need to manually add the physical files to the file system.
Note
This action requires a Dataverse installation account with super-user permissions.
To import a dataset with an existing persistent identifier (PID), the dataset’s metadata should be prepared in Dataverse installation’s native JSON format. The PID is provided as a parameter at the URL. The following line imports a dataset with the PID PERSISTENT_IDENTIFIER
to the Dataverse installation, and then releases it:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export DATAVERSE_ID=root
export PERSISTENT_IDENTIFIER=doi:ZZ7/MOSEISLEYDB94
curl -H X-Dataverse-key:$API_TOKEN -X POST $SERVER_URL/api/dataverses/$DATAVERSE_ID/datasets/:import?pid=$PERSISTENT_IDENTIFIER&release=yes --upload-file dataset.json
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X POST https://demo.dataverse.org/api/dataverses/root/datasets/:import?pid=doi:ZZ7/MOSEISLEYDB94&release=yes --upload-file dataset.json
The pid
parameter holds a persistent identifier (such as a DOI or Handle). The import will fail if no PID is provided, or if the provided PID fails validation.
The optional release
parameter tells the Dataverse installation to immediately publish the dataset. If the parameter is changed to no
, the imported dataset will remain in DRAFT
status.
The JSON format is the same as that supported by the native API’s create dataset command, although it also allows packages. For example:
{
"datasetVersion": {
"termsOfUse": "CC0 Waiver",
"license": "CC0",
"protocol":"doi",
"authority":"10.502",
"identifier":"ZZ7/MOSEISLEYDB94",
"metadataBlocks": {
"citation": {
"fields": [
{
"typeName": "title",
"multiple": false,
"value": "Imported dataset with package files No. 3",
"typeClass": "primitive"
},
{
"typeName": "productionDate",
"multiple": false,
"value": "2011-02-23",
"typeClass": "primitive"
},
{
"typeName": "dsDescription",
"multiple": true,
"value": [
{
"dsDescriptionValue": {
"typeName": "dsDescriptionValue",
"multiple": false,
"value": "Native Dataset",
"typeClass": "primitive"
}
}
],
"typeClass": "compound"
},
{
"typeName": "subject",
"multiple": true,
"value": [
"Medicine, Health and Life Sciences"
],
"typeClass": "controlledVocabulary"
},
{
"typeName": "author",
"multiple": true,
"value": [
{
"authorAffiliation": {
"typeName": "authorAffiliation",
"multiple": false,
"value": "LibraScholar Medical School",
"typeClass": "primitive"
},
"authorName": {
"typeName": "authorName",
"multiple": false,
"value": "Doc, Bob",
"typeClass": "primitive"
}
},
{
"authorAffiliation": {
"typeName": "authorAffiliation",
"multiple": false,
"value": "LibraScholar Medical School",
"typeClass": "primitive"
},
"authorName": {
"typeName": "authorName",
"multiple": false,
"value": "Prof, Arthur",
"typeClass": "primitive"
}
}
],
"typeClass": "compound"
},
{
"typeName": "depositor",
"multiple": false,
"value": "Prof, Arthur",
"typeClass": "primitive"
},
{
"typeName": "datasetContact",
"multiple": true,
"value": [
{
"datasetContactEmail": {
"typeName": "datasetContactEmail",
"multiple": false,
"value": "aprof@mailinator.com",
"typeClass": "primitive"
}
}
],
"typeClass": "compound"
}
],
"displayName": "Citation Metadata"
}
},
"files": [
{
"description": "",
"label": "pub",
"restricted": false,
"version": 1,
"datasetVersionId": 1,
"dataFile": {
"id": 4,
"filename": "pub",
"contentType": "application/vnd.dataverse.file-package",
"filesize": 1698795873,
"description": "",
"storageIdentifier": "162017e5ad5-ee2a2b17fee9",
"originalFormatLabel": "UNKNOWN",
"rootDataFileId": -1,
"checksum": {
"type": "SHA-1",
"value": "54bc7ddb096a490474bd8cc90cbed1c96730f350"
}
}
}
]
}
}
Before calling the API, make sure the data files referenced by the POST
ed JSON are placed in the dataset directory with filenames matching their specified storage identifiers. In installations using POSIX storage, these files must be made readable by the app server user.
Tip
If possible, it’s best to avoid spaces and special characters in the storage identifier in order to avoid potential portability problems. The storage identifier corresponds with the filesystem name (or bucket identifier) of the data file, so these characters may cause unpredictability with filesystem tools.
Warning
Note
This action requires a Dataverse installation account with super-user permissions.
To import a dataset with an existing persistent identifier (PID), you have to provide the PID as a parameter at the URL. The following line imports a dataset with the PID PERSISTENT_IDENTIFIER
to the Dataverse installation, and then releases it:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export DATAVERSE_ID=root
export PERSISTENT_IDENTIFIER=doi:ZZ7/MOSEISLEYDB94
curl -H X-Dataverse-key:$API_TOKEN -X POST $SERVER_URL/api/dataverses/$DATAVERSE_ID/datasets/:importddi?pid=$PERSISTENT_IDENTIFIER&release=yes --upload-file ddi_dataset.xml
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X POST https://demo.dataverse.org/api/dataverses/root/datasets/:importddi?pid=doi:ZZ7/MOSEISLEYDB94&release=yes --upload-file ddi_dataset.xml
The optional pid
parameter holds a persistent identifier (such as a DOI or Handle). The import will fail if the provided PID fails validation.
The optional release
parameter tells the Dataverse installation to immediately publish the dataset. If the parameter is changed to no
, the imported dataset will remain in DRAFT
status.
The file is a DDI xml file.
Warning
In order to publish a Dataverse collection, you must know either its “alias” (which the GUI calls an “identifier”) or its database ID.
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export
below.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl -H X-Dataverse-key:$API_TOKEN -X POST $SERVER_URL/api/dataverses/$ID/actions/:publish
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X POST https://demo.dataverse.org/api/dataverses/root/actions/:publish
You should expect a 200 (“OK”) response and JSON output.
Note Creation of new datasets is done with a POST
onto a Dataverse collection. See the Dataverse Collections section above.
Note In all commands below, dataset versions can be referred to as:
:draft
the draft version, if any:latest
either a draft (if exists) or the latest published version.:latest-published
the latest published versionx.y
a specific version, where x
is the major version number and y
is the minor version number.x
same as x.0
Note
Datasets can be accessed using persistent identifiers. This is done by passing the constant :persistentId
where the numeric id of the dataset is expected, and then passing the actual persistent id as a query parameter with the name persistentId
.
Example: Getting the dataset whose DOI is 10.5072/FK2/J8SJZB:
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_IDENTIFIER=doi:10.5072/FK2/J8SJZB
curl $SERVER_URL/api/datasets/:persistentId/?persistentId=$PERSISTENT_IDENTIFIER
The fully expanded example above (without environment variables) looks like this:
curl https://demo.dataverse.org/api/datasets/:persistentId/?persistentId=doi:10.5072/FK2/J8SJZB
Getting its draft version:
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_IDENTIFIER=doi:10.5072/FK2/J8SJZB
curl http://$SERVER/api/datasets/:persistentId/versions/:draft?persistentId=$PERSISTENT_IDENTIFIER
The fully expanded example above (without environment variables) looks like this:
curl https://demo.dataverse.org/api/datasets/:persistentId/versions/:draft?persistentId=doi:10.5072/FK2/J8SJZB
CORS Show the dataset whose id is passed:
export SERVER_URL=https://demo.dataverse.org
export ID=408730
curl $SERVER_URL/api/datasets/$ID
The fully expanded example above (without environment variables) looks like this:
curl https://demo.dataverse.org/api/datasets/408730
The dataset id can be extracted from the response retrieved from the API which uses the persistent identifier (/api/datasets/:persistentId/?persistentId=$PERSISTENT_IDENTIFIER
).
CORS List versions of the dataset:
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl $SERVER_URL/api/dataverses/$ID/versions
The fully expanded example above (without environment variables) looks like this:
curl https://demo.dataverse.org/api/datasets/24/versions
It returns a list of versions with their metadata, and file list:
{
"status": "OK",
"data": [
{
"id": 7,
"datasetId": 24,
"datasetPersistentId": "doi:10.5072/FK2/U6AEZM",
"storageIdentifier": "file://10.5072/FK2/U6AEZM",
"versionNumber": 2,
"versionMinorNumber": 0,
"versionState": "RELEASED",
"lastUpdateTime": "2015-04-20T09:58:35Z",
"releaseTime": "2015-04-20T09:58:35Z",
"createTime": "2015-04-20T09:57:32Z",
"license": "CC0",
"termsOfUse": "CC0 Waiver",
"termsOfAccess": "You need to request for access.",
"fileAccessRequest": true,
"metadataBlocks": {...},
"files": [...]
},
{
"id": 6,
"datasetId": 24,
"datasetPersistentId": "doi:10.5072/FK2/U6AEZM",
"storageIdentifier": "file://10.5072/FK2/U6AEZM",
"versionNumber": 1,
"versionMinorNumber": 0,
"versionState": "RELEASED",
"UNF": "UNF:6:y4dtFxWhBaPM9K/jlPPuqg==",
"lastUpdateTime": "2015-04-20T09:56:34Z",
"releaseTime": "2015-04-20T09:56:34Z",
"createTime": "2015-04-20T09:43:45Z",
"license": "CC0",
"termsOfUse": "CC0 Waiver",
"termsOfAccess": "You need to request for access.",
"fileAccessRequest": true,
"metadataBlocks": {...},
"files": [...]
}
]
}
CORS Show a version of the dataset. The output includes any metadata blocks the dataset might have:
export SERVER_URL=https://demo.dataverse.org
export ID=24
export VERSION=1.0
curl $SERVER_URL/api/datasets/$ID/versions/$VERSION
The fully expanded example above (without environment variables) looks like this:
curl https://demo.dataverse.org/api/datasets/24/versions/1.0
CORS Export the metadata of the current published version of a dataset in various formats see Note below:
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_IDENTIFIER=doi:10.5072/FK2/J8SJZB
export METADATA_FORMAT=ddi
curl $SERVER_URL/api/datasets/export?exporter=$METADATA_FORMAT&persistentId=PERSISTENT_IDENTIFIER
The fully expanded example above (without environment variables) looks like this:
curl https://demo.dataverse.org/api/datasets/export?exporter=ddi&persistentId=doi:10.5072/FK2/J8SJZB
Note
Supported exporters (export formats) are ddi
, oai_ddi
, dcterms
, oai_dc
, schema.org
, OAI_ORE
, Datacite
, oai_datacite
and dataverse_json
. Descriptive names can be found under Supported Metadata Export Formats in the User Guide.
Please note that the schema.org
format has changed in backwards-incompatible ways after Dataverse Software version 4.9.4:
Both forms are valid according to Google’s Structured Data Testing Tool at https://search.google.com/structured-data/testing-tool . (This tool will report “The property affiliation is not recognized by Google for an object of type Thing” and this known issue is being tracked at https://github.com/IQSS/dataverse/issues/5029 .) Schema.org JSON-LD is an evolving standard that permits a great deal of flexibility. For example, https://schema.org/docs/gs.html#schemaorg_expected indicates that even when objects are expected, it’s ok to just use text. As with all metadata export formats, we will try to keep the Schema.org JSON-LD format your Dataverse installation emits backward-compatible to made integrations more stable, despite the flexibility that’s afforded by the standard.
CORS Lists all the file metadata, for the given dataset and version:
export SERVER_URL=https://demo.dataverse.org
export ID=24
export VERSION=1.0
curl $SERVER_URL/api/datasets/$ID/versions/$VERSION/files
The fully expanded example above (without environment variables) looks like this:
curl https://demo.dataverse.org/api/datasets/24/versions/1.0/files
CORS Provides a crawlable view of files and folders within the given dataset and version:
curl $SERVER_URL/api/datasets/$ID/dirindex/
Optional parameters:
folder
- A subfolder within the dataset (default: top-level view of the dataset)version
- Specifies the version (default: latest published version)original=true
- Download original versions of ingested tabular files.This API outputs a simple html listing, based on the standard Apache directory index, with Access API download links for individual files, and recursive calls to the API above for sub-folders.
Using this API, wget --recursive
(or a similar crawling client) can
be used to download all the files in a dataset, preserving the file
names and folder structure; without having to use the download-as-zip
API. In addition to being faster (zipping is a relatively
resource-intensive operation on the server side), this process can be
restarted if interrupted (with wget --continue
or equivalent) -
unlike zipped multi-file downloads that always have to start from the
beginning.
On a system that uses S3 with download redirects, the individual file downloads will be handled by S3 directly, without having to be proxied through the Dataverse application.
For example, if you have a dataset version with 2 files, one with the folder named “subfolder”:
or, as viewed as a tree on the dataset page:
The output of the API for the top-level folder (/api/datasets/{dataset}/dirindex/
) will be as follows:
with the underlying html source:
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 3.2 Final//EN">
<html><head><title>Index of folder /</title></head>
<body><h1>Index of folder / in dataset doi:XXX/YY/ZZZZ (v. MM)</h1>
<table>
<tr><th>Name</th><th>Last Modified</th><th>Size</th><th>Description</th></tr>
<tr><th colspan="4"><hr></th></tr>
<tr><td><a href="/api/datasets/NNNN/dirindex/?folder=subfolder">subfolder/</a></td><td align="right"> - </td><td align="right"> - </td><td align="right"> </td></tr>
<tr><td><a href="/api/access/datafile/KKKK">testfile.txt</a></td><td align="right">13-January-2021 22:35</td><td align="right">19 B</td><td align="right"> </td></tr>
</table></body></html>
The /dirindex/?folder=subfolder
link above will produce the following view:
with the html source as follows:
<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 3.2 Final//EN">
<html><head><title>Index of folder /subfolder</title></head>
<body><h1>Index of folder /subfolder in dataset doi:XXX/YY/ZZZZ (v. MM)</h1>
<table>
<tr><th>Name</th><th>Last Modified</th><th>Size</th><th>Description</th></tr>
<tr><th colspan="4"><hr></th></tr>
<tr><td><a href="/api/access/datafile/subfolder/LLLL">50by1000.tab</a></td><td align="right">11-January-2021 09:31</td><td align="right">102.5 KB</td><td align="right"> </td></tr>
</table></body></html>
An example of a wget
command line for crawling (“recursive downloading”) of the files and folders in a dataset:
wget -r -e robots=off -nH --cut-dirs=3 --content-disposition https://demo.dataverse.org/api/datasets/24/dirindex/
Note
In addition to the files and folders in the dataset, the command line above will also save the directory index of each folder, in a separate folder “dirindex”.
CORS Lists all the metadata blocks and their content, for the given dataset and version:
export SERVER_URL=https://demo.dataverse.org
export ID=24
export VERSION=1.0
curl $SERVER_URL/api/datasets/$ID/versions/$VERSION/metadata
The fully expanded example above (without environment variables) looks like this:
curl https://demo.dataverse.org/api/datasets/24/versions/1.0/metadata
CORS Lists the metadata block named METADATA_BLOCK, for the given dataset and version:
export SERVER_URL=https://demo.dataverse.org
export ID=24
export VERSION=1.0
export METADATA_BLOCK=citation
curl $SERVER_URL/api/datasets/$ID/versions/$VERSION/metadata/$METADATA_BLOCK
The fully expanded example above (without environment variables) looks like this:
curl https://demo.dataverse.org/api/datasets/24/versions/1.0/metadata/citation
Updates the metadata for a dataset. If a draft of the dataset already exists, the metadata of that draft is overwritten; otherwise, a new draft is created with this metadata.
You must download a JSON representation of the dataset, edit the JSON you download, and then send the updated JSON to the Dataverse installation.
For example, after making your edits, your JSON file might look like dataset-update-metadata.json
which you would send to the Dataverse installation like this:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_IDENTIFIER=doi:10.5072/FK2/BCCP9Z
curl -H "X-Dataverse-key: $API_TOKEN" -X PUT $SERVER_URL/api/datasets/:persistentId/versions/:draft?persistentId=$PERSISTENT_IDENTIFIER --upload-file dataset-update-metadata.json
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X PUT https://demo.dataverse.org/api/datasets/:persistentId/versions/:draft?persistentId=doi:10.5072/FK2/BCCP9Z --upload-file dataset-update-metadata.json
Note that in the example JSON file above, there is a single JSON object with metadataBlocks
as a key. When you download a representation of your dataset in JSON format, the metadataBlocks
object you need is nested inside another object called json
. To extract just the metadataBlocks
key when downloading a JSON representation, you can use a tool such as jq
like this:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_IDENTIFIER=doi:10.5072/FK2/BCCP9Z
curl -H "X-Dataverse-key: $API_TOKEN" $SERVER_URL/api/datasets/:persistentId/versions/:latest?persistentId=$PERSISTENT_IDENTIFIER | jq '.data | {metadataBlocks: .metadataBlocks}' > dataset-update-metadata.json
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" https://demo.dataverse.org/api/datasets/:persistentId/versions/:latest?persistentId=doi:10.5072/FK2/BCCP9Z | jq '.data | {metadataBlocks: .metadataBlocks}' > dataset-update-metadata.json
Now that the resulting JSON file only contains the metadataBlocks
key, you can edit the JSON such as with vi
in the example below:
vi dataset-update-metadata.json
Now that you’ve made edits to the metadata in your JSON file, you can send it to a Dataverse installation as described above.
Alternatively to replacing an entire dataset version with its JSON representation you may add data to dataset fields that are blank or accept multiple values with the following:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_IDENTIFIER=doi:10.5072/FK2/BCCP9Z
curl -H "X-Dataverse-key: $API_TOKEN" -X PUT $SERVER_URL/api/datasets/:persistentId/editMetadata/?persistentId=$PERSISTENT_IDENTIFIER --upload-file dataset-add-metadata.json
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X PUT https://demo.dataverse.org/api/datasets/:persistentId/editMetadata/?persistentId=doi:10.5072/FK2/BCCP9Z --upload-file dataset-add-metadata.json
You may also replace existing metadata in dataset fields with the following (adding the parameter replace=true):
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_IDENTIFIER=doi:10.5072/FK2/BCCP9Z
curl -H "X-Dataverse-key: $API_TOKEN" -X PUT $SERVER_URL/api/datasets/:persistentId/editMetadata?persistentId=$PERSISTENT_IDENTIFIER&replace=true --upload-file dataset-update-metadata.json
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X PUT https://demo.dataverse.org/api/datasets/:persistentId/editMetadata/?persistentId=doi:10.5072/FK2/BCCP9Z&replace=true --upload-file dataset-update-metadata.json
For these edits your JSON file need only include those dataset fields which you would like to edit. A sample JSON file may be downloaded here: dataset-edit-metadata-sample.json
You may delete some of the metadata of a dataset version by supplying a file with a JSON representation of dataset fields that you would like to delete with the following:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_IDENTIFIER=doi:10.5072/FK2/BCCP9Z
curl -H "X-Dataverse-key: $API_TOKEN" -X PUT $SERVER_URL/api/datasets/:persistentId/deleteMetadata/?persistentId=$PERSISTENT_IDENTIFIER --upload-file dataset-delete-author-metadata.json
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X PUT https://demo.dataverse.org/api/datasets/:persistentId/deleteMetadata/?persistentId=doi:10.5072/FK2/BCCP9Z --upload-file dataset-delete-author-metadata.json
For these deletes your JSON file must include an exact match of those dataset fields which you would like to delete. A sample JSON file may be downloaded here: dataset-delete-author-metadata.json
When publishing a dataset it’s good to be aware of the Dataverse Software’s versioning system, which is described in the Dataset + File Management section of the User Guide.
If this is the first version of the dataset, its version number will be set to 1.0
. Otherwise, the new dataset version number is determined by the most recent version number and the type
parameter. Passing type=minor
increases the minor version number (2.3 is updated to 2.4). Passing type=major
increases the major version number (2.3 is updated to 3.0). (Superusers can pass type=updatecurrent
to update metadata without changing the version number.)
This call also supports an optional boolean query parameter: assureIsIndexed
. If true, the call will fail with a 409 (“CONFLICT”) response if the dataset is awaiting re-indexing. If indexing occurs during publishing it could cause the publish request to fail, after a 202 response has been received. Using this parameter allows the caller to wait for indexing to occur and avoid this possibility. It is most useful in situations where edits are made immediately before publication.
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export
below.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/J8SJZB
export MAJOR_OR_MINOR=major
curl -H "X-Dataverse-key: $API_TOKEN" -X POST "$SERVER_URL/api/datasets/:persistentId/actions/:publish?persistentId=$PERSISTENT_ID&type=$MAJOR_OR_MINOR"
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST "https://demo.dataverse.org/api/datasets/:persistentId/actions/:publish?persistentId=doi:10.5072/FK2/J8SJZB&type=major"
The quotes around the URL are required because there is more than one query parameter separated by an ampersand (&
), which has special meaning to Unix shells such as Bash. Putting the &
in quotes ensures that “type” is interpreted as one of the query parameters.
You should expect JSON output and a 200 (“OK”) response in most cases. If you receive a 202 (“ACCEPTED”) response, this is normal for installations that have workflows configured. Workflows are described in the Workflows section of the Developer Guide. A 409 (“CONFLICT”) response is also possible if you set assureIsIndexed=true
. (In this case, one could then repeat the call until a 200/202 response is sent.)
Note
POST should be used to publish a dataset. GET is supported for backward compatibility but is deprecated and may be removed: https://github.com/IQSS/dataverse/issues/2431
Deletes the draft version of dataset $ID
. Only the draft version can be deleted:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key: $API_TOKEN" -X DELETE $SERVER_URL/api/datasets/$ID/versions/:draft
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X DELETE https://demo.dataverse.org/api/datasets/24/versions/:draft
Sets the dataset citation date field type for a given dataset. :publicationDate
is the default.
Note that the dataset citation date field type must be a date field.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_IDENTIFIER=doi:10.5072/FK2/J8SJZB
export DATASET_FIELD_TYPE_NAME=dateOfDeposit
curl -H "X-Dataverse-key: $API_TOKEN" -X PUT $SERVER_URL/api/datasets/:persistentId/citationdate?persistentId=$PERSISTENT_IDENTIFIER --data "$DATASET_FIELD_TYPE_NAME"
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X PUT https://demo.dataverse.org/api/datasets/:persistentId/citationdate?persistentId=doi:10.5072/FK2/J8SJZB --data "dateOfDeposit"
Restores the default citation date field type, :publicationDate
, for a given dataset.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_IDENTIFIER=doi:10.5072/FK2/J8SJZB
curl -H "X-Dataverse-key: $API_TOKEN" -X DELETE $SERVER_URL/api/datasets/:persistentId/citationdate?persistentId=$PERSISTENT_IDENTIFIER
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X DELETE https://demo.dataverse.org/api/datasets/:persistentId/citationdate?persistentId=doi:10.5072/FK2/J8SJZB
Lists all role assignments on a given dataset:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=2347
curl -H X-Dataverse-key:$API_TOKEN $SERVER_URL/api/datasets/$ID/assignments
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx https://demo.dataverse.org/api/datasets/2347/assignments
Assigns a new role, based on the POSTed JSON:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=2347
curl -H X-Dataverse-key:$API_TOKEN -X POST -H "Content-Type: application/json" $SERVER_URL/api/datasets/$ID/assignments --upload-file role.json
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X POST -H "Content-Type: application/json" https://demo.dataverse.org/api/datasets/2347/assignments --upload-file role.json
POSTed JSON example (the content of role.json
file):
{
"assignee": "@uma",
"role": "curator"
}
Delete the assignment whose id is $id
:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=2347
export ASSIGNMENT_ID=6
curl -H X-Dataverse-key:$API_TOKEN -X DELETE $SERVER_URL/api/datasets/$ID/assignments/$ASSIGNMENT_ID
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X DELETE https://demo.dataverse.org/api/datasets/2347/assignments/6
Create a Private URL (must be able to manage dataset permissions):
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key: $API_TOKEN" -X POST $SERVER_URL/api/datasets/$ID/privateUrl
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST https://demo.dataverse.org/api/datasets/24/privateUrl
Get a Private URL from a dataset (if available):
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key: $API_TOKEN" $SERVER_URL/api/datasets/$ID/privateUrl
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" https://demo.dataverse.org/api/datasets/24/privateUrl
Delete a Private URL from a dataset (if it exists):
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key: $API_TOKEN" -X DELETE $SERVER_URL/api/datasets/$ID/privateUrl
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X DELETE https://demo.dataverse.org/api/datasets/24/privateUrl
When adding a file to a dataset, you can optionally specify the following:
In the curl example below, all of the above are specified but they are optional.
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export
below.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export FILENAME='data.tsv'
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/J8SJZB
curl -H X-Dataverse-key:$API_TOKEN -X POST -F "file=@$FILENAME" -F 'jsonData={"description":"My description.","directoryLabel":"data/subdir1","categories":["Data"], "restrict":"false"}' "$SERVER_URL/api/datasets/:persistentId/add?persistentId=$PERSISTENT_ID"
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X POST -F file=@data.tsv -F 'jsonData={"description":"My description.","directoryLabel":"data/subdir1","categories":["Data"], "restrict":"false"}' "https://demo.dataverse.org/api/datasets/:persistentId/add?persistentId=doi:10.5072/FK2/J8SJZB"
You should expect a 201 (“CREATED”) response and JSON indicating the database id that has been assigned to your newly uploaded file.
Please note that it’s possible to “trick” a Dataverse installation into giving a file a content type (MIME type) of your choosing. For example, you can make a text file be treated like a video file with -F 'file=@README.txt;type=video/mpeg4'
, for example. If the Dataverse installation does not properly detect a file type, specifying the content type via API like this a potential workaround.
The curl syntax above to upload a file is tricky and a Python version is provided below. (Please note that it depends on libraries such as “requests” that you may need to install but this task is out of scope for this guide.) Here are some parameters you can set in the script:
dataverse_server
- e.g. https://demo.dataverse.orgapi_key
- See the top of this document for a descriptionpersistentId
- Example: doi:10.5072/FK2/6XACVA
dataset_id
- Database id of the datasetIn practice, you only need one the dataset_id
or the persistentId
. The example below shows both uses.
from datetime import datetime
import json
import requests # http://docs.python-requests.org/en/master/
# --------------------------------------------------
# Update the 4 params below to run this code
# --------------------------------------------------
dataverse_server = 'https://your dataverse installation' # no trailing slash
api_key = 'api key'
dataset_id = 1 # database id of the dataset
persistentId = 'doi:10.5072/FK2/6XACVA' # doi or hdl of the dataset
# --------------------------------------------------
# Prepare "file"
# --------------------------------------------------
file_content = 'content: %s' % datetime.now()
files = {'file': ('sample_file.txt', file_content)}
# --------------------------------------------------
# Using a "jsonData" parameter, add optional description + file tags
# --------------------------------------------------
params = dict(description='Blue skies!',
categories=['Lily', 'Rosemary', 'Jack of Hearts'])
params_as_json_string = json.dumps(params)
payload = dict(jsonData=params_as_json_string)
# --------------------------------------------------
# Add file using the Dataset's id
# --------------------------------------------------
url_dataset_id = '%s/api/datasets/%s/add?key=%s' % (dataverse_server, dataset_id, api_key)
# -------------------
# Make the request
# -------------------
print '-' * 40
print 'making request: %s' % url_dataset_id
r = requests.post(url_dataset_id, data=payload, files=files)
# -------------------
# Print the response
# -------------------
print '-' * 40
print r.json()
print r.status_code
# --------------------------------------------------
# Add file using the Dataset's persistentId (e.g. doi, hdl, etc)
# --------------------------------------------------
url_persistent_id = '%s/api/datasets/:persistentId/add?persistentId=%s&key=%s' % (dataverse_server, persistentId, api_key)
# -------------------
# Update the file content to avoid a duplicate file error
# -------------------
file_content = 'content2: %s' % datetime.now()
files = {'file': ('sample_file2.txt', file_content)}
# -------------------
# Make the request
# -------------------
print '-' * 40
print 'making request: %s' % url_persistent_id
r = requests.post(url_persistent_id, data=payload, files=files)
# -------------------
# Print the response
# -------------------
print '-' * 40
print r.json()
print r.status_code
Shows the combined size in bytes of all the files uploaded into the dataset id
.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H X-Dataverse-key:$API_TOKEN $SERVER_URL/api/datasets/$ID/storagesize
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx https://demo.dataverse.org/api/datasets/24/storagesize
The size of published and unpublished files will be summed in the dataset specified.
By default, only the archival files are counted - i.e., the files uploaded by users (plus the tab-delimited versions generated for tabular data files on ingest). If the optional argument includeCached=true
is specified, the API will also add the sizes of all the extra files generated and cached by the Dataverse installation - the resized thumbnail versions for image files, the metadata exports for published datasets, etc. Because this deals with unpublished files the token supplied must have permission to view unpublished drafts.
Shows the combined size in bytes of all the files available for download from version versionId
of dataset id
.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
export VERSIONID=1.0
curl -H X-Dataverse-key:$API_TOKEN $SERVER_URL/api/datasets/$ID/versions/$VERSIONID/downloadsize
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx https://demo.dataverse.org/api/datasets/24/versions/1.0/downloadsize
The size of all files available for download will be returned. If :draft is passed as versionId the token supplied must have permission to view unpublished drafts. A token is not required for published datasets. Also restricted files will be included in this total regardless of whether the user has access to download the restricted file(s).
When dataset authors do not have permission to publish directly, they can click the “Submit for Review” button in the web interface (see Dataset + File Management), or perform the equivalent operation via API:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/J8SJZB
curl -H "X-Dataverse-key: $API_TOKEN" -X POST "$SERVER_URL/api/datasets/:persistentId/submitForReview?persistentId=$PERSISTENT_ID"
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST "https://demo.dataverse.org/api/datasets/:persistentId/submitForReview?persistentId=doi:10.5072/FK2/J8SJZB"
The people who need to review the dataset (often curators or journal editors) can check their notifications periodically via API to see if any new datasets have been submitted for review and need their attention. See the Notifications section for details. Alternatively, these curators can simply check their email or notifications to know when datasets have been submitted (or resubmitted) for review.
After the curators or journal editors have reviewed a dataset that has been submitted for review (see “Submit for Review”, above) they can either choose to publish the dataset (see the :publish
“action” above) or return the dataset to its authors. In the web interface there is a “Return to Author” button (see Dataset + File Management), but the interface does not provide a way to explain why the dataset is being returned. There is a way to do this outside of this interface, however. Instead of clicking the “Return to Author” button in the UI, a curator can write a “reason for return” into the database via API.
Here’s how curators can send a “reason for return” to the dataset authors. First, the curator creates a JSON file that contains the reason for return:
{
"reasonForReturn": "You forgot to upload any files."
}
In the example below, the curator has saved the JSON file as reason-for-return.json
in their current working directory. Then, the curator sends this JSON file to the returnToAuthor
API endpoint like this:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/J8SJZB
curl -H "X-Dataverse-key: $API_TOKEN" -X POST "$SERVER_URL/api/datasets/:persistentId/returnToAuthor?persistentId=$PERSISTENT_ID" -H "Content-type: application/json" -d @reason-for-return.json
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST "https://demo.dataverse.org/api/datasets/:persistentId/returnToAuthor?persistentId=doi:10.5072/FK2/J8SJZB" -H "Content-type: application/json" -d @reason-for-return.json
The review process can sometimes resemble a tennis match, with the authors submitting and resubmitting the dataset over and over until the curators are satisfied. Each time the curators send a “reason for return” via API, that reason is persisted into the database, stored at the dataset version level.
Creates a link between a dataset and a Dataverse collection (see Dataset Linking section of Dataverse Collection Management in the User Guide for more information):
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export DATASET_ID=24
export DATAVERSE_ID=test
curl -H "X-Dataverse-key: $API_TOKEN" -X PUT $SERVER_URL/api/datasets/$DATASET_ID/link/$DATAVERSE_ID
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X PUT https://demo.dataverse.org/api/datasets/24/link/test
To check if a dataset is locked:
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl $SERVER_URL/api/datasets/$ID/locks
The fully expanded example above (without environment variables) looks like this:
curl https://demo.dataverse.org/api/datasets/24/locks
Optionally, you can check if there’s a lock of a specific type on the dataset:
export SERVER_URL=https://demo.dataverse.org
export ID=24
export LOCK_TYPE=Ingest
curl "$SERVER_URL/api/datasets/$ID/locks?type=$LOCK_TYPE"
The fully expanded example above (without environment variables) looks like this:
curl "https://demo.dataverse.org/api/datasets/24/locks?type=Ingest"
Currently implemented lock types are Ingest
, Workflow
, InReview
, DcmUpload
, pidRegister
, and EditInProgress
.
The API will output the list of locks, for example:
{"status":"OK","data":
[
{
"lockType":"Ingest",
"date":"Fri Aug 17 15:05:51 EDT 2018",
"user":"dataverseAdmin"
},
{
"lockType":"Workflow",
"date":"Fri Aug 17 15:02:00 EDT 2018",
"user":"dataverseAdmin"
}
]
}
If the dataset is not locked (or if there is no lock of the requested type), the API will return an empty list.
The following API end point will lock a Dataset with a lock of specified type. Note that this requires “superuser” credentials:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
export LOCK_TYPE=Ingest
curl -H "X-Dataverse-key: $API_TOKEN" -X POST $SERVER_URL/api/datasets/$ID/lock/$LOCK_TYPE
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST https://demo.dataverse.org/api/datasets/24/lock/Ingest
Use the following API to unlock the dataset, by deleting all the locks currently on the dataset. Note that this requires “superuser” credentials:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key: $API_TOKEN" -X DELETE $SERVER_URL/api/datasets/$ID/locks
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X DELETE https://demo.dataverse.org/api/datasets/24/locks
Or, to delete a lock of the type specified only. Note that this requires “superuser” credentials:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
export LOCK_TYPE=pidRegister
curl -H "X-Dataverse-key: $API_TOKEN" -X DELETE $SERVER_URL/api/datasets/$ID/locks?type=$LOCK_TYPE
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X DELETE https://demo.dataverse.org/api/datasets/24/locks?type=pidRegister
If the dataset is not locked (or if there is no lock of the specified type), the API will exit with a warning message.
(Note that the API calls above all support both the database id and persistent identifier notation for referencing the dataset)
Please note that these dataset level metrics are only available if support for Make Data Count has been enabled in your Dataverse installation. See the Dataset Metrics in the Dataset + File Management section of the User Guide and the Make Data Count section of the Admin Guide for details.
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export
below.
export SERVER_URL=https://demo.dataverse.org
To confirm that the environment variable was set properly, you can use echo
like this:
echo $SERVER_URL
Please note that for each of these endpoints except the “citations” endpoint, you can optionally pass the query parameter “country” with a two letter code (e.g. “country=us”) and you can specify a particular month by adding it in yyyy-mm format after the requested metric (e.g. “viewsTotal/2019-02”).
Please note that “viewsTotal” is a combination of “viewsTotalRegular” and “viewsTotalMachine” which can be requested separately.
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/J8SJZB
curl "$SERVER_URL/api/datasets/:persistentId/makeDataCount/viewsTotal?persistentId=$PERSISTENT_ID"
The fully expanded example above (without environment variables) looks like this:
curl "https://demo.dataverse.org/api/datasets/:persistentId/makeDataCount/viewsTotal?persistentId=10.5072/FK2/J8SJZB"
Please note that “viewsUnique” is a combination of “viewsUniqueRegular” and “viewsUniqueMachine” which can be requested separately.
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/J8SJZB
curl "$SERVER_URL/api/datasets/:persistentId/makeDataCount/viewsUnique?persistentId=$PERSISTENT_ID"
The fully expanded example above (without environment variables) looks like this:
curl "https://demo.dataverse.org/api/datasets/:persistentId/makeDataCount/viewsUnique?persistentId=10.5072/FK2/J8SJZB"
Please note that “downloadsTotal” is a combination of “downloadsTotalRegular” and “downloadsTotalMachine” which can be requested separately.
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/J8SJZB
curl "$SERVER_URL/api/datasets/:persistentId/makeDataCount/downloadsTotal?persistentId=$PERSISTENT_ID"
The fully expanded example above (without environment variables) looks like this:
curl "https://demo.dataverse.org/api/datasets/:persistentId/makeDataCount/downloadsTotal?persistentId=10.5072/FK2/J8SJZB"
Please note that “downloadsUnique” is a combination of “downloadsUniqueRegular” and “downloadsUniqueMachine” which can be requested separately.
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/J8SJZB
curl "$SERVER_URL/api/datasets/:persistentId/makeDataCount/downloadsUnique?persistentId=$PERSISTENT_ID"
The fully expanded example above (without environment variables) looks like this:
curl "https://demo.dataverse.org/api/datasets/:persistentId/makeDataCount/downloadsUnique?persistentId=10.5072/FK2/J8SJZB"
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/J8SJZB
curl "$SERVER_URL/api/datasets/:persistentId/makeDataCount/citations?persistentId=$PERSISTENT_ID"
The fully expanded example above (without environment variables) looks like this:
curl "https://demo.dataverse.org/api/datasets/:persistentId/makeDataCount/citations?persistentId=10.5072/FK2/J8SJZB"
Delete the dataset whose id is passed:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key: $API_TOKEN" -X DELETE $SERVER_URL/api/datasets/$ID
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X DELETE https://demo.dataverse.org/api/datasets/24
Normally published datasets should not be deleted, but there exists a “destroy” API endpoint for superusers which will act on a dataset given a persistent ID or dataset database ID:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/AAA000
curl -H "X-Dataverse-key: $API_TOKEN" -X DELETE $SERVER_URL/api/datasets/:persistentId/destroy/?persistentId=$PERSISTENT_ID
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X DELETE https://demo.dataverse.org/api/datasets/:persistentId/destroy/?persistentId=doi:10.5072/FK2/AAA000
Delete with dataset identifier:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key: $API_TOKEN" -X DELETE $SERVER_URL/api/datasets/$ID/destroy
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key: xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X DELETE https://demo.dataverse.org/api/datasets/24/destroy
Calling the destroy endpoint is permanent and irreversible. It will remove the dataset and its datafiles, then re-index the parent Dataverse collection in Solr. This endpoint requires the API token of a superuser.
/api/datasets/$dataset-id/storageDriver
can be used to check, configure or reset the designated file store (storage driver) for a dataset. Please see the Managing Datasets and Dataverse Collections section of the guide for more information on this API.
/api/datasets/$dataset-id/timestamps
can be used to view timestamps associated with various events in the dataset’s lifecycle. For published datasets, this API call provides the createTime
, publicationTime
, lastMetadataExportTime
and lastMajorVersionReleaseTime
, as well as two booleans - hasStaleIndex
and hasStalePermissionIndex
- which, if false, indicate the Dataverse displays for the dataset are up-to-date. The response is application/json
with the timestamps included in the returned data
object.
When called by a user who can view the draft version of the dataset, additional timestamps are reported: lastUpdateTime
, lastIndexTime
, lastPermissionUpdateTime
, and globalIdCreateTime
.
One use case where this API call could be useful is in allowing an external application to poll and wait for changes being made by the Dataverse software or other external tool to complete prior to continuing its own processing.
Note
Files can be added via the native API but the operation is performed on the parent object, which is a dataset. Please see the Datasets endpoint above for more information.
Note
Access API has its own section in the Guide: Data Access API
Note Data Access API calls can now be made using persistent identifiers (in addition to database ids). This is done by passing the constant :persistentId
where the numeric id of the file is expected, and then passing the actual persistent id as a query parameter with the name persistentId
.
Example: Getting the file whose DOI is 10.5072/FK2/J8SJZB
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/J8SJZB
curl "$SERVER_URL/api/access/datafile/:persistentId/?persistentId=$PERSISTENT_ID"
The fully expanded example above (without environment variables) looks like this:
curl "https://demo.dataverse.org/api/access/datafile/:persistentId/?persistentId=doi:10.5072/FK2/J8SJZB"
Note: you can use the combination of cURL’s -J
(--remote-header-name
) and -O
(--remote-name
) options to save the file in its original file name, such as
curl -J -O "https://demo.dataverse.org/api/access/datafile/:persistentId/?persistentId=doi:10.5072/FK2/J8SJZB"
Restrict or unrestrict an existing file where id
is the database id of the file or pid
is the persistent id (DOI or Handle) of the file to restrict. Note that some Dataverse installations do not allow the ability to restrict files.
A curl example using an id
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key:$API_TOKEN" -X PUT -d true $SERVER_URL/api/files/$ID/restrict
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X PUT -d true https://demo.dataverse.org/api/files/24/restrict
A curl example using a pid
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/AAA000
curl -H "X-Dataverse-key:$API_TOKEN" -X PUT -d true $SERVER_URL/api/files/:persistentId/restrict?persistentId=$PERSISTENT_ID
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X PUT -d true "https://demo.dataverse.org/api/files/:persistentId/restrict?persistentId=doi:10.5072/FK2/AAA000"
Reverse the tabular data ingest process performed on a file where ID
is the database id or PERSISTENT_ID
is the persistent id (DOI or Handle) of the file to process. Note that this requires “superuser” credentials.
A curl example using an ID
:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key:$API_TOKEN" -X POST $SERVER_URL/api/files/$ID/uningest
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST https://demo.dataverse.org/api/files/24/uningest
A curl example using a PERSISTENT_ID
:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/AAA000
curl -H "X-Dataverse-key:$API_TOKEN" -X POST "$SERVER_URL/api/files/:persistentId/uningest?persistentId=$PERSISTENT_ID"
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST "https://demo.dataverse.org/api/files/:persistentId/uningest?persistentId=doi:10.5072/FK2/AAA000"
Attempt to ingest an existing datafile as tabular data. This API can be used on a file that was not ingested as tabular back when it was uploaded. For example, a Stata v.14 file that was uploaded before ingest support for Stata 14 was added (in Dataverse Software v.4.9). It can also be used on a file that failed to ingest due to a bug in the ingest plugin that has since been fixed (hence the name “reingest”).
Note that this requires “superuser” credentials.
A curl example using an ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key:$API_TOKEN" -X POST $SERVER_URL/api/files/$ID/reingest
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST https://demo.dataverse.org/api/files/24/reingest
A curl example using a PERSISTENT_ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/AAA000
curl -H "X-Dataverse-key:$API_TOKEN" -X POST $SERVER_URL/api/files/:persistentId/reingest?persistentId=$PERSISTENT_ID
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST "https://demo.dataverse.org/api/files/:persistentId/reingest?persistentId=doi:10.5072/FK2/AAA000"
Note: at present, the API cannot be used on a file that’s already successfully ingested as tabular.
The Dataverse Software uses a variety of methods for determining file types (MIME types or content types) and these methods (listed below) are updated periodically. If you have files that have an unknown file type, you can have the Dataverse Software attempt to redetect the file type.
When using the curl command below, you can pass dryRun=true
if you don’t want any changes to be saved to the database. Change this to dryRun=false
(or omit it) to save the change.
A curl example using an id
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key:$API_TOKEN" -X POST "$SERVER_URL/api/files/$ID/redetect?dryRun=true"
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST "https://demo.dataverse.org/api/files/24/redetect?dryRun=true"
A curl example using a pid
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/AAA000
curl -H "X-Dataverse-key:$API_TOKEN" -X POST "$SERVER_URL/api/files/:persistentId/redetect?persistentId=$PERSISTENT_ID&dryRun=true"
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST "https://demo.dataverse.org/api/files/:persistentId/redetect?persistentId=doi:10.5072/FK2/AAA000&dryRun=true"
Currently the following methods are used to detect file types:
MimeTypeDetectionByFileExtension.properties
.Replace an existing file where ID
is the database id of the file to replace or PERSISTENT_ID
is the persistent id (DOI or Handle) of the file. Requires the file
to be passed as well as a jsonString
expressing the new metadata. Note that metadata such as description, directoryLabel (File Path) and tags are not carried over from the file being replaced.
A curl example using an ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key:$API_TOKEN" -X POST -F 'file=@file.extension' -F 'jsonData={json}' $SERVER_URL/api/files/$ID/replace
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST -F 'file=@data.tsv' \
-F 'jsonData={"description":"My description.","categories":["Data"],"forceReplace":false}' \
https://demo.dataverse.org/api/files/24/replace
A curl example using a PERSISTENT_ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/AAA000
curl -H "X-Dataverse-key:$API_TOKEN" -X POST -F 'file=@file.extension' -F 'jsonData={json}' \
"$SERVER_URL/api/files/:persistentId/replace?persistentId=$PERSISTENT_ID"
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST -F 'file=@data.tsv' \
-F 'jsonData={"description":"My description.","categories":["Data"],"forceReplace":false}' \
"https://demo.dataverse.org/api/files/:persistentId/replace?persistentId=doi:10.5072/FK2/AAA000"
Provides a json representation of the file metadata for an existing file where ID
is the database id of the file to get metadata from or PERSISTENT_ID
is the persistent id (DOI or Handle) of the file.
A curl example using an ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl $SERVER_URL/api/files/$ID/metadata
The fully expanded example above (without environment variables) looks like this:
curl https://demo.dataverse.org/api/files/24/metadata
A curl example using a PERSISTENT_ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/AAA000
curl "$SERVER_URL/api/files/:persistentId/metadata?persistentId=$PERSISTENT_ID"
The fully expanded example above (without environment variables) looks like this:
curl "https://demo.dataverse.org/api/files/:persistentId/metadata?persistentId=doi:10.5072/FK2/AAA000"
The current draft can also be viewed if you have permissions and pass your API token
A curl example using an ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key:$API_TOKEN" $SERVER_URL/api/files/$ID/metadata/draft
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" https://demo.dataverse.org/api/files/24/metadata/draft
A curl example using a PERSISTENT_ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/AAA000
curl -H "X-Dataverse-key:$API_TOKEN" "$SERVER_URL/api/files/:persistentId/metadata/draft?persistentId=$PERSISTENT_ID"
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" "https://demo.dataverse.org/api/files/:persistentId/metadata/draft?persistentId=doi:10.5072/FK2/AAA000"
Note: The id
returned in the json response is the id of the file metadata version.
Updates the file metadata for an existing file where ID
is the database id of the file to update or PERSISTENT_ID
is the persistent id (DOI or Handle) of the file. Requires a jsonString
expressing the new metadata. No metadata from the previous version of this file will be persisted, so if you want to update a specific field first get the json with the above command and alter the fields you want.
A curl example using an ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key:$API_TOKEN" -X POST \
-F 'jsonData={"description":"My description bbb.","provFreeform":"Test prov freeform","categories":["Data"],"restrict":false}' \
$SERVER_URL/api/files/$ID/metadata
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST \
-F 'jsonData={"description":"My description bbb.","provFreeform":"Test prov freeform","categories":["Data"],"restrict":false}' \
http://demo.dataverse.org/api/files/24/metadata
A curl example using a PERSISTENT_ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/AAA000
curl -H "X-Dataverse-key:$API_TOKEN" -X POST \
-F 'jsonData={"description":"My description bbb.","provFreeform":"Test prov freeform","categories":["Data"],"restrict":false}' \
"$SERVER_URL/api/files/:persistentId/metadata?persistentId=$PERSISTENT_ID"
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST \
-F 'jsonData={"description":"My description bbb.","provFreeform":"Test prov freeform","categories":["Data"],"restrict":false}' \
"https://demo.dataverse.org/api/files/:persistentId/metadata?persistentId=doi:10.5072/FK2/AAA000"
Also note that dataFileTags are not versioned and changes to these will update the published version of the file.
Updates variable level metadata using ddi xml FILE
, where ID
is file id.
A curl example using an ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
export FILE=dct.xml
curl -H "X-Dataverse-key:$API_TOKEN" -X PUT $SERVER_URL/api/edit/$ID --upload-file $FILE
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X PUT https://demo.dataverse.org/api/edit/24 --upload-file dct.xml
You can download dct.xml
from the example above to see what the XML looks like.
A curl example using an ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key:$API_TOKEN" $SERVER_URL/api/files/$ID/prov-json
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" https://demo.dataverse.org/api/files/24/prov-json
A curl example using a PERSISTENT_ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/AAA000
curl -H "X-Dataverse-key:$API_TOKEN" "$SERVER_URL/api/files/:persistentId/prov-json?persistentId=$PERSISTENT_ID"
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" "https://demo.dataverse.org/api/files/:persistentId/prov-json?persistentId=doi:10.5072/FK2/AAA000"
A curl example using an ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key:$API_TOKEN" $SERVER_URL/api/files/$ID/prov-freeform
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" https://demo.dataverse.org/api/files/24/prov-freeform
A curl example using a PERSISTENT_ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/AAA000
curl -H "X-Dataverse-key:$API_TOKEN" "$SERVER_URL/api/files/:persistentId/prov-freeform?persistentId=$PERSISTENT_ID"
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" "https://demo.dataverse.org/api/files/:persistentId/prov-freeform?persistentId=doi:10.5072/FK2/AAA000"
Requires a JSON file with the description connected to a key named “text”
A curl example using an ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
export FILE_PATH=provenance.json
curl -H "X-Dataverse-key:$API_TOKEN" -X POST $SERVER_URL/api/files/$ID/prov-freeform -H "Content-type:application/json" --upload-file $FILE_PATH
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST https://demo.dataverse.org/api/files/24/prov-freeform -H "Content-type:application/json" --upload-file provenance.json
A curl example using a PERSISTENT_ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/AAA000
export FILE_PATH=provenance.json
curl -H "X-Dataverse-key:$API_TOKEN" -X POST "$SERVER_URL/api/files/:persistentId/prov-freeform?persistentId=$PERSISTENT_ID" -H "Content-type:application/json" --upload-file $FILE_PATH
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X POST "https://demo.dataverse.org/api/files/:persistentId/prov-freeform?persistentId=doi:10.5072/FK2/AAA000" -H "Content-type:application/json" --upload-file provenance.json
See a sample JSON file file-provenance.json
from http://openprovenance.org (c.f. Huynh, Trung Dong and Moreau, Luc (2014) ProvStore: a public provenance repository. At 5th International Provenance and Annotation Workshop (IPAW‘14), Cologne, Germany, 09-13 Jun 2014. pp. 275-277).
A curl example using an ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key:$API_TOKEN" -X DELETE $SERVER_URL/api/files/$ID/prov-json
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X DELETE https://demo.dataverse.org/api/files/24/prov-json
A curl example using a PERSISTENT_ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PERSISTENT_ID=doi:10.5072/FK2/AAA000
curl -H "X-Dataverse-key:$API_TOKEN" -X DELETE "$SERVER_URL/api/files/:persistentId/prov-json?persistentId=$PERSISTENT_ID"
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X DELETE "https://demo.dataverse.org/api/files/:persistentId/prov-json?persistentId=doi:10.5072/FK2/AAA000"
Starting the release 4.10 the size of the saved original file (for an ingested tabular datafile) is stored in the database. The following API will retrieve and permanently store the sizes for any already existing saved originals:
export SERVER_URL=https://localhost
curl $SERVER_URL/api/admin/datafiles/integrity/fixmissingoriginalsizes
with limit parameter:
export SERVER_URL=https://localhost
export LIMIT=10
curl "$SERVER_URL/api/admin/datafiles/integrity/fixmissingoriginalsizes?limit=$LIMIT"
The fully expanded example above (without environment variables) looks like this:
curl https://localhost/api/admin/datafiles/integrity/fixmissingoriginalsizes"
with limit parameter:
curl https://localhost/api/admin/datafiles/integrity/fixmissingoriginalsizes?limit=10"
Note the optional “limit” parameter. Without it, the API will attempt to populate the sizes for all the saved originals that don’t have them in the database yet. Otherwise it will do so for the first N such datafiles.
By default, the admin API calls are blocked and can only be called from localhost. See more details in :BlockedApiEndpoints and :BlockedApiPolicy settings in Configuration.
The following endpoints will allow users to manage their API tokens.
In order to obtain the expiration date of a token use:
curl -H X-Dataverse-key:$API_TOKEN -X GET $SERVER_URL/api/users/token
In order to obtain a new token use:
curl -H X-Dataverse-key:$API_TOKEN -X POST $SERVER_URL/api/users/token/recreate
In order to delete a token use:
curl -H X-Dataverse-key:$API_TOKEN -X DELETE $SERVER_URL/api/users/token
Builtin users are known as “Username/Email and Password” users in the Account Creation + Management of the User Guide. The Dataverse installation stores a password (encrypted, of course) for these users, which differs from “remote” users such as Shibboleth or OAuth users where the password is stored elsewhere. See also Auth Modes: Local vs. Remote vs. Both section of Configuration in the Installation Guide. It’s a valid configuration of a Dataverse installation to not use builtin users at all.
For security reasons, builtin users cannot be created via API unless the team who runs the Dataverse installation has populated a database setting called BuiltinUsers.KEY
, which is described under Securing Your Installation and Database Settings sections of Configuration in the Installation Guide. You will need to know the value of BuiltinUsers.KEY
before you can proceed.
To create a builtin user via API, you must first construct a JSON document. You can download user-add.json
or copy the text below as a starting point and edit as necessary.
{
"firstName": "Lisa",
"lastName": "Simpson",
"userName": "lsimpson",
"affiliation": "Springfield",
"position": "Student",
"email": "lsimpson@mailinator.com"
}
Place this user-add.json
file in your current directory and run the following curl command, substituting variables as necessary. Note that both the password of the new user and the value of BuiltinUsers.KEY
are passed as query parameters:
curl -d @user-add.json -H "Content-type:application/json" "$SERVER_URL/api/builtin-users?password=$NEWUSER_PASSWORD&key=$BUILTIN_USERS_KEY"
Optionally, you may use a third query parameter “sendEmailNotification=false” to explicitly disable sending an email notification to the new user.
Creates a new role under Dataverse collection id
. Needs a json file with the role description:
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=root
curl -H X-Dataverse-key:$API_TOKEN -X POST -H "Content-type:application/json" $SERVER_URL/api/dataverses/$ID/roles --upload-file roles.json
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X POST -H "Content-type:application/json" https://demo.dataverse.org/api/dataverses/root/roles --upload-file roles.json
Where roles.json
looks like this:
{
"alias": "sys1",
"name": “Restricted System Role”,
"description": “A person who may only add datasets.”,
"permissions": [
"AddDataset"
]
}
Note
Only a Dataverse installation account with superuser permissions is allowed to create roles in a Dataverse Collection.
A curl example using an ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key:$API_TOKEN" -X DELETE $SERVER_URL/api/roles/$ID
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X DELETE https://demo.dataverse.org/api/roles/24
A curl example using a Role alias ALIAS
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ALIAS=roleAlias
curl -H "X-Dataverse-key:$API_TOKEN" -X DELETE "$SERVER_URL/api/roles/:alias?alias=$ALIAS"
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X DELETE https://demo.dataverse.org/api/roles/:alias?alias=roleAlias
Explicit groups list their members explicitly. These groups are defined in Dataverse collections, which is why their API endpoint is under api/dataverses/$id/
, where $id
is the id of the Dataverse collection.
Create a new explicit group under Dataverse collection $id
:
POST http://$server/api/dataverses/$id/groups
Data being POSTed is json-formatted description of the group:
{
"description":"Describe the group here",
"displayName":"Close Collaborators",
"aliasInOwner":"ccs"
}
List explicit groups under Dataverse collection $id
:
GET http://$server/api/dataverses/$id/groups
Show group $groupAlias
under dataverse $dv
:
GET http://$server/api/dataverses/$dv/groups/$groupAlias
Update group $groupAlias
under Dataverse collection $dv
. The request body is the same as the create group one, except that the group alias cannot be changed. Thus, the field aliasInOwner
is ignored.
PUT http://$server/api/dataverses/$dv/groups/$groupAlias
Delete group $groupAlias
under Dataverse collection $dv
:
DELETE http://$server/api/dataverses/$dv/groups/$groupAlias
Bulk add role assignees to an explicit group. The request body is a JSON array of role assignee identifiers, such as @admin
, &ip/localhosts
or :authenticated-users
:
POST http://$server/api/dataverses/$dv/groups/$groupAlias/roleAssignees
Add a single role assignee to a group. Request body is ignored:
PUT http://$server/api/dataverses/$dv/groups/$groupAlias/roleAssignees/$roleAssigneeIdentifier
Remove a single role assignee from an explicit group:
DELETE http://$server/api/dataverses/$dv/groups/$groupAlias/roleAssignees/$roleAssigneeIdentifier
Management of Shibboleth groups via API is documented in the Shibboleth section of the Installation Guide.
CORS Get the Dataverse installation version. The response contains the version and build numbers:
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export below.
export SERVER_URL=https://demo.dataverse.org
curl $SERVER_URL/api/info/version
The fully expanded example above (without environment variables) looks like this:
curl https://demo.dataverse.org/api/info/version
Get the server name. This is useful when a Dataverse installation is composed of multiple app servers behind a load balancer:
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export below.
export SERVER_URL=https://demo.dataverse.org
curl $SERVER_URL/api/info/server
The fully expanded example above (without environment variables) looks like this:
curl https://demo.dataverse.org/api/info/server
For now, only the value for the :DatasetPublishPopupCustomText setting from the Configuration section of the Installation Guide is exposed:
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export below.
export SERVER_URL=https://demo.dataverse.org
curl $SERVER_URL/api/info/settings/:DatasetPublishPopupCustomText
The fully expanded example above (without environment variables) looks like this:
curl https://demo.dataverse.org/api/info/settings/:DatasetPublishPopupCustomText
Get API Terms of Use. The response contains the text value inserted as API Terms of use which uses the database setting :ApiTermsOfUse
:
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export below.
export SERVER_URL=https://demo.dataverse.org
curl $SERVER_URL/api/info/apiTermsOfUse
The fully expanded example above (without environment variables) looks like this:
curl https://demo.dataverse.org/api/info/apiTermsOfUse
CORS Lists brief info about all metadata blocks registered in the system:
GET http://$SERVER/api/metadatablocks
CORS
Return data about the block whose identifier
is passed. identifier
can either be the block’s id, or its name:
GET http://$SERVER/api/metadatablocks/$identifier
Each user can get a dump of their notifications by passing in their API token:
curl -H "X-Dataverse-key:$API_TOKEN" $SERVER_URL/api/notifications/all
Each user can get a dump of their basic information in JSON format by passing in their API token:
curl -H "X-Dataverse-key:$API_TOKEN" $SERVER_URL/api/users/:me
PIDs is short for Persistent IDentifiers. Examples include DOI or Handle. There are some additional PID operations listed in the Managing Datasets and Dataverse Collections section of the Admin Guide.
Get information on a PID, especially its “state” such as “draft” or “findable”. Currently, this API only works on DataCite DOIs. A superuser API token is required.
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export below.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PID=doi:10.70122/FK2/9BXT5O
curl -H "X-Dataverse-key:$API_TOKEN" $SERVER_URL/api/pids?persistentId=$PID
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx https://demo.dataverse.org/api/pids?persistentId=doi:10.70122/FK2/9BXT5O
Get a list of PIDs that have not been reserved on the PID provider side. This can happen, for example, if a dataset is created while the PID provider is down. A superuser API token is required.
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export below.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
curl -H "X-Dataverse-key:$API_TOKEN" $SERVER_URL/api/pids/unreserved
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx https://demo.dataverse.org/api/pids/unreserved
Reserved a PID for a dataset. A superuser API token is required.
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export below.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PID=doi:10.70122/FK2/9BXT5O
curl -H "X-Dataverse-key:$API_TOKEN" -X POST $SERVER_URL/api/pids/:persistentId/reserve?persistentId=$PID
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X POST https://demo.dataverse.org/api/pids/:persistentId/reserve?persistentId=doi:10.70122/FK2/9BXT5O
Delete PID (this is only possible for PIDs that are in the “draft” state) and within a Dataverse installation, set globalidcreatetime
to null and identifierregistered
to false. A superuser API token is required.
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export below.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export PID=doi:10.70122/FK2/9BXT5O
curl -H "X-Dataverse-key:$API_TOKEN" -X DELETE $SERVER_URL/api/pids/:persistentId/delete?persistentId=$PID
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X DELETE https://demo.dataverse.org/api/pids/:persistentId/delete?persistentId=doi:10.70122/FK2/9BXT5O
This is the administrative part of the API. For security reasons, it is absolutely essential that you block it before allowing public access to a Dataverse installation. Blocking can be done using settings. See the post-install-api-block.sh
script in the scripts/api
folder for details. See Blocking API Endpoints in Securing Your Installation section of the Configuration page of the Installation Guide.
Sets setting name
to the body of the request:
PUT http://$SERVER/api/admin/settings/$name
Get the setting under name
:
GET http://$SERVER/api/admin/settings/$name
Delete the setting under name
:
DELETE http://$SERVER/api/admin/settings/$name
Communications to users can be handled via banner messages that are displayed at the top of all pages within your Dataverse installation. Two types of banners can be configured:
Note that HTML can be included in banner messages.
Add a Banner Message:
curl -H "Content-type:application/json" -X POST http://$SERVER/api/admin/bannerMessage --upload-file messages.json
Where messages.json
looks like this:
{
"dismissibleByUser": "true",
"messageTexts": [
{
"lang": "en",
"message": "Dismissible Banner Message added via API"
},
{
"lang": "fr",
"message": "Message de bannière ajouté via l'API"
}
]
}
Get a list of active Banner Messages:
curl -X GET http://$SERVER/api/admin/bannerMessage
Delete a Banner Message by its id:
curl -X DELETE http://$SERVER/api/admin/bannerMessage/$id
Deactivate a Banner Message by its id (allows you to hide a message while retaining information about which users have dismissed the banner):
curl -X PUT http://$SERVER/api/admin/bannerMessage/$id/deactivate
List the authentication provider factories. The alias field of these is used while configuring the providers themselves.
GET http://$SERVER/api/admin/authenticationProviderFactories
List all the authentication providers in the system (both enabled and disabled):
GET http://$SERVER/api/admin/authenticationProviders
Add new authentication provider. The POST data is in JSON format, similar to the JSON retrieved from this command’s GET
counterpart.
POST http://$SERVER/api/admin/authenticationProviders
Show data about an authentication provider:
GET http://$SERVER/api/admin/authenticationProviders/$id
Enable or disable an authentication provider (denoted by id
):
PUT http://$SERVER/api/admin/authenticationProviders/$id/enabled
Note
The former endpoint, ending with :enabled
(that is, with a colon), is still supported, but deprecated.
Check whether an authentication proider is enabled:
GET http://$SERVER/api/admin/authenticationProviders/$id/enabled
The body of the request should be either true
or false
. Content type has to be application/json
, like so:
curl -H "Content-type: application/json" -X POST -d"false" http://localhost:8080/api/admin/authenticationProviders/echo-dignified/:enabled
Deletes an authentication provider from the system. The command succeeds even if there is no such provider, as the postcondition holds: there is no provider by that id after the command returns.
DELETE http://$SERVER/api/admin/authenticationProviders/$id/
Creates a global role in the Dataverse installation. The data POSTed are assumed to be a role JSON.
POST http://$SERVER/api/admin/roles
A curl example using an ID
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key:$API_TOKEN" -X DELETE $SERVER_URL/api/admin/roles/$ID
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X DELETE https://demo.dataverse.org/api/admin/roles/24
A curl example using a Role alias ALIAS
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ALIAS=roleAlias
curl -H "X-Dataverse-key:$API_TOKEN" -X DELETE "$SERVER_URL/api/admin/roles/:alias?alias=$ALIAS"
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" -X DELETE https://demo.dataverse.org/api/admin/roles/:alias?alias=roleAlias
List users with the options to search and “page” through results. Only accessible to superusers. Optional parameters:
searchTerm
A string that matches the beginning of a user identifier, first name, last name or email address.itemsPerPage
The number of detailed results to return. The default is 25. This number has no limit. e.g. You could set it to 1000 to return 1,000 resultsselectedPage
The page of results to return. The default is 1.sortKey
A string that represents a field that is used for sorting the results. Possible values are “id”, “useridentifier” (username), “lastname” (last name), “firstname” (first name), “email” (email address), “affiliation” (affiliation), “superuser” (flag that denotes if the user is an administrator of the site), “position”, “createdtime” (created time), “lastlogintime” (last login time), “lastapiusetime” (last API use time). The default is “useridentifier”.export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export ID=24
curl -H "X-Dataverse-key:$API_TOKEN" $SERVER_URL/api/admin/list-users
# sort by createdtime (the creation time of the account)
curl -H "X-Dataverse-key:$API_TOKEN" "$SERVER_URL/api/admin/list-users?sortKey=createdtime"
The fully expanded example above (without environment variables) looks like this:
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" https://demo.dataverse.org/api/admin/list-users
# sort by createdtime (the creation time of the account)
curl -H "X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx" "https://demo.dataverse.org/api/admin/list-users?sortKey=createdtime"
Sample output appears below.
selectedPage
parameters may be specified.pagination
section includes pageCount
, previousPageNumber
, nextPageNumber
, and other variables that may be used to re-create the UI.{
"status":"OK",
"data":{
"userCount":27,
"selectedPage":1,
"pagination":{
"isNecessary":true,
"numResults":27,
"numResultsString":"27",
"docsPerPage":25,
"selectedPageNumber":1,
"pageCount":2,
"hasPreviousPageNumber":false,
"previousPageNumber":1,
"hasNextPageNumber":true,
"nextPageNumber":2,
"startResultNumber":1,
"endResultNumber":25,
"startResultNumberString":"1",
"endResultNumberString":"25",
"remainingResults":2,
"numberNextResults":2,
"pageNumberList":[
1,
2
]
},
"bundleStrings":{
"userId":"ID",
"userIdentifier":"Username",
"lastName":"Last Name ",
"firstName":"First Name ",
"email":"Email",
"affiliation":"Affiliation",
"position":"Position",
"isSuperuser":"Superuser",
"authenticationProvider":"Authentication",
"roles":"Roles",
"createdTime":"Created Time",
"lastLoginTime":"Last Login Time",
"lastApiUseTime":"Last API Use Time"
},
"users":[
{
"id":8,
"userIdentifier":"created1",
"lastName":"created1",
"firstName":"created1",
"email":"created1@g.com",
"affiliation":"hello",
"isSuperuser":false,
"authenticationProvider":"BuiltinAuthenticationProvider",
"roles":"Curator",
"createdTime":"2017-06-28 10:36:29.444"
},
{
"id":9,
"userIdentifier":"created8",
"lastName":"created8",
"firstName":"created8",
"email":"created8@g.com",
"isSuperuser":false,
"authenticationProvider":"BuiltinAuthenticationProvider",
"roles":"Curator",
"createdTime":"2000-01-01 00:00:00.0"
},
{
"id":1,
"userIdentifier":"dataverseAdmin",
"lastName":"Admin",
"firstName":"Dataverse",
"email":"dataverse@mailinator2.com",
"affiliation":"Dataverse.org",
"position":"Admin",
"isSuperuser":true,
"authenticationProvider":"BuiltinAuthenticationProvider",
"roles":"Admin, Contributor",
"createdTime":"2000-01-01 00:00:00.0",
"lastLoginTime":"2017-07-03 12:22:35.926",
"lastApiUseTime":"2017-07-03 12:55:57.186"
}
// ... 22 more user documents ...
]
}
}
Note
“List all users” GET http://$SERVER/api/admin/authenticatedUsers
is deprecated, but supported.
List user whose identifier
(without the @
sign) is passed:
GET http://$SERVER/api/admin/authenticatedUsers/$identifier
Sample output using “dataverseAdmin” as the identifier
:
{
"authenticationProviderId": "builtin",
"persistentUserId": "dataverseAdmin",
"position": "Admin",
"id": 1,
"identifier": "@dataverseAdmin",
"displayName": "Dataverse Admin",
"firstName": "Dataverse",
"lastName": "Admin",
"email": "dataverse@mailinator.com",
"superuser": true,
"affiliation": "Dataverse.org"
}
Create an authenticatedUser:
POST http://$SERVER/api/admin/authenticatedUsers
POSTed JSON example:
{
"authenticationProviderId": "orcid",
"persistentUserId": "0000-0002-3283-0661",
"identifier": "@pete",
"firstName": "Pete K.",
"lastName": "Dataversky",
"email": "pete@mailinator.com"
}
If a user has created multiple accounts and has been performed actions under both accounts that need to be preserved, these accounts can be combined. One account can be merged into another account and all data associated with both accounts will be combined in the surviving account. Only accessible to superusers.:
POST https://$SERVER/api/users/$toMergeIdentifier/mergeIntoUser/$continuingIdentifier
Example: curl -H "X-Dataverse-key: $API_TOKEN" -X POST http://demo.dataverse.org/api/users/jsmith2/mergeIntoUser/jsmith
This action moves account data from jsmith2 into the account jsmith and deletes the account of jsmith2.
Note: User accounts can only be merged if they are either both active or both deactivated. See deactivate a user.
Changes identifier for user in AuthenticatedUser
, BuiltinUser
, AuthenticatedUserLookup
& RoleAssignment
. Allows them to log in with the new identifier. Only accessible to superusers.:
POST http://$SERVER/api/users/$oldIdentifier/changeIdentifier/$newIdentifier
Example: curl -H "X-Dataverse-key: $API_TOKEN" -X POST https://demo.dataverse.org/api/users/johnsmith/changeIdentifier/jsmith
This action changes the identifier of user johnsmith to jsmith.
Toggles superuser mode on the AuthenticatedUser
whose identifier
(without the @
sign) is passed.
POST http://$SERVER/api/admin/superuser/$identifier
Deletes an AuthenticatedUser
whose identifier
(without the @
sign) is passed.
DELETE http://$SERVER/api/admin/authenticatedUsers/$identifier
Deletes an AuthenticatedUser
whose id
is passed.
DELETE http://$SERVER/api/admin/authenticatedUsers/id/$id
Note: If the user has performed certain actions such as creating or contributing to a Dataset or downloading a file they cannot be deleted. To see where in the database these actions are stored you can use the Show User Traces API. If a user cannot be deleted for this reason, you can choose to deactivate a user.
Deactivates a user. A superuser API token is not required but the command will operate using the first superuser it finds.
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export below.
export SERVER_URL=http://localhost:8080
export USERNAME=jdoe
curl -X POST $SERVER_URL/api/admin/authenticatedUsers/$USERNAME/deactivate
The fully expanded example above (without environment variables) looks like this:
curl -X POST http://localhost:8080/api/admin/authenticatedUsers/jdoe/deactivate
The database ID of the user can be passed instead of the username.
export SERVER_URL=http://localhost:8080
export USERID=42
curl -X POST $SERVER_URL/api/admin/authenticatedUsers/id/$USERID/deactivate
Note: A primary purpose of most Dataverse installations is to serve an archive. In the archival space, there are best practices around the tracking of data access and the tracking of modifications to data and metadata. In support of these key workflows, a simple mechanism to delete users that have performed edit or access actions in the system is not provided. Providing a Deactivate User endpoint for users who have taken certain actions in the system alongside a Delete User endpoint to remove users that haven’t taken certain actions in the system is by design.
This is an irreversible action. There is no option to undeactivate a user.
Deactivating a user with this endpoint will:
Deactivating a user with this endpoint will keep:
Show the traces that the user has left in the system, such as datasets created, guestbooks filled out, etc. This can be useful for understanding why a user cannot be deleted. A superuser API token is required.
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export below.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export USERNAME=jdoe
curl -H "X-Dataverse-key:$API_TOKEN" -X GET $SERVER_URL/api/users/$USERNAME/traces
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X GET https://demo.dataverse.org/api/users/jdoe/traces
Removes all roles from the user. This is equivalent of clicking the “Remove All Roles” button in the superuser dashboard. Note that you can preview the roles that will be removed with the Show User Traces API. A superuser API token is required.
Note
See curl Examples and Environment Variables if you are unfamiliar with the use of export below.
export API_TOKEN=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx
export SERVER_URL=https://demo.dataverse.org
export USERNAME=jdoe
curl -H "X-Dataverse-key:$API_TOKEN" -X POST $SERVER_URL/api/users/$USERNAME/removeRoles
The fully expanded example above (without environment variables) looks like this:
curl -H X-Dataverse-key:xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -X POST http://localhost:8080/api/users/jdoe/removeRoles
List all role assignments of a role assignee (i.e. a user or a group):
GET http://$SERVER/api/admin/assignments/assignees/$identifier
Note that identifier
can contain slashes (e.g. &ip/localhost-users
).
List permissions a user (based on API Token used) has on a Dataverse collection or dataset:
GET http://$SERVER/api/admin/permissions/$identifier
The $identifier
can be a Dataverse collection alias or database id or a dataset persistent ID or database id.
List a role assignee (i.e. a user or a group):
GET http://$SERVER/api/admin/assignee/$identifier
The $identifier
should start with an @
if it’s a user. Groups start with &
. “Built in” users and groups start with :
. Private URL users start with #
.
The Saved Search, Linked Dataverses, and Linked Datasets features shipped with Dataverse 4.0, but as a “superuser-only” because they are experimental (see #1364, #1813, #1840, #1890, #1939, #2167, #2186, #2053, and #2543). The following API endpoints were added to help people with access to the “admin” API make use of these features in their current form. There is a known issue (#1364) that once a link to a Dataverse collection or dataset is created, it cannot be removed (apart from database manipulation and reindexing) which is why a DELETE
endpoint for saved searches is neither documented nor functional. The Linked Dataverse collections feature is powered by Saved Search and therefore requires that the “makelinks” endpoint be executed on a periodic basis as well.
List all saved searches.
GET http://$SERVER/api/admin/savedsearches/list
List a saved search by database id.
GET http://$SERVER/api/admin/savedsearches/$id
Execute a saved search by database id and make links to Dataverse collections and datasets that are found. The JSON response indicates which Dataverse collections and datasets were newly linked versus already linked. The debug=true
query parameter adds to the JSON response extra information about the saved search being executed (which you could also get by listing the saved search).
PUT http://$SERVER/api/admin/savedsearches/makelinks/$id?debug=true
Execute all saved searches and make links to Dataverse collections and datasets that are found. debug
works as described above. This happens automatically with a timer. For details, see Saved Searches Links Timer in the Admin Guide.
PUT http://$SERVER/api/admin/savedsearches/makelinks/all?debug=true
Recalculate the UNF value of a dataset version, if it’s missing, by supplying the dataset version database id:
POST http://$SERVER/api/admin/datasets/integrity/{datasetVersionId}/fixmissingunf
Recalculate the check sum value value of a datafile, by supplying the file’s database id and an algorithm (Valid values for $ALGORITHM include MD5, SHA-1, SHA-256, and SHA-512):
curl -H X-Dataverse-key:$API_TOKEN -X POST $SERVER_URL/api/admin/computeDataFileHashValue/{fileId}/algorithm/$ALGORITHM
Validate an existing check sum value against one newly calculated from the saved file:
curl -H X-Dataverse-key:$API_TOKEN -X POST $SERVER_URL/api/admin/validateDataFileHashValue/{fileId}
The following validates all the physical files in the dataset spcified, by recalculating the checksums and comparing them against the values saved in the database:
$SERVER_URL/api/admin/validate/dataset/files/{datasetId}
It will report the specific files that have failed the validation. For example:
curl http://localhost:8080/api/admin/validate/dataset/files/:persistentId/?persistentId=doi:10.5072/FK2/XXXXX
{"dataFiles": [
{"datafileId":2658,"storageIdentifier":"file://123-aaa","status":"valid"},
{"datafileId":2659,"storageIdentifier":"file://123-bbb","status":"invalid","errorMessage":"Checksum mismatch for datafile id 2669"},
{"datafileId":2659,"storageIdentifier":"file://123-ccc","status":"valid"}
]
}
These are only available to super users.
Validate the dataset and its components (DatasetVersion, FileMetadatas, etc.) for constraint violations:
curl $SERVER_URL/api/admin/validate/dataset/{datasetId}
if validation fails, will report the specific database entity and the offending value. For example:
{"status":"OK","data":{"entityClassDatabaseTableRowId":"[DatasetVersion id:73]","field":"archiveNote","invalidValue":"random text, not a url"}}
If the optional argument variables=true
is specified, the API will also validate the metadata associated with any tabular data files found in the dataset specified. (For example: an invalid or empty variable name).
Validate all the datasets in the Dataverse installation, report any constraint violations found:
curl $SERVER_URL/api/admin/validate/datasets
If the optional argument variables=true
is specified, the API will also validate the metadata associated with any tabular data files. (For example: an invalid or empty variable name). Note that validating all the tabular metadata may significantly increase the run time of the full validation pass.
This API streams its output in real time, i.e. it will start producing the output immediately and will be reporting on the progress as it validates one dataset at a time. For example:
{"datasets": [
{"datasetId":27,"status":"valid"},
{"datasetId":29,"status":"valid"},
{"datasetId":31,"status":"valid"},
{"datasetId":33,"status":"valid"},
{"datasetId":35,"status":"valid"},
{"datasetId":41,"status":"invalid","entityClassDatabaseTableRowId":"[DatasetVersion id:73]","field":"archiveNote","invalidValue":"random text, not a url"},
{"datasetId":57,"status":"valid"}
]
}
Note that if you are attempting to validate a very large number of datasets in your Dataverse installation, this API may time out - subject to the timeout limit set in your app server configuration. If this is a production Dataverse installation serving large amounts of data, you most likely have that timeout set to some high value already. But if you need to increase it, it can be done with the asadmin command. For example:
asadmin set server-config.network-config.protocols.protocol.http-listener-1.http.request-timeout-seconds=3600
List all available workflows in the system:
GET http://$SERVER/api/admin/workflows
Get details of a workflow with a given id:
GET http://$SERVER/api/admin/workflows/$id
Add a new workflow. Request body specifies the workflow properties and steps in JSON format.
Sample json
files are available at scripts/api/data/workflows/
:
POST http://$SERVER/api/admin/workflows
Delete a workflow with a specific id:
DELETE http://$SERVER/api/admin/workflows/$id
Warning
If the workflow designated by $id
is a default workflow, a 403 FORBIDDEN response will be returned, and the deletion will be canceled.
List the default workflow for each trigger type:
GET http://$SERVER/api/admin/workflows/default/
Set the default workflow for a given trigger. This workflow is run when a dataset is published. The body of the PUT request is the id of the workflow. Trigger types are PrePublishDataset, PostPublishDataset
:
PUT http://$SERVER/api/admin/workflows/default/$triggerType
Get the default workflow for triggerType
. Returns a JSON representation of the workflow, if present, or 404 NOT FOUND.
GET http://$SERVER/api/admin/workflows/default/$triggerType
Unset the default workflow for triggerType
. After this call, dataset releases are done with no workflow.
DELETE http://$SERVER/api/admin/workflows/default/$triggerType
Set the whitelist of IP addresses separated by a semicolon (;
) allowed to resume workflows. Request body is a list of IP addresses allowed to send “resume workflow” messages to this Dataverse installation:
PUT http://$SERVER/api/admin/workflows/ip-whitelist
Get the whitelist of IP addresses allowed to resume workflows:
GET http://$SERVER/api/admin/workflows/ip-whitelist
Restore the whitelist of IP addresses allowed to resume workflows to default (localhost only):
DELETE http://$SERVER/api/admin/workflows/ip-whitelist
Clear all cached metric results:
DELETE http://$SERVER/api/admin/clearMetricsCache
Clear a specific metric cache. Currently this must match the name of the row in the table, which is named metricName*_*metricYYYYMM (or just metricName if there is no date range for the metric). For example dataversesToMonth_2018-05:
DELETE http://$SERVER/api/admin/clearMetricsCache/$metricDbName
Recursively applies the role assignments of the specified Dataverse collection, for the roles specified by the :InheritParentRoleAssignments
setting, to all Dataverse collections contained within it:
GET http://$SERVER/api/admin/dataverse/{dataverse alias}/addRoleAssignmentsToChildren
Note: setting :InheritParentRoleAssignments
will automatically trigger inheritance of the parent Dataverse collection’s role assignments for a newly created Dataverse collection. Hence this API call is intended as a way to update existing child Dataverse collections or to update children after a change in role assignments has been made on a parent Dataverse collection.