For most projects, the NIH recommends researchers submit their data to an appropriate field-specific repository. Field-specific repositories store data from a specific discipline or field, are operated by a professional organization or research consortium, and use specialized metadata and vocabularies for describing and organizing research data. The following resources are helpful for identifying an appropriate field-specific repository for your data.

NIH-supported Scientific Data Repositories
List of NIH-supported repositories for data sharing. Note that this list is not exhaustive. Select the link provided in the “Data Submission Policy” column to find data submission instructions for each repository.

Registry of Research Data Repositories
Global registry of research data repositories covering a wide range of disciplines from around the world. Allows researchers to search for repositories by field of study and identify relevant polices and terms of use.

FAIRSharing.org
Searchable database of three interlinked registries: standards (a registry of data terminology, standards, and schemas), databases (a registry of data repositories and knowledgebases) and policies (a registry of funder and publisher data management and sharing policies).

OpenDOAR
Global directory of open access repositories that provide free, open access to academic outputs and resources. All entries are reviewed by an editorial team for quality assurance. Use advanced search to filter by discipline, repository type, or content type.

Open Access Directory
List of open access data repositories by discipline maintained by Simmons College.

If no appropriate field-specific repository is available, researchers can submit their data to a general repository. General repositories accept data regardless of data type, format, content, or disciplinary focus. For more information, see the Generalist Repository Comparison Chart.

Dataverse
Free data repository hosted by Harvard for sharing, archiving, and exploring research data. Open to all researchers from any discipline. 

Dryad
Open-source, community-led data curation, publishing, and preservation platform for publicly available research data. 

Figshare
Free, open access data repository where researchers can preserve and share their research outputs, including figures, datasets, images, and videos.

Mendeley Data
Free and secure cloud-based communal repository where researchers can store and share their data. 

Open Science Framework
Free, open access repository and project management platform that enables collaboration and supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery. Features include automated versioning, logging of all actions, collaboration support, free and unlimited file storage, registrations, and connections to other tools/services.

Vivli
Global data repository dedicated to the sharing, analysis, and reuse of clinical research data. 

Zenodo
General-purpose open repository operated by CERN that allows researchers to deposit research papers, datasets, software, reports, and related outputs.

If no field-specific or general repository is available, researchers can submit their data to their local institutional repository. Institutional repositories are repositories that collect, preserve, and disseminate the research output of a particular institution.

SOAR: Scholarly Open Access at Rutgers
Institutional repository dedicated to collecting and providing free public access to Rutgers research and scholarship. Works submitted by researchers are made available through the SOAR research portal and indexed by Google and other search engines where they can be discovered and read by researchers worldwide. Because SOAR only accepts files up to 5 GB, it is typically only used to store small supplementary datasets that support deposited publications.

When choosing a data repository, researchers should consider the following characteristics:

• Unique persistent identifiers
  Assigns a citable unique identifier (such as a DOI) to support data discovery and reporting.
• Long-term sustainability
  Long-term plan for managing data integrity, authenticity, and availability backed by a stable technical infrastructure and funding.
• Metadata
  Ensures datasets are accompanied by sufficient metadata to enable discovery, reuse, and citation.
• Curation & quality assurance
  Provides expertise to improve the accuracy and integrity of datasets and metadata.
• Free and easy access
  Provides broad, equitable, and open access to datasets and their metadata free of charge and consistent with legal and ethical limits, Tribal sovereignty, and protection of other sensitive data.
• Broad and measured reuse
  Makes datasets and their metadata available with broadest possible terms of reuse, and provides the ability to measure attribution, citation, and reuse of data.
• Clear use guidance
  Provides accompanying documentation describing terms of dataset access and use.
• Secure
  Has documented measures in place to prevent unauthorized access to, modification of, or release of data, with levels of security commensurate with the sensitivity of data.
• Confidentiality
  Has documented capabilities for ensuring that administrative, technical, and physical safeguards are employed to comply with applicable confidentiality, risk management, and continuous monitoring requirements for sensitive data.
• Common format
  Access to data and metadata from the repository is formatted in widely used, non-proprietary formats.
• Provenance
  Records the origin, chain of custody, and any modifications to submitted datasets and metadata.
• Retention policy
  Provides documentation on policies for data retention within the repository.