add "review" dataset type and related metadata blocks

doc/release-notes/11747-review-dataset-type.md

@@ -0,0 +1,3 @@
+### New Dataset Type: Review
+
+A new, experimental dataset type called "review" has been added. When this type is published, it will be sent to DataCite as "Other" for resourceTypeGeneral. See #11747.

doc/sphinx-guides/source/api/native-api.rst

@@ -1015,8 +1015,8 @@ You should expect an HTTP 200 ("OK") response and JSON indicating the database I
 
 .. _api-create-dataset-with-type:
 
-Create a Dataset with a Dataset Type (Software, etc.)
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Create a Dataset with a Dataset Type (Software, Workflow, Review, etc.)
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 By default, datasets are given the type "dataset" but if your installation had added additional types (see :ref:`api-add-dataset-type`), you can specify the type.
 
@@ -1070,8 +1070,8 @@ Before calling the API, make sure the data files referenced by the ``POST``\ ed
 
 .. _import-dataset-with-type:
 
-Import a Dataset with a Dataset Type (Software, etc.)
-^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+Import a Dataset with a Dataset Type (Software, Workflow, Review, etc.)
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
 By default, datasets are given the type "dataset" but if your installation had added additional types (see :ref:`api-add-dataset-type`), you can specify the type.
 
@@ -4193,7 +4193,27 @@ The fully expanded example above (without environment variables) looks like this
 Add Dataset Type
 ^^^^^^^^^^^^^^^^
 
-Note: Before you add any types of your own, there should be a single type called "dataset". If you add "software" or "workflow", these types will be sent to DataCite (if you use DataCite). Otherwise, the only functionality you gain currently from adding types is an entry in the "Dataset Type" facet but be advised that if you add a type other than "software" or "workflow", you will need to add your new type to your Bundle.properties file for it to appear in Title Case rather than lower case in the "Dataset Type" facet.
+Note: Before you add any types of your own, there should be a single type called "dataset".
+
+Adding certain dataset types will result in a value other than "Dataset" being sent to DataCite (if you use DataCite) as shown in the table below.
+
+.. list-table:: Values sent to DataCite for resourceTypeGeneral by Dataset Type
+   :header-rows: 1
+   :stub-columns: 1
+   :align: left
+
+   * - Dataset Type
+     - Value sent to DataCite
+   * - dataset
+     - Dataset
+   * - software
+     - Software
+   * - workflow
+     - Workflow
+   * - review
+     - Other
+
+Other than sending a different resourceTypeGeneral to DataCite, the only functionality you gain currently from adding types is an entry in the "Dataset Type" facet but be advised that if you add a type other than "software", "workflow", or "review", you will need to add your new type to your Bundle.properties file for it to appear in Title Case rather than lower case in the "Dataset Type" facet.
 
 With all that said, we'll add a "software" type in the example below. This API endpoint is superuser only. The "name" of a type cannot be only digits. Note that this endpoint also allows you to add metadata blocks and available licenses for your new dataset type by adding "linkedMetadataBlocks" and/or "availableLicenses" arrays to your JSON.
 

doc/sphinx-guides/source/user/appendix.rst

@@ -43,6 +43,8 @@ Unlike supported metadata, experimental metadata is not enabled by default in a
 - Computational Workflow Metadata (`see .tsv <https://github.com/IQSS/dataverse/blob/master/scripts/api/data/metadatablocks/computational_workflow.tsv>`__): adapted from `Bioschemas Computational Workflow Profile, version 1.0 <https://bioschemas.org/profiles/ComputationalWorkflow/1.0-RELEASE>`__ and `Codemeta <https://codemeta.github.io/terms/>`__.
 - Archival Metadata (`see .tsv <https://github.com/IQSS/dataverse/blob/master/scripts/api/data/metadatablocks/archival.tsv>`__): Enables repositories to register metadata relating to the potential archiving of the dataset at a depositor archive, whether that be your own institutional archive or an external archive, i.e. a historical archive.
 - Local Contexts Metadata (`see .tsv <https://github.com/gdcc/dataverse-external-vocab-support/blob/main/packages/local_contexts/cvocLocalContexts.tsv>`__): Supports integration with the `Local Contexts <https://localcontexts.org/>`__ platform, enabling the use of Traditional Knowledge and Biocultural Labels, and Notices. For more information on setup and configuration, see :doc:`../installation/localcontexts`.
+- Trusted Data Dimensions and Intensities (`see .tsv <https://github.com/IQSS/dataverse/blob/master/scripts/api/data/metadatablocks/trusteddatadimensionsintensities.tsv>`__): Enables repositories to indicate dimensions of trust.
+- Repository Characteristics (`see .tsv <https://github.com/IQSS/dataverse/blob/master/scripts/api/data/metadatablocks/repositorycharacteristics.tsv>`__): Details related to the security, sustainability, and certifications of the repository.
 
 Please note: these custom metadata schemas are not included in the Solr schema for indexing by default, you will need
 to add them as necessary for your custom metadata blocks. See "Update the Solr Schema" in :doc:`../admin/metadatacustomization`.

doc/sphinx-guides/source/user/dataset-management.rst

@@ -847,11 +847,11 @@ Dataset Types
 
 .. note:: Development of the dataset types feature is ongoing. Please see https://github.com/IQSS/dataverse-pm/issues/307 for details.
 
-Out of the box, all datasets have a dataset type of "dataset". Superusers can add additional types such as "software" or "workflow" using the :ref:`api-add-dataset-type` API endpoint.
+Out of the box, all datasets have a dataset type of "dataset". Superusers can add additional types such as "software", "workflow", or "review" using the :ref:`api-add-dataset-type` API endpoint.
 
 Once more than one type appears in search results, a facet called "Dataset Type" will appear allowing you to filter down to a certain type.
 
-If your installation is configured to use DataCite as a persistent ID (PID) provider, the appropriate type ("Dataset", "Software", "Workflow") will be sent to DataCite when the dataset is published for those three types.
+If your installation is configured to use DataCite as a persistent ID (PID) provider, the appropriate type ("Dataset", "Software", "Workflow", "Review") will be sent to DataCite when the dataset is published for those types.
 
 Currently, specifying a type for a dataset can only be done via API and only when the dataset is created. The type can't currently be changed afterward. For details, see the following sections of the API guide:
 

scripts/api/data/metadatablocks/review.tsv

@@ -0,0 +1,40 @@
+#metadataBlock	name	dataverseAlias	displayName													
+	review		Review Metadata													
+#datasetField	name	title	description	watermark	fieldType	displayOrder	displayFormat	advancedSearchField	allowControlledVocabulary	allowmultiples	facetable	displayoncreate	required	parent	metadatablock_id	termURI
+	itemReviewed	Item Reviewed	The item being reviewed		none	1		FALSE	FALSE	FALSE	FALSE	FALSE	FALSE		review	
+	itemReviewedUrl	URL	The URL of the item being reviewed		url	2		FALSE	FALSE	FALSE	FALSE	FALSE	FALSE	itemReviewed	review	
+	itemReviewedType	Type	The type of the item being reviewed		text	3		FALSE	TRUE	FALSE	FALSE	FALSE	FALSE	itemReviewed	review	
+	itemReviewedCitation	Citation	The full bibliographic citation of the item being reviewed		textbox	4		FALSE	FALSE	FALSE	FALSE	FALSE	FALSE	itemReviewed	review	
+#controlledVocabulary	DatasetField	Value	identifier	displayOrder												
+	itemReviewedType	Audiovisual		0												
+	itemReviewedType	Award		1												
+	itemReviewedType	Book		2												
+	itemReviewedType	Book Chapter		3												
+	itemReviewedType	Collection		4												
+	itemReviewedType	Computational Notebook		5												
+	itemReviewedType	Conference Paper		6												
+	itemReviewedType	Conference Proceeding		7												
+	itemReviewedType	DataPaper		8												
+	itemReviewedType	Dataset		9												
+	itemReviewedType	Dissertation		10												
+	itemReviewedType	Event		11												
+	itemReviewedType	Image		12												
+	itemReviewedType	Interactive Resource		13												
+	itemReviewedType	Instrument		14												
+	itemReviewedType	Journal		15												
+	itemReviewedType	Journal Article		16												
+	itemReviewedType	Model		17												
+	itemReviewedType	Output Management Plan		18												
+	itemReviewedType	Peer Review		19												
+	itemReviewedType	Physical Object		20												
+	itemReviewedType	Preprint		21												
+	itemReviewedType	Project		22												
+	itemReviewedType	Report		23												
+	itemReviewedType	Service		24												
+	itemReviewedType	Software		25												
+	itemReviewedType	Sound		26												
+	itemReviewedType	Standard		27												
+	itemReviewedType	Study Registration		28												
+	itemReviewedType	Text		29												
+	itemReviewedType	Workflow		30												
+	itemReviewedType	Other		31												

src/main/java/edu/harvard/iq/dataverse/DataCitation.java

@@ -740,8 +740,11 @@ public Map<String, String> getDataCiteMetadata() {
 
     public JsonObject getCSLJsonFormat() {
         CSLItemDataBuilder itemBuilder = new CSLItemDataBuilder();
+        // TODO consider making this a switch
         if (type.equals(DatasetType.DATASET_TYPE_SOFTWARE)) {
             itemBuilder.type(CSLType.SOFTWARE);
+        } else if (type.equals(DatasetType.DATASET_TYPE_REVIEW)) {
+            itemBuilder.type(CSLType.REVIEW);
         } else {
             itemBuilder.type(CSLType.DATASET);
         }

src/main/java/edu/harvard/iq/dataverse/api/Datasets.java

@@ -35,6 +35,7 @@
 import edu.harvard.iq.dataverse.externaltools.ExternalToolHandler;
 import edu.harvard.iq.dataverse.globus.GlobusServiceBean;
 import edu.harvard.iq.dataverse.globus.GlobusUtil;
+import edu.harvard.iq.dataverse.i18n.i18nUtil;
 import edu.harvard.iq.dataverse.ingest.IngestServiceBean;
 import edu.harvard.iq.dataverse.ingest.IngestUtil;
 import edu.harvard.iq.dataverse.makedatacount.*;
@@ -100,13 +101,12 @@
 import java.util.stream.Collectors;
 import static edu.harvard.iq.dataverse.api.ApiConstants.*;
 
-import edu.harvard.iq.dataverse.dataset.DatasetType;
-import edu.harvard.iq.dataverse.dataset.DatasetTypeServiceBean;
 import edu.harvard.iq.dataverse.license.License;
 
 import static edu.harvard.iq.dataverse.util.json.JsonPrinter.*;
 import static edu.harvard.iq.dataverse.util.json.NullSafeJsonBuilder.jsonObjectBuilder;
 
+import static jakarta.ws.rs.core.HttpHeaders.ACCEPT_LANGUAGE;
 import static jakarta.ws.rs.core.Response.Status.BAD_REQUEST;
 import static jakarta.ws.rs.core.Response.Status.NOT_FOUND;
 import static jakarta.ws.rs.core.Response.Status.FORBIDDEN;
@@ -5720,17 +5720,19 @@ public Response resetPidGenerator(@Context ContainerRequestContext crc, @PathPar
 
     @GET
     @Path("datasetTypes")
-    public Response getDatasetTypes() {
+    public Response getDatasetTypes(@HeaderParam(ACCEPT_LANGUAGE) String acceptLanguage) {
+        Locale locale = i18nUtil.parseAcceptLanguageHeader(acceptLanguage);
         JsonArrayBuilder jab = Json.createArrayBuilder();
         for (DatasetType datasetType : datasetTypeSvc.listAll()) {
-            jab.add(datasetType.toJson());
+            jab.add(datasetType.toJson(locale));
         }
         return ok(jab);
     }
 
     @GET
     @Path("datasetTypes/{idOrName}")
-    public Response getDatasetTypes(@PathParam("idOrName") String idOrName) {
+    public Response getDatasetTypes(@PathParam("idOrName") String idOrName, @HeaderParam(ACCEPT_LANGUAGE) String acceptLanguage) {
+        Locale locale = i18nUtil.parseAcceptLanguageHeader(acceptLanguage);
         DatasetType datasetType = null;
         if (StringUtils.isNumeric(idOrName)) {
             try {
@@ -5743,7 +5745,7 @@ public Response getDatasetTypes(@PathParam("idOrName") String idOrName) {
             datasetType = datasetTypeSvc.getByName(idOrName);
         }
         if (datasetType != null) {
-            return ok(datasetType.toJson());
+            return ok(datasetType.toJson(locale));
         } else {
             return error(NOT_FOUND, "Could not find a dataset type with name " + idOrName);
         }
@@ -5768,6 +5770,8 @@ public Response addDatasetType(@Context ContainerRequestContext crc, String json
         }
 
         String nameIn = null;
+        String displayNameIn = null;
+        String descriptionIn = null;
 
         JsonArrayBuilder datasetTypesAfter = Json.createArrayBuilder();
         List<MetadataBlock> metadataBlocksToSave = new ArrayList<>();
@@ -5776,6 +5780,8 @@ public Response addDatasetType(@Context ContainerRequestContext crc, String json
         try {
             JsonObject datasetTypeObj =  JsonUtil.getJsonObject(jsonIn);
             nameIn = datasetTypeObj.getString("name");
+            displayNameIn = datasetTypeObj.getString("displayName", null);
+            descriptionIn = datasetTypeObj.getString("description", null);
 
             JsonArray arr = datasetTypeObj.getJsonArray("linkedMetadataBlocks");
             if (arr != null && !arr.isEmpty()) {
@@ -5813,6 +5819,9 @@ public Response addDatasetType(@Context ContainerRequestContext crc, String json
         if (nameIn == null) {
             return error(BAD_REQUEST, "A name for the dataset type is required");
         }
+        if (displayNameIn == null) {
+            return error(BAD_REQUEST, "A displayName for the dataset type is required");
+        }
         if (StringUtils.isNumeric(nameIn)) {
             // getDatasetTypes supports id or name so we don't want a names that looks like an id
             return error(BAD_REQUEST, "The name of the type cannot be only digits.");
@@ -5821,12 +5830,17 @@ public Response addDatasetType(@Context ContainerRequestContext crc, String json
         try {
             DatasetType datasetType = new DatasetType();
             datasetType.setName(nameIn);
+            datasetType.setDisplayName(displayNameIn);
+            datasetType.setDescription(descriptionIn);
             datasetType.setMetadataBlocks(metadataBlocksToSave);
             datasetType.setLicenses(licensesToSave);
             DatasetType saved = datasetTypeSvc.save(datasetType);
             Long typeId = saved.getId();
             String name = saved.getName();
-            return ok(saved.toJson());
+            // Locale is null because when creating the dataset type we are relying entirely
+            // on the database. The new dataset type has not yet been localized in a
+            // properties file.
+            return ok(saved.toJson(null));
         } catch (WrappedResponse ex) {
             return error(BAD_REQUEST, ex.getMessage());
         }