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.


The Dataverse software has been translated into multiple languages. More information.


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.


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.


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.


Embed listings of data in external websites. More information.


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.


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.


Upload standard W3C provenance files or enter free text instead. More information.

Support for rsync

File transfer using rsync (experimental). 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.

Please help us keep this page up to date! To contribute ideas, please reply on theĀ favorite features thread on the mailing list or request access to the crowdsourced list of ideas spreadsheet (further instructions). See also our Comparative Review of Various Data Repositories.

Try the Dataverse software and its rich set of features on our demo site.