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Data Management Plans

This guide covers what Data Management Plans are, how to make an implementable one, and how to use the DMPTool

2023 NIH Data Management & Sharing Policy

                                               Previously, the NIH only required grants with $500,000 per year or more in direct costs to provide a brief explanation  of how and when data resulting fNIH Logorom the grant would be managed and shared.

The 2023 NIH policy is entirely new. Beginning January 25, 2023ALL grant applications or renewals that generate Scientific Data must include a Data Management & Sharing Plan (DMSP) which outlines a robust and detailed plan for managing and sharing data during the entire funded period as part of the funding application.

The term Scientific Data is defined in the policy as: 

"The recorded factual material commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications. Scientific data do not include laboratory notebooks, preliminary analyses, completed case report forms, drafts of scientific papers, plans for future research, peer reviews, communications with colleagues, or physical objects, such as laboratory specimens."

The DMSP should include information on data storage, access policies/procedures, preservation, metadata standards, distribution approaches, and more. The DMSP is similar to what other funders call a data management plan (DMP).

The DMSP will be assessed by NIH Program Staff (though peer reviewers will be able to comment on the proposed data management and sharing budget). The Institute, Center, or Office (ICO)-approved plan becomes a Term and Condition of the Notice of Award.

What Do I Need to Do?

High-level first steps

  1. Determine whether the NIH policy applies to you. If you are unsure whether NIH's new policy will apply to your research, check NIH's page about Research Covered Under the Data Management & Sharing Policy. Remember, all NIH funded or partially funded research generating Scientific Data will be subject to this policy beginning on January 25, 2023.
  2. Figure out your personal timeline. If you have an active NIH award going up for renewal with receipt date of January 2023, or if you are planning to submit an NIH proposal this year, then developing a DMSP should be a high priority, especially if you are working with external collaborators as it may take time to set up appropriate data procedures/agreements. 
  3. Read through this page to familiarize yourself with the changes and with the policy itself (including the supplements)
  4. Familiarize yourself with the FAIR principles (Wilkinson et. al, 2016). The FAIR (findable, accessible, interoperable, reusable) data principles are the guiding principles the NIH has used in creating the new policy. 
  5. Assess your own project and data management practices relative to the policy (see the NIH-provided supplements below), especially around documenting existing practices and developing new ones to address the increased emphasis on data sharing and administrative oversight.
  6. Review data services at PSU (e.g., computing, storageconsulting) and assess whether they will meet your needs. Also consider costs you may need to budget for such as labor for data cleaning and documentation (see the NIH-provided supplement on allowable costs).

If your research requires Institutional Review Board (IRB) approval, known as the Human Research Protection Program (HRPP) at Penn State, the HRPP may ask for information contained in your DMSP. Therefore, it is strongly recommended to draft your DMSP prior to seeking any IRB approval.

What Do I Need to Submit as Part of My Funding Proposal

If you plan to generate scientific data, you must submit a Data Management and Sharing Plan (DMSP) and Data Management and Sharing Budget Justification with your application for extramural awards. 

Your plan should be two pages or fewer and must include the information on the following topics:

  • Data Type

  • Related Tools, Software and/or Code

  • Standards

  • Data Preservation, Access, and Associated Timelines

  • Access, Distribution, or Reuse Considerations

  • Oversight of Data Management and Sharing.

To draft the plan itself, we recommend the DMPTool (log in with your Penn State credentials) using the NIH 2023 template. Check out our guide to learn how to use the DMPTool.

If you are including institutional services and tools in the DMSP, be sure to budget for any associated costs. See Additional Resources at the end of this LibGuide for Penn State resources available to you.

Any costs related to complying with the policy must be paid for up-front during the performance period. For example, costs for long-term data preservation must be budgeted for in the proposal and paid before the end of the grant. You may find the NIHM Data Archive (NDA) cost estimation worksheet useful.

Data Sharing

Unlike NIH's prior policies, the new policy requires a plan for maximizing the sharing of Scientific Data while acknowledging factors (legal, ethical, or technical) that may affect the extent to which it can be shared. NIH defines scientific data as "The recorded factual material commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications. Scientific data do not include laboratory notebooks, preliminary analyses, completed case report forms, drafts of scientific papers, plans for future research, peer reviews, communications with colleagues, or physical objects, such as laboratory specimens.”

If you are conducting research with human subjects, you must incorporate consent during the data management and sharing process, even if data will be de-identified. See Supplemental Information to the NIH Policy for Data Management and Sharing: Protecting Privacy When Sharing Human Research Participant Data.

If you are conducting research with American Indian, Alaska Native, or Indigenous populations, you must secure appropriate agreements with tribal authorities before using and sharing that information. See Supplemental Information to the NIH Policy for Data Management and Sharing: Responsible Management and Sharing of American Indian/Alaska Native Participant Data.

Where do I share my data?

NIH recommends sharing datasets through established data repositories to improve the FAIRness (Findable, Accessible, Interoperable, and Re-usable) of the data.

While NIH supports many data repositories, your data may or may not be appropriate for an NIH repository. You should also consider data repositories supported by other organizations, both public and private.  

We are in the process of developing a specific guide for data sharing and will update this when it is completed.

For more information on data sharing, see:

When do I need to share my data?

You will need to share your data when you publish your work or before your performance period ends, whichever comes first.

In general, you should make your data accessible as soon as possible. You can also use relevant requirements and expectations such as data repository policies, award record retention requirements, or journal policies, to decide when to share your data sets.


How do I prepare my data for sharing?

The policy does not state specific requirements for how you share your data.  When you share your data, you should address the NIH’s goal of making data as accessible as possible. The NIH expects all shareable data to be made available, whether or not it is associated with a publication.

All data used or generated as part of a grant must be managed, but not all data should be shared. You should not share data if doing so would violate privacy protections or applicable laws. 

You may share data related to human subjects, but your plan should address how data sharing will be communicated in the informed consent process (e.g., consent forms, waivers of consent) and privacy maintained. 

Before submitting your data to your chosen repository, you will need to:

  • Bundle your data together in logical "chunks" for citation and reuse. Appropriate bundling makes it easy to assign a persistent identifier(s) (e.g., DOI) to the dataset.  NIH strongly encourages the use of persistent identifiers for datasets. These identifiers, usually assigned by data repositories, make it easier for others to cite your data and for the NIH to track compliance.

  • De-identify your data, if appropriate

  • Convert your data to an open, machine-readable file format such as .csv when possible

  • Use data and metadata standards appropriate to your field (if any). Refer to for a searchable database of standards.

  • Document the dataset thoroughly in a separate readme.txt file, and/or create metadata according to the format required by your chosen repository or discipline

How Will Compliance Be Monitored?

You must comply with the ICO-approved plan and document that compliance in reports such as the annual Research Performance Progress Report (RPPR). Non-compliance may result in enforcement action from the NIH such as

  • Addition of special terms and conditions to the award

  • Termination of the award

Non-compliance may also affect future funding decisions. To avoid possible issues when reporting progress, ensure that your submitted plan contains enough detail for the program officer to be able to evaluate compliance.

If you make changes to your submitted plan, your new plan must be re-approved. We will provide guidance from the NIH on the process for making changes soon.

Where Can I Get Help?

General Support
Research Integrity and Assurance
General Support

NIH Guidance


This guide was adapted from the University of Arizona's NIH Data Management and Sharing Policy (2023) page (CC By-NC 4.0). Penn State University Libraries recognizes their expertise and authorship.