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Data Management Sharing Plans & Repositories

Planning for a project involves making decisions about data resources and potential products. A Data Management Plan (DMP) describes data that will be acquired or produced during research; how the data will be managed, described, and stored, what standards you will use, and how data will be handled and protected during and after the completion of the project.

Jump ahead to the NIH, NSF or Respositories.

Elements of a Data Management Sharing (DMS) plan

The image of the data management sharing plan provides an overview of how to incorporate both FAIR Principles while meeting the requirements of any data management sharing plans. It is important to develop your data management sharing plan at the beginning of your project. This type of project planning saves time and effort. Consult with the UF Research Development team to set a timeline, discuss the new requirements, and determine what campus data services you may need.

  • Data type
    • Identifying data to be preserved and shared
  • Related tools, software, code
    • Tools and software needed to access and manipulate data
  • Standards
    • Standards to be applied to scientific data and metadata
  • Data preservation, access, timelines
    • Repository to be used, persistent unique identifier, and when/ how long data will be available
  • Access, distribution, reuse considerations
    • Description of factors for data access, distribution, or reuse
  • Oversight of data management and sharing 
    • Plan compliance will be monitored/ managed and by whom

*Get started by downloading this DMS checklist.

Source: NIH

NIH Data Management Sharing Policy

NIH has a longstanding commitment to making the results of NIH-funded funded research available. Responsible data management and sharing has many benefits, including accelerating the pace of biomedical research, enabling validation of research results, and providing accessibility to high-value datasets.

A complete list of NIH grant program activity codes can be found here.

Writing a Data Management & Sharing Plan

This information includes the expectations of NIH, and the required information.

Budgeting for Data Management & Sharing Plan

This information includes allowable & unallowable costs, request & justify data management and sharing costs, and an assessment of the budget.

NSF Data Management Plans

Data management requirements and plans specific to the Directorate, Office, Division, Program, or other NSF unit, relevant to a proposal are available at:

Plans for data management and sharing of the products of research. Proposals must include a document of no more than two pages uploaded under “Data Management Plan” in the supplementary documentation section of FastLane or This supplementary document should describe how the proposal will conform to NSF policy on the dissemination and sharing of research results (see Chapter XI.D.4), and may include:

  1. the types of data, samples, physical collections, software, curriculum materials, and other materials to be produced in the course of the project;
  2. the standards to be used for data and metadata format and content (where existing standards are absent or deemed inadequate, this should be documented along with any proposed solutions or remedies);
  3. policies for access and sharing including provisions for appropriate protection of privacy, confidentiality, security, intellectual property, or other rights or requirements;
  4. policies and provisions for re-use, re-distribution, and the production of derivatives; and
  5. plans for archiving data, samples, and other research products, and for preservation of access to them.

NSF Specific Program Solicitations

Please note that if a specific program solicitation provides guidance on preparation of data management plans, such guidance must be followed.


As outlined in NIH’s Supplemental Policy Information: Selecting a Repository for Data Resulting from NIH-Supported Research, using a quality data repository generally improves the FAIRness (Findable, Accessible, Interoperable, and Re-usable) of the data. For that reason, NIH strongly encourages the use of established repositories to the extent possible for preserving and sharing scientific data.

Check out the list of NIH-supported scientific data repositories.

Generalist Repositories

NIH supports a Generalist Repository Ecosystem Initiative (GREI) that includes seven established generalist repositories that collaborate to establish consistent metadata, develop use cases for data sharing, train and educate researchers on FAIR data, and the importance of data sharing. These recommended generalist repositories are a great tool for all types of data sets.

Check out the GREI Collaborative Webinar Series on data sharing.

  • Dataverse: Open source research data repository.
  • Dryad: Curated resource that makes research data discoverable, freely reusable, and citable. Dryad provides a general-purpose home for a wide diversity of data types.
  • Figshare: Store, share, and discover research to open scientific data to the world.
  • Mendeley Data: Free and secure cloud-based communal repository.
  • Open Science Framework: Free, open platform to support your research and enable collaboration.
  • Vivli: Global clinical research data.
  • Zenodo: Open science, open source, FAIR principles, free catch-all repository that assigns DOIs, open & closed data, versioning, GitHub integration, and usage statistics.

If you feel like exploring more repositories, check out the Registry of Research Data Repositories.

Citing Data

Citing data is as important as citing any type of publication. Styles differ depending on the citation style but the following information is usually required:

  • Author(s): Who is the creator of the data set? Individual, a group, or an organization.
  • Year: What year was the data set published? When was it posted online?
  • Title of dataset: in italics
  • Version: (in parentheses)
  • Description: [Data set] or [Unpublished raw data]
  • Publisher/distributor: (e.g., database, repository)
  • Persistent identifier (e.g., DOI) or Date accessed and URL

Examples of cited data sets

APA 7th edition:
Lastname, F. M. or Name of Group (Year). Title of dataset (Version No.) [Data set]. Publisher.
     DOI or URL

Use a citation manager to help manage, organize, and store all your citations.

***EndNote Premium, Papers, and Zotero displays article retraction alerts.***

Need additional help choosing a citation manager? Reach out to the UF librarians:


*Researcher checklist source citation: Ye, H., Exner, N., Muilenburg, J., Otsuji, R., Calkins, H., Sheridan, H., LaPreze, D., Sewell, K., Dolan, L., Hertz, M., Badger, K., Koshoffer, A.E., Grynoch, T., Renirie, R., Denton, A., Jones, L.C., Farrell, S., Contaxis, N., Nieman, C., Phegley, L., Smith, K., Orlowska, D., Bohman, L., 2022. Public Sharing [WWW Document]. doi:10.17605/OSF.IO/3P972