NIDDK Data Management & Sharing

The goal of the NIH Data Management and Sharing (DMS) policy is to maximize the availability of data from NIH-supported research to advance NIH’s mission to enhance health, lengthen life, and reduce illness and disability. The DMS policy provides a consistent, minimum expectation of data management and sharing for all research supported by the agency. To help investigators implementing the NIH DMS policy, the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) offers Institute-specific guidance for drafting a DMS Plan, as well as tools and examples to supplement the NIH DMS policy and resources.

NIDDK DMS Webinar Series – Registration now open!

NIDDK will host a DMS webinar series to provide education and outreach to the NIDDK scientific community about data management and sharing topics.

“Writing a DMS Plan” on April 25, 2023, will provide an overview of DMS planning and highlight NIH and NIDDK resources available to investigators. Participants will learn:

• What DMS tools and resources are available from NIH and NIDDK
• Where to go for help with planning, managing, and sharing data, and the role of data librarians
• How institutions may support DMS throughout the research life cycle—featuring one research organization’s approach

“Finding a Repository for Your Data” on May 31, 2023, will provide in-depth information to guide investigators in selecting appropriate repositories for their scientific data. Participants will learn:

• What NIDDK DMS resources and tools for identifying repositories are available.
• How NIDDK programs, such as dkNET (NIDDK Information Network) and the NIDDK Central Repository, can be utilized.
• How generalist repositories, particularly those participating in the NIH Generalist Repository Ecosystem Initiative (GREI), can aid investigators when there is not a good match for their data.

“Metadata and Data Standards for NIDDK Research Data” on June 27, 2023, will cover importance and utility of metadata and data standards in maximizing the value of scientific data and how these standards intersect with the NIH DMS policy. Participants will learn:

• How to select appropriate metadata and data standards when drafting a DMS Plan.
• What NIDDK DMS resources and tools are available for including metadata and data standards in DMS Plans.
• Best practices and lessons learned from NIDDK and NIH projects that developed and implemented rigorous data and metadata schema, and how these efforts enhanced the quality of the data.

“The “R” in FAIR: Data Reuse” on July 13, 2023, will focus on what data contributors can do to increase the reusability of their data and how secondary use of shared data can advance scientific knowledge.

• Explain why data generators benefit by making research data available for reuse
• Identify how considerations for secondary analyses differ from analysis performed on primary data
• Learn about tools to help data generators increase the reusability of their data and how secondary researchers can find relevant data

Registration information is coming soon.

Overview – Developing a DMS Plan

Follow the stages below when developing a DMS Plan.

1. Evaluate study design and objectives
   • Identify study design elements, formats, and content to include in a DMS Plan.
   • Evaluate sharing needs according to all relevant policies governing the data.
2. Identify data types that will be generated
   • Scientific data include any data needed to validate and replicate research findings.
   • 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.
3. Determine applicability of the policy to your research data
   • The 2023 DMS Policy applies to all research funded or conducted in whole or in part by NIH that generates scientific data.
   • The policy applies to all NIH research regardless of funding level, including: grants, cooperative agreements, contracts, intramural research, or other funding agreements.
4. Consider standards and related tools appropriate for your research data
   • NIDDK expects that investigators will use data standards widely accepted within the community.
   • Metadata should be described in the DMS Plan.
   • Investigators may choose to use existing NIH Common Data Element (CDE) resources; for example, the NIH CDE Repository.
   • Investigators should list and describe resources (e.g., code, software, tools, analytic workflows) used to manage data or develop datasets to be shared.
5. Select one or more repositories by considering
   • Policy compliance and FAIR (Findable, Accessible, Interoperable, and Reusable) principles.
   • Desirable characteristics such as unique persistent identifiers, long-term sustainability, and other characteristics.
   • The following factors when selecting a repository: Funding Opportunity Announcement (FOA) requirements, availability of organism- or data type-specific established repositories, and consortium requirements.
   • Data preservation and submission timelines for your study.
   • NIH and NIDDK repository guidance to select one or more repositories where data will be shared.
6. Generate DMS Plan
   • Use the NIDDK DMS Tools and Examples.
   • Follow NIH guidance for estimating allowable DMS costs.
   • Update DMS Plan, when needed.

Have a Question?

For additional information, please contact your Program Officer. You can find their contact information in Research Programs & Contacts.