Request for Information (RFI) on Data Management, Sharing, and Secondary Data Use Challenges and Opportunities
Notice Number:

Key Dates

Release Date:

April 19, 2024

Response Date:
May 31, 2024

Related Announcements

  • October 29, 2020 - Final NIH Policy for Data Management and Sharing. See NOT-OD-21-013.

Issued by

National Institute on Aging (NIA)


The purpose of this Request for Information (RFI) is to solicit comments and suggestions for the National Institute on Aging (NIA) to consider as it explores strategies relevant to its ongoing implementation of the National Institutes of Health (NIH) Data Management and Sharing (DMS) Policy. NIA seeks public input on challenges, opportunities, and use-cases related to data management, sharing, and secondary use of scientific data related to Aging and Alzheimer's disease (AD) and AD-related dementias (ADRD) research, needs of investigators supported through the NIA, and strategies that can be capitalized upon to address these needs. The goal is to develop an overarching NIA data strategy that informs NIA programs and policies, and addresses gaps in the existing data ecosystem and sociocultural barriers to data sharing and use.

NIA wishes to engage a wide variety of stakeholders, including the following: 

  • Individuals who have shared primary research data produced by their own research teams, 
  • Individuals who have used existing research data to conduct secondary analyses, 
  • Research networks and consortia who provide data sharing resources, and
  • Academic research institutions, research professional societies, and organizations that represent the interests of NIA-supported researchers.  

NIA solicits information from all interested respondents, including the following: 

NIA solicits information on both the current data ecosystem and additional resources needed to fully benefit from the rich data produced by NIA-funded research.


The NIH issued a  DMS policy, effective on January 25, 2023, which applies to all research, funded or conducted in whole or in part by NIH, that results in the generation of scientific data. This includes research funded or conducted by extramural grants, contracts, Intramural Research Projects, or other funding agreements regardless of NIH funding level or funding mechanism. The policy establishes the expectation to maximize the appropriate sharing of scientific data and encourages sharing consistent with findable, accessible, interoperable, and reusable (FAIR) data principles. Under the new DMS policy, NIH-supported investigators should prospectively plan for the managing and sharing of scientific data, submit a DMS plan and comply with the approved plan, including budgeting appropriately for DMS activities. Shared scientific data should be made accessible as soon as possible, and no later than the time of an associated publication, or the end of performance period, whichever comes first.  DMS Plans are recommended to address six elements, and a DMS format page is provided to help investigators respond to the policy.  The policy applies to many, but not all, activity codes, covering a broad range of data types, including biological, phenotypic, imaging, “-omics” data, clinical studies results, social and behavioral data, surveys, questionnaires, surveillance data, and related metadata and programming code. 

Information Requested

NIA invites comments on notable strategies for DMS, legal, ethical, sociocultural, or technical barriers that limit data sharing and preservation, as well as unmet gaps and needs.  Comments are invited from all interested respondents, including individuals who have shared primary research data, those who have used research data to conduct secondary data analyses, research networks and consortia who provide data sharing resources, and academic research institutions, research professional societies, and organizations that represent the interests of U.S.-based and international NIA-supported researchers.

Respondents should not feel compelled to address all items listed below. Comments may address, but are not limited to, the following topics:

  • Approaches to DMS:
    • Advantages and limitations of existing data infrastructures (centralized, federated, or hybrid) for DMS.
    • Critical factors affecting choice of repository or repositories, and choice of dataset(s) for secondary use including data quality, relevancy, and format compatibility. 
    • Critical factors that affect the choice of computing environment for data analysis, including on-premises and cloud computing, with considerations of data security, scalability, and cost-efficiency.
  • Incentives to DMS:
    • Critical legal, sociocultural, or organizational factors that encourage and/or facilitate data sharing, such as academic recognition and funding requirements.
    • Infrastructure services that encourage and/or facilitate data sharing.
    • Metadata standards that might be utilized to better support DMS for diverse scientific data types emphasizing the role of interoperability.
  • DMS burdens and constraints:
    • Factors affecting effort and monetary costs for DMS, including data curation and storage costs.
    • Critical legal, ethical, or sociocultural constraints that potentially limit DMS, such as informed consent, existing data use agreements, intellectual property, international data policies, or privacy concerns.
    • Personnel resources required for reviews of data access requests and data users questions.
  • DMS challenges, limitations, and opportunities to better meet researchers’ needs:
    • Critical factors that promote finding, accessing, and using shared data emphasizing the role of user-friendly interfaces, efficient search functionalities, and barriers existing systems create for cross system communication.
    • Technological constraints on data sharing, such as repository availability, data provenance tracking, governance structure of the study, and implementation of access controls.
    • Procedures for submitting data for sharing, collecting, and approving data use requests, obtaining, and analyzing shared data.
    • Information about data sustainability plans providing guidance on how long data will be maintained.
  • Examples of success:
    • Suggestions for improving the DMS process, such as noteworthy data formats, standards, documentation, and support resources.
    • Noteworthy examples of individual resources or data ecosystems (within or outside NIH) that successfully support DMS within or across multiple fields.
    • Descriptions of what makes these resources successful (e.g., databases, platforms, cloud computing resources, software applications, cross resource integration capabilities).

How to Submit a Response

Responses to this RFI may be submitted using the response form. To ensure consideration, responses must be submitted by May 31, 2024.

Response to this RFI is voluntary. You may voluntarily include your name and contact information with your response. Responders are free to address any or all the topics listed above and/or to provide feedback on any relevant issues. The submitted information will be reviewed by NIH staff.

This request is for information and planning purposes only and should not be construed as a solicitation or as an obligation on the part of the Federal Government. The NIH does not intend to make awards based on responses to this RFI or to otherwise pay for the preparation of any information submitted or for the Government's use of such information.

The NIH will use the information submitted in response to this RFI at its discretion and will not provide comments to any responder's submission. The information provided will be analyzed and may be aggregated in presentations and reports. Respondents are advised that the Government is under no obligation to acknowledge receipt of the information received or provide feedback to respondents with respect to any information submitted. No proprietary, classified, confidential, or sensitive information should be included in your response. The Government reserves the right to use any non-proprietary technical information in any resultant solicitation(s).


Please direct all inquiries to:

National Institute on Aging
The contacts below can be reached by email at

Division of Behavioral and Social Research
Partha Bhattacharyya, Ph.D.
Rebecca Krupenevich, Ph.D.

Division of Geriatrics and Clinical Gerontology
Rosaly Correa-De-Araujo, MD, MSc, Ph.D.
Beth Wilmot, Ph.D.

Division of Aging Biology
Jennifer Fox, Ph.D.
Yi-Ping Fu, Ph.D.

Division of Neuroscience
Mette Peters, Ph.D.
Luci Roberts, Ph.D.

Intramural Research Program
Dr. Shepherd Schurman
Dr. Eleanor Simonsick