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Dataverse 4.18

This release brings new features, enhancements, and bug fixes to Dataverse. Thank you to all of the community members who contributed code, suggestions, bug reports, and other assistance across the project.

Release Highlights

File Page Previews and Previewers

File-level External Tools can now be configured to display in a "Preview Mode" designed for embedding within the file landing page.

While not technically part of this release, previewers have been made available for several common file types. The previewers support for spreadsheet, image, text, document, audio, video, html files and more. These previewers can be found in the Qualitative Data Repository Github Repository. The spreadsheet viewer was contributed by the Dataverse SSHOC project.

Microsoft Login

Users can now create Dataverse accounts and login using self-provisioned Microsoft accounts such as live.com and outlook.com. Users can also use Microsoft accounts managed by their institutions. This new feature not only makes it easier to log in to Dataverse but will also streamline the interaction between any external tools that utilize Azure services that require login.

Add Data and Host Dataverse

More workflows to add data have been added across the UI, including a new button on the My Data tab of the Account page, as well as a link in the Dataverse navbar, which will display on every page. This will provider users much easier access to start depositing data. By default, the Host Dataverse will be the installation root dataverse for these new Add Data workflows, but there is now a dropdown component allowing creators to select a dataverse you have proper permissions to create a new dataverse or dataset in.

Primefaces 7

Primefaces, the open source UI framework upon which the Dataverse front end is built, has been updated to the most recent version. This provides security updates and bug fixes and will also allow Dataverse developers to take advantage of new features and enhancements.

Integration Test Pipeline and Test Health Reporting

As part of the Dataverse Community's ongoing efforts to provide more robust automated testing infrastructure, and in support of the project's desire to have the develop branch constantly in a "release ready" state, API-based integration tests are now run every time a branch is merged to develop. The status of the last test run is available as a badge at the bottom of the README.md file that serves as the homepage of Dataverse Github Repository.

Make Data Count Metrics Updates

A new configuration option has been added that allows Make Data Count metrics to be collected, but not reflected in the front end. This option was designed to allow installations to collect and verify metrics for a period before turning on the display to users.

Search API Enhancements

The Dataverse Search API will now display unpublished content when an API token is passed (and appropriate permissions exist).

Additional Dataset Author Identifiers

The following dataset author identifiers are now supported:

Major Use Cases

Newly-supported use cases in this release include:

  • Users can view previews of several common file types, eliminating the need to download or explore a file just to get a quick look.
  • Users can log in using self-provisioned Microsoft accounts and also can log in using Microsoft accounts managed by an organization.
  • Dataverse administrators can now revoke and regenerate API tokens with an API call.
  • Users will receive notifications when their ingests complete, and will be informed if the ingest was a success or failure.
  • Dataverse developers will receive feedback about the health of the develop branch after their pull request was merged.
  • Dataverse tool developers will be able to query the Dataverse API for unpublished data as well as published data.
  • Dataverse administrators will be able to collect Make Data Count metrics without turning on the display for users.
  • Users with a DAI, ResearcherID, or ScopusID can use these author identifiers in their datasets.