Grant Support: National Institute of Health (NIH) Data Plan Requirements

On January 25, 2023, the NIH will be adopting a new policy for grants regarding data and data management.  These changes will impact any researcher or grant writer working with the NIH.  

The entire plan and its supplements can be found here - Final NIH Policy for Data Management and Sharing - NOT-OD-21-013

NIH has also provided a quick guide here NIH Data Sharing

If you need help with the plan or its requirements, please email me, and I will do my best to answer your questions.  

The DMS Plan must be submitted through eRA Commons as a component of the grant application. If the Genomic Data Sharing (GDS) Policy also applies, the DMS Plan must address the required elements of the GDS Policy (i.e., you will not draft a separate Genomic Data Sharing Plan). However, separate plans must be drafted for any other policies (e.g., Model Organism Sharing, Research Tools, Clinical Trials Dissemination) that may apply to your project.

Unless otherwise noted in Section V of the Funding Opportunity Announcement (FOA) to which you are applying, the DMS Plan will not be evaluated or scored during the peer review process. During the pre-award phase, NIA program staff will evaluate how well your DMS Plan addresses the required elements of the policy, as well as any FOA-specific expectations. Robust development of the DMS Plan will support expedient processing and prevent delays during the pre-award phase. If revisions are required, your program officer will contact you directly. Note that the plan must be approved by program staff before an application can be funded.

A few key things to know about the New DMS Policy in brief:

Who: Will apply to all research that is funded in whole or in part by the NIH, and which generates scientific data.

What: Requires the submission of an official Data Management and Sharing Plan as part of the application for funding.

When: Officially goes into effect on January 25, 2023.  Until then, the current NIH Data Sharing Policy (2003) will remain in effect.

Where: Does not require use of a single, specific data repository; however, they do encourage the use of "established" repositories and provide supplemental guidance about how to select an appropriate repository.

Why: Supports the NIH's commitment to ensuring the results and outputs of funded research is available to the public.  Data sharing helps promote testing of validity; reusing rare or unique data sets; strengthening analysis through combining data; and overall increasing reproducibility and replicability of research.

How: Compliance will be determined by the NIH.  Failure to comply may result in enforcement actions and/or affect future funding.

Major Changes in the 2023 NIH Guidelines for Data Management Plans

In short, the changes are as follows:

• A Data Management and Sharing Plan (DMSP) for all grant applications or renewals. 
  • Before this, only those over $500,000 were expected to have a brief plan. 
• The DMSP requirement also makes the requirements for all data plans greater in the new policy, two pages (see Plan Requirements) instead of a brief paragraph.  
• Allows researchers to request funding for related data management costs - Allowable Costs Supplement 
• While required, a plan will not be used to determine the proposal's scientific merit.
• The DMSP is part of the terms and conditions of the grant, with compliance monitored

NIH DMPS Templates and Resources

You can find an excellent Data Management and Plans primer here - Data Curation Network Education Committee Data Management Primer for Researchers. 

Several templates and other available documents to help you write your plan. A few are listed below:

The NIH wants all data from projects they sponsor to be as freely available as possible. They hope these new guidelines move them towards that goal while addressing protection and privacy concerns.   The new NIH guidelines will now ask researchers and grant writers to include the following in their DMSP(from a very good review from Cornell University)

• Data Type: Briefly describe the scientific data to be managed, preserved, and shared.
• Related Tools, Software, and/or Code: An indication of whether specialized tools are needed to access or manipulate shared scientific data to support replication or reuse, and name(s) of the required tool(s) and software. 
• Standards: An indication of what standards will be applied to the scientific data and associated metadata (i.e., data format, data dictionaries, definitions, unique identifiers, and other documentation as needed). 
• Data Preservation, Access, and Associated Timelines: Plans and timelines for data preservation and access, including repositories, how data will be findable, and when it will be available
• Access, Distribution, or Reuse Considerations: NIH expects researchers to maximize the appropriate sharing of scientific data generated from NIH-funded or conducted research, consistent with privacy, security, informed consent, and proprietary issues. Describe any applicable factors affecting subsequent access, distribution, or reuse of scientific data.
• Oversight of Data Management and Sharing: Indicate how compliance with the Plan will be monitored and managed, the frequency of oversight, and by whom (e.g., titles, roles),

Miami University's Libraries and MiEBDI (Miami Ecological Big Data Initiative) have developed a Canvas module to provide students and others with an overview of data management skills and an introduction to statistical inference. This series is divided into four modules which can be taken individually or as a series. These modules can be incorporated into university courses through Canvas. Use the "Modules" link on the menu on the left to access these modules. They can be completed online, and each will take approximately four hours to complete.

These modules have been designed by Miami University's Libraries and MiEBDI (Miami Ecological Big Data Initiative). 

For questions specific to each module, please contact the following:

1. Data Management | Beth Mette | dickmaem@miamioh.edu
2. Data Curation & Reuse | Kristen Adams | adamsk3@miamioh.edu
3. Data Analysis and Introduction to R | Ginny Boehme  | boehmemv@miamioh.edu
4. Data Visualization | Kristen Adams | adamsk3@miamioh.edu

For access to the course, contact your subject librarian or email Kristen Adams adamsk3@miamioh.edu, Ginny Boehme boehmemv@miamioh.edu, or  Roger Justus justusra@miamioh.edu.  

The NIH Data Management and Sharing Policy Overview

Data Management & Sharing Policy Overview

All Policy documents can be found here:

Final NIH Policy for Data Management and Sharing

NIH Policy Library

The Council on Government Relations (COGR) an Association of Research Universities and Affiliated Medical Centers and Independent Research Institutes has published updates and information on the changes and resources.

COGR NIH DMSP Resource Page

Several universities have also developed guides and resources around this change; some of the better ones include:

• Cornell University 
• University of Arizona
• Duke University
• University of North Carolina
• University of Michigan
• Ohio State University 
• Harvard Univeristy