Features
Support for FAIR Data Principles
Findable, Accessible, Interoperable, Reusable. More information.
Data citation for datasets and files
EndNote XML, RIS, or BibTeX format at the dataset or file level. More information.
OAI-PMH (Harvesting)
Gather and expose metadata from and to other systems using standardized metadata formats: Dublin Core, Data Document Initiative (DDI), OpenAIRE, etc. More information.
APIs for interoperability and custom integrations
Search API, Data Deposit (SWORD) API, Data Access API, Metrics API, Migration API, etc. More information.
API client libraries
Interact with Dataverse APIs from Python, R, Javascript, Java, and Ruby More information.
DataCite integration
DOIs are reserved, and when datasets are published, their metadata is published to DataCite. More information.
Login via Shibboleth
Single Sign On (SSO) using your institution's credentials. More information.
Login via ORCID, Google, GitHub, or Microsoft
Log in using popular OAuth2 providers. More information.
Login via OpenID Connect (OIDC)
Log in using your institution's identity provider or a third party. More information.
Internationalization
The Dataverse software has been translated into multiple languages. More information.
Versioning
History of changes to datasets and files are preserved. More information.
Restricted files
Control who can download files and choose whether or not to enable a "Request Access" button. More information.
Embargo
Make content inaccessible until an embargo end date. More information.
Custom licenses
CC0 by default but add as many standard licenses as you like or create your own. More information.
Custom terms of use
Custom terms of use can be used in place of a license or disabled by an administrator. More information.
Publishing workflow support
Datasets start as drafts and can be submitted for review before publication. More information.
File hierarchy
Users are able to control dataset file hierarchy and directory structure. More information.
File previews
A preview is available for text, tabular, image, audio, video, and geospatial files. More information.
Preview and analysis of tabular files
Data Explorer allows for searching, charting and cross tabulation analysis More information.
Usage statistics and metrics
Download counters, support for Make Data Count. More information.
Guestbook
Optionally collect data about who is downloading the files from your datasets. More information.
Fixity checks for files
MD5, SHA-1, SHA-256, SHA-512, UNF. More information.
File download in R and TSV format
Proprietary tabular formats are converted into RData and TSV. More information.
Faceted search
Facets are data driven and customizable per collection. More information.
Customization of collections
Each personal or organizational collection can be customized and branded. More information.
Private URL
Create a URL for reviewers to view an unpublished (and optionally anonymized) dataset. More information.
Widgets
Embed listings of data in external websites. More information.
Notifications
In app and email notifications for access requests, requests for review, etc. More information.
Schema.org JSON-LD
Used by Google Dataset Search and other services for discoverability. More information.
External tools
Enable additional features not built in to the Dataverse software. More information.
External vocabulary
Let users pick from external vocabularies (provided via API/SKOSMOS) when filling in metadata. More information.
Dropbox integration
Upload files stored on Dropbox. More information.
GitHub integration
A GitHub Action is available to upload files from GitHub to a dataset. More information.
Integration with Jupyter notebooks
Datasets can be opened in Binder to run code in Jupyter notebooks, RStudio, and other computation environments. More information.
User management
Dashboard for common user-related tasks. More information.
Curation status labels
Let curators mark datasets with a status label customized to your needs. More information.
Branding
Your installation can be branded with a custom homepage, header, footer, CSS, etc. More information.
Backend storage on S3 or Swift
Choose between filesystem or object storage, configurable per collection and per dataset. More information.
Direct upload and download for S3
After a permission check, files can pass freely and directly between a client computer and S3. More information.
Export data in BagIt format
For preservation, bags can be sent to the local filesystem, Duraclound, and Google Cloud. More information.
Post-publication automation (workflows)
Allow publication of a dataset to kick off external processes and integrations. More information.
Pull header metadata from Astronomy (FITS) files
Dataset metadata prepopulated from FITS file metadata. More information.
Provenance
Upload standard W3C provenance files or enter free text instead. More information.
Auxiliary files for data files
Each data file can have any number of auxiliary files for documentation or other purposes (experimental). More information.
Try the Dataverse software and its rich set of features on our demo site.