NIH 2023 Data Management and Sharing Policy (DMS Policy)
- NIH 2023 DMS Policy
- The 2023 NIH Data Management and Sharing Policy
- What do I need to do?
- What do I need to submit as part of my funding proposal
- Data sharing
- Where do I share my data?
- When do I need to share my data?
- How do I prepare my data for sharing?
- How will compliance be monitored?
- Where can I get help?
- NIH Guidance
- Data management and sharing plan examples
- Acknowledgment
- Tutorials
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The 2023 NIH Data Management and 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 from the grant would be shared.
The 2023 NIH policy is entirely new. Beginning January 25, 2023, ALL grant applications or renewals that generate Scientific Data must include a robust and detailed plan for managing and sharing data during the entire funded period. This includes information on data storage, access policies/procedures, preservation, metadata standards, distribution approaches, and more. You must provide this information in a data management and sharing plan (DMSP). 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 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?
A Data Management & Sharing Plan (DMSP) must be submitted as part of the funding application for all new and competing proposals/renewals that generate Scientific Data for January 25, 2023, and subsequent receipt dates. 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."
High-level first steps
- 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.
- Figure out your personal timeline. If you have an active NIH award going up for renewal with a 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.
- Read through this website to familiarize yourself with the changes and with the policy itself (including the supplements)
- 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.
- Assess your 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.
- Review data services at ASU (e.g., computing, storage, consulting) 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 ASU’s Institutional Review Board (IRB) approval, IRB may ask for the information in your DMSP. Therefore, drafting your DMSP before seeking IRB approval is strongly recommended.
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) to the funding NIH ICO as part of the Budget Justification section of your application for extramural awards.
Your plan should be two pages or fewer and must include:
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Data Type
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Related Tools, Software and/or Code
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Standards
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Data Preservation, Access, and Associated Timelines
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Access, Distribution, or Reuse Considerations
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Oversight of Data Management and Sharing.
To draft the plan itself, we recommend the DMPTool (log in with your ASURITE ID) using the NIH 2023 template. Additional guidance for completing each section of the template will be added to the DMPTool on a rolling basis. Check out our self-guided tutorial to learn how to use the DMPTool to and get updated guidance on writing your data management and sharing plan.
If you are including institutional services and tools in the DMSP, be sure to budget for any associated costs. See the following section for what kinds of services and tools are available.
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.
- Supplemental Information: Elements of an NIH Data Management and Sharing Plan (2023)Information to help researchers choose data repositories suitable for the preservation and sharing of data
- Data Management Plan ExamplesUse these funded examples to tailor your own data management plan.
- ASU Research Data Management PlanningOverview of planning components and resources to meet your needs.
- Ten simple rules for maximizing the recommendations of the NIH data management and sharing planThis article provides ten critical recommendations for creating a data management and Sharing Plan (DMSP) that is both maximally compliant and effective for the January 2023 National Institutes of Health (NIH) Policy for Data Management and Sharing.
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. The new NIH definition of scientific data "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.
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.
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.
For more information, see:
- Guide to Sharing and Storing Research DataASU Library guide on best practices and resource links for choosing where to store and manage your research data.
- Supplemental Information to the NIH Policy for Data Management and Sharing: Selecting a Repository for Data Resulting from NIH-Supported ResearchNIH information to help researchers choose data repositories suitable for the preservation and sharing of data
- Five criteria for Yes/No response used in the query to repositoriesDefinitions of the five criteria for Yes/No response used in the query to repositories by the Trans-NIH BioMedical Informatics Coordinating Committee (BMIC).
- NNLM Data Repository FinderA tool to locate NIH-supported repositories for sharing research data. Answering questions to narrow the number of repositories to compare. Provided by the Network of the National Library of Medicine
- ICPSR NIH DataICPSR also supports data archiving for NIH-funded data collections. They provide cost estimates, assist with planning NIH grants, and offer letters of support to bolster grant applications.
- ASU Research Data RepositoryASU's institutional research data publishing platform is compliant only for de-identified data. Available to ASU affiliated researchers to submit openly accessible research data.
- Data Sharing ResourcesIncludes links to lists of NIH-supported data repositories and generalist repositories by the National Library of Medicine.
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).
Before submitting your data to your chosen repository, you will need to:
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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.
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De-identify your data, if appropriate
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Convert your data to an open, machine-readable file format such as .csv when possible
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Use data and metadata standards appropriate to your field (if any). Refer to fairsharing.org for a searchable database of standards.
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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
Refer to the Research Data Sharing and Management library guide for help on storing and publishing your research data.
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
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Addition of special terms and conditions to the award
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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?
Research Data Management and Sharing
- ASU Research Data ManagementResearch data management services and technology solutions for ASU research projects. We can assist with the preparation of data management plans, undertake technology needs assessments for your project, provide subsidized computing resources and data storage, and assist with data publication. A partnership with Knowledge Enterprise and the ASU Library.
- Open Scholarly PublishingSupporting Open Science and helping you meet funder open mandates, the Library Researcher Support team assists with research dissemination and traditional publication. If you are a new author, get guidance in choosing the right venue for your work. Experienced authors can benefit from insight into intellectual property rights and ways that ensure maximum impact for any research publication.
Research Integrity and Assurance
- ASU Human SubjectsTraining
IRB application
Review process
Modifying, continuing review and closing a study
General Support
- ASU Researcher Support (Knowledge Enterprise)A step-by-step guide to all the resources, services and support to researchers throughout the entire research life-cycle, from locating funding opportunities to commercializing new technologies. Select the dropdown on each section to find out which departments at ASU can help you with where you are in your project lifecycle.
NIH Guidance
- Final NIH Policy for Data Management and Sharing (2023)Complete NIH 2023 Policy (NOT-OD-21-013) including related announcements, summary and discussion
- NIDDK Central Repository Policy Notice (2024)(NOT-DK-24-003) This notice rescinds the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Data Sharing Policy (July 2013) and NIDDK Repository Usage Policy (March 2015) and introduces NIDDK Central Repository Resource Archival and Sharing Policy that aligns with timelines and requirements and expectations of the NIH Data Management and Sharing Policy and NIDDK Data Management and Sharing Guidance.
- FAQs about the 2023 NIH Data Management & Sharing PolicyFAQs are intended to help clarify the implementation of the NIH DMS Policy and are updated on an ongoing basis. The new Section F is dedicated to Budget/Cost questions.
- Supplemental Information: Elements of an NIH Data Management and Sharing Plan (2023)Information to help researchers choose data repositories suitable for the preservation and sharing of data
- Supplemental Information: Allowable Costs for Data Management and Sharing (2023)Costs you should factor into your budget. This information outlines categories of allowable NIH costs associated with data management and sharing to assist individuals and entities subject to the final NIH DMS Policy.
- Supplemental Information: Selecting a Repository for Data Resulting from NIH-Supported Research (2023)Information to help researchers choose data repositories suitable for preserving and sharing data (i.e., scientific data and metadata). Deposit in an established, quality data repository generally improves the data's FAIRness (Findable, Accessible, Interoperable, and Re-usable).
- Supplemental Information: Responsible Management and Sharing of American Indian/Alaska Native Participant DataConsiderations and best practices for the responsible and respectful management and sharing of American Indian/Alaska Native (AI/AN) participant data under the DMS Policy. Developed in response to Tribal Nations’ input received through Tribal Consultation and public comments from AI/AN organizations and community members, researchers, institutions, data providers and users, research participants, infrastructure developers, and others to further promote culturally respectful and effective research partnerships.
- Supplemental Information: Protecting Privacy When Sharing Human Research Participant DataInformation on privacy considerations when sharing human research participant data. This information is not intended to provide a guide for compliance with regulatory requirements, nor is it establishing binding rules for NIH awardees, but instead provides a set of principles, best practices, and points to consider for creating a robust framework for protecting the privacy of research participants when sharing data.
- Informed Consent for Secondary Research with Data and BiospecimensGuidance and sample language. (PDF)
- NIH Data STRIDES initiativeThe NIH Science and Technology Research Infrastructure for Discovery, Experimentation and Sustainability (STRIDES) Initiative allows NIH to explore the use of cloud environments to streamline NIH data use by partnering with commercial providers.
- NLM-ScrubberNLM-Scrubber is a freely available clinical text deidentification tool designed and developed at the National Library of Medicine.
- List of NIH activity codes subject to the DMS PolicyNIH activity codes included
Data management and sharing plan examples
Below are examples of data management and sharing plans that are helpful as guides for your own data management and sharing plan.
When developing your own plan or choosing an existing template, consider your own project needs.
- Directory of data management and sharing plan examplesCompiled from researchers, institutions, libraries, and workgroups who shared their data management plans online from 2012-2022 to help researchers comply with the 2023 NIH policy. Includes multiple funders and will not be updated.
- Converting a resource sharing plan into a DMS PlanSample plan created by the NIH DMSP Guidance for Data Support Services Working Group. An example of a resource-sharing plan written by a PI before the 2023 NIH Data Management and Sharing Policy. (PDF)
- Determination of Soil Damping by Hydraulic PendulumNSF-GEN generic, created with DMPTool (PDF)
- Doctoral Dissertation Research: An Agent-Based Model of Population Changes in a Vulnerable Coastal EnvironmentNSF-SBE: Social, Behavioral, Economic Sciences, created by Kenan, Louisiana State University with the DMPTool.
- Sample Data Management Plan for Depositing Data with ICPSR ArchiveData management and sharing plan provided by the Inter-university Consortium for Political and Social Research (ICPSR) to assist grant applicants. Edit and customize this text before submission. A letter of commitment from ICPSR confirming that it will archive the data should accompany the plan.
- U.S. Geological Survey (USGS) Data Management PlansA selection of DMP templates provided by USGS science centers and programs. Each template was designed with specific needs and use cases in mind. Some of the listed plans are for educational purposes only and are subject to change.
- National Institutes of Health (NIH) example submitted to Behavioral Medicine, Interventions and Outcomes Study Section [BMIO]Damian Yukio Romero Diaz. (2022). "Using natural language processing to determine predictors of healthy diet and physical activity behavior change in ovarian cancer survivors" [Data Management Plan] DMPHub. https://doi.org/10.48321/D1BK5T
Winner of the FASEB DMP prize. Created using DMPTool
Acknowledgment
from: https://data.library.arizona.edu/data-management/nih-data-management-sharing-policy-2023 CC By-NC 4.0
This guide was adapted from the University of Arizona's NIH Data Management and Sharing Policy (2023) page. ASU Library recognizes their expertise and authorship.