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Research Data Management

Learn about best practices in research data management

What is the DMSP?

Under the new Data Management & Sharing Policy, NIH requires researchers to prospectively plan for how scientific data will be preserved and shared through submission of a Data Management and Sharing Plan. This plan will be effective as of January 25, 2023. This guide will help you prepare now for these changes. 

The Library can help you learn more about this policy, answer questions about data storage and appropriate repositories, and guide you to additional resources. Email to get in touch with us. 

What is in the Data Management & Sharing Plan?

The DSMP asks you to describe the types of data you produce, how you will preserve and share the data, and any guidelines you may set around reuse or access. It also asks you to consider who on your team is in charge of stewarding and managing the data. 


Data Type: Briefly describe the scientific data to be managed and shared:

  • Summarize the types (for example, 256-channel EEG data and fMRI images) and amount (for example, from 50 research participants) of scientific data to be generated and/or used in the research. Descriptions may include the data modality (e.g., imaging, genomic, mobile, survey), level of aggregation (e.g., individual, aggregated, summarized), and/or the degree of data processing.
  • Describe which scientific data from the project will be preserved and shared. NIH does not anticipate that researchers will preserve and share all scientific data generated in a study. Researchers should decide which scientific data to preserve and share based on ethical, legal, and technical factors. The plan should provide the reasoning for these decisions.
  • A brief listing of the metadata, other relevant data, and any associated documentation (e.g., study protocols and data collection instruments) that will be made accessible to facilitate interpretation of the scientific data.

Related Tools, Software and/or Code: Indicate whether specialized tools are needed to access or manipulate shared scientific data to support replication or reuse, and name(s) of the needed tool(s) and software. If applicable, specify how needed tools can be accessed.

Standards: Describe what standards, if any, will be applied to the scientific data and associated metadata (i.e., data formats, data dictionaries, data identifiers, definitions, unique identifiers, and other data documentation).

Data Preservation, Access, and Associated Timelines: Give plans and timelines for data preservation and access, including:

  • The name of the repository(ies) where scientific data and metadata arising from the project will be archived. See Selecting a Data Repository for information on selecting an appropriate repository. 
  • How the scientific data will be findable and identifiable, i.e., via a persistent unique identifier or other standard indexing tools.
  • When the scientific data will be made available to other users and for how long. Identify any differences in timelines for different subsets of scientific data to be shared.
    • Note that NIH encourages scientific data to be shared as soon as possible, and no later than the time of an associated publication or end of the performance period, whichever comes first. NIH also encourages researchers to make scientific data available for as long as they anticipate it being useful for the larger research community, institutions, and/or the broader public.

Access, Distribution, or Reuse Considerations: Describe any applicable factors affecting subsequent access, distribution, or reuse of scientific data related to:

  • Informed consent
  • Privacy and confidentiality protections consistent with applicable federal, Tribal, state, and local laws, regulations, and policies
  • Whether access to scientific data derived from humans will be controlled 
  • Any restrictions imposed by federal, Tribal, or state laws, regulations, or policies, or existing or anticipated agreements
  • Any other considerations that may limit the extent of data sharing. Any potential limitations on subsequent data use should be communicated to the individuals or entities (for example, data repository managers) that will preserve and share the scientific data. The NIH IC will assess whether an applicant’s DMS plan appropriately considers and describes these factors.


The DMPTool is a free, open-source, online application that helps researchers create data management plans. The tool provides a click-through wizard with templates for creating data management plans that comply with funder requirements from many different agencies. The templates are automatically updated when funders release new guidance or mandates, so you don't have to spend time tracking down new information. 

The UConn Library is an institutional partner with the DMPTool. The tool offers an option to send your draft plan to the Research Data Services team to review. UConn Library can review your plan or answer questions, but we cannot write the plan for you. We can also meet with you before or during the writing of your plan to answer questions. 

Image of the homepage of the DMPTool website

Repositories and Storage Options

  • For some programs and types of data, NIH and/or Institute, Center, Office (ICO) policy(ies) and Funding Opportunity Announcements (FOAs) identify particular data repositories (or sets of repositories) to be used to preserve and share data.
    • For data generated from research subject to such policies or funded under such FOAs, researchers should use the designated data repository(ies).
  • For data generated from research for which no data repository is specified by NIH, researchers are encouraged to select a data repository that is appropriate for the data generated from the research project. Be sure to consult the list of desirable characteristics and the following guidance:
    • Primary consideration should be given to data repositories that are discipline or data-type specific to support effective data discovery and reuse. For a list of NIH-supported repositories, visit Repositories for Sharing Scientific Data.
    • If no appropriate discipline or data-type specific repository is available, researchers should consider a variety of other potentially suitable data sharing options:
      • Small datasets (up to 2 GB in size) may be included as supplementary material to accompany articles submitted to PubMed Central (instructions).
      • Data repositories, including generalist repositories or institutional repositories, that make data available to the larger research community, institutions, or the broader public.
      • Large datasets may benefit from cloud-based data repositories for data access, preservation, and sharing.

Icons for GREI repositories

  • The NIH recently established the GREI, NIH Generalist Repository Ecosystem Initiative . It's members are:
  • Dryad 
  • Dataverse
  • Figshare
  •  Mendeley Data
  •  Open Science Framework,
  • Vivli,
  • Zenodo.

Objectives of the GREI:

GREI branch model objective illustration

Webinars and other resources

Dr. Lisa Federer presents an introduction to the NIH Policy for Data Management and Sharing which will take effect at the start of 2023. Originally presented by NNLM in February 2022.