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NIH Data Management and Sharing Policy

Need assistance with NIH Data Management and Sharing?

The 2023 NIH Data Management and Sharing (DMS) Policy is a policy applies to all research, funded or conducted in whole or in part by NIH, that results in the generation of scientific data. The policy details expectations and requirements regarding data management and sharing of scientific data generated out of NIH funded projects as well as budgeting for the costs to do so. The policy is effective January 25th 2023, and applies to all awards with receipt dates on or after that date.

NIH Sharing Website: In addition to the information here, the NIH has set up a website that goes into detail on the policy and related information. Access the NIH Data management and Sharing Policy Webpage.

Where can I get help on understanding the new NIH DMS Policy?

Duke personnel should reach out to researchdata@duke.edu concerning any questions on the NIH DMS policy they may have. For inquiries specific to writing a DMS Plan please reach out to datamanagement@duke.edu.

Main Policy Points

  1. Data Management and Sharing Plan (DMSP): As part of the project proposal you are required to submit a Data Management and Sharing Plan (DMSP) detailing the data management during the project, AND sharing plans for after the project. This plan will be treated as a term and condition of the award and is expected to be adhered to throughout the life of the award.
  2. Sharing Scientific Data: Scientific data generated out of the project should be shared as soon as possible. No later than the time of an associated publication to work conducted in the project, or the project end of performance period, whichever comes first.
  3. Budgeting for the managing and sharing of data: Costs associated with data management and sharing during the project period can now be charged as direct costs. A budget for implementation of your DMSP is now required as part of your proposal.
What funding types does the policy apply to?

The DMS Policy applies to all research, funded or conducted in whole or in part by NIH, that results in the generation of scientific data regardless of funding amount or funding mechanism.

A NIH provided definition of scientific data can be found below:

Scientific Data is defined as data 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 includes any data needed to validate and replicate research findings.
  • Scientific data does 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.
     

For a full list of NIH activity codes subject to the DMS policy please see the following:

https://sharing.nih.gov/sites/default/files/List-of-Activity-Codes-Applicable-to-DMS-Policy.pdf
 

The DMS Policy does not apply to research and other activities that do not generate scientific data, including: Ts, Fs, KM1, C06, R13, Gs, S06

Data Management and Sharing Plans

The NIH requires all applicants planning to generate scientific data to write a DMS Plan that describes the management and sharing of scientific data during and after the award period.

DMS Plans should be at maximum 2 pages and attached to the proposal application as a pdf file.
Plan Elements

Plans should address the following six elements.

1. Data Type

  • General summary of types and estimated amounts of scientific data to be generated or used.
  • Describe which scientific data will be preserved and shared, with reasoning being provided of why certain data may not be shared based on legal, ethical and technical factors being documented in the plan.
  • Brief listing of metadata and documentation that will be made accessible to facilitate interpretation of data.

2. Related Tools, Software and/or Code

  • State whether tools, software or code are needed to access or manipulate the data, and if so provide the names and versions if applicable.
  • If applicable, specify how needed tools can be accessed, and, whether such tools are likely to remain available for as long as the scientific data remain available.

3. Standards

  • State what common data standards (if any) will be applied to the scientific data and associated metadata. Describe how these data standards will be applied (may be related to data formats, data dictionaries, definitions, identifiers, etc.) to the scientific data generated by the research proposed in this project. If applicable, indicate that no consensus standards exist

4. Data Preservation, Access and Timelines

  • Describe when scientific data and metadata/documentation associated with your research will be made available. It is highly recommended to put your datasets into an established data repository, which are organizations that collect, manage, and archive datasets for data analysis, sharing and reuse. In some cases, a repository may be specified by the funding Institute or Center. In cases where it is not specified, the NIH has guidance on selecting suitable repositories. Small datasets (up to 2 GB in size) may be included as supplementary material to accompany articles submitted to PubMed Central rather than using a separate repository. Duke also provides the Duke Research Data Repository as an option for data that may be openly shared.
  • Describe how the data will be findable and identifiable (i.e., with a persistent identifier such as a DOI number)
  • Describe when the data will be made available for sharing and for how long. Please note that data must be shared no later than time of an associated publication or end of the performance period, whichever comes first. Researchers are encouraged to consider requirements and policies (e.g., data repository policies, award record retention requirements, journal policies) as guidance for the minimum time frame scientific data should be made available.

Note that depositing data in to a repository qualifies as data retention for the purposes of the Duke University Retention Policy of 2023. Though please note that the Duke policy states that data must be retained for a minimum of 6 years, so if data is taken out of a repository prior to 6 years after the publication the dataset was associated with was published, the data must be stored in another location accessible to Duke.

5. Access, Distribution, or Reuse Considerations

  • Describe any privacy, security, consent or proprietary issues that might affect access and reuse (informed consent, privacy, confidentiality or other regulatory or contractual protections).
  • Whether access to data derived from human subjects will be controlled (e.g. made available by a data repository only after approval).
  • If generating scientific data derived from humans, describe how the privacy, rights, and confidentiality of human research participants will be protected (e.g., through de-identification, Certificates of Confidentiality, and other protective measures). See also the NIH Guidance Protecting Privacy When Sharing Human Research Participant Data.

6. Oversight of Data Management and Sharing

  • Describe how compliance with this Plan will be monitored and managed, frequency of oversight, and by whom at your institution (e.g., titles/office name, roles).

Note on the level of Detail in plans:

The NIH does not expect researchers to necessarily have all details at the application stage and the advice is to give your best educated guesses for any information that you do have yet.

If there are any clarifying details that the program officer wants in your plan they will give you feedback and you can revise them at Just in time submission.

Plans will be expected to be updated at reporting periods like RPPR to reflect any new changes or plans for the project.

Plan Review

Program staff at the proposed NIH Institute or Center will assess DMS Plans, not peer reviewers. During peer review, reviewers will not be asked to comment on the DMS Plan nor will they factor the DMS Plan into the Overall Impact score. Peer reviewers will only use the information found in the budget justification to determine whether the requested Data Management and Sharing Costs are reasonable.

Templates, Examples and DMPTool

DMS Plan Template

The NIH has provided a template of Data Management and Sharing Plan Format Page for writing a DMS Plan. Please note that the template has text in italics to help explain the answers for each element. This italicized text should be deleted prior to submitting the DMS Plan.

DMS Plan Examples

The National institute of Mental Health (NIMH) has provided examples that are consistent with the expectations of the NIH. Please note that there are also additional elements required by NIMH that shown in these examples, but they are labeled as NIMH required.

Additional examples from the NIH and other NIH ICOs will be shared as they become available

DMPTool

The DMPTool is an online tool that can provide templates and helpful information to assist you in writing your DMSPs. We highly recommend this as a starting place for writing a DMSP as it provides detailed guidance on how to write plans as well as sample language for each element. To draft the plan itself, go to the DMPTool website, Log in using your Duke Shibboleth and create a new plan using the NIH 2023 template.

Please note that DMS Plans are to be at maximum two pages.

Sharing Data

Timing for Sharing Scientific Data

The NIH expects that Scientific data generated out of the project should be shared as soon as possible. No later than the time of an associated publication to work conducted in the project, or the project end of performance period, whichever comes first. No costs extensions will extend this timeline to the new end of the performance period.

Methods for Sharing Scientific Data

The NIH highly recommends the use of established data repositories, which are organizations  that collect, manage, and archive datasets for data analysis, reuse, and sharing of the scientific data associated with a project.

For some programs and types of data, the NIH or NIH ICO will identify a NIH supported data repository or set of repositories that should be used. This will be identified in the Funding Opportunity Announcements (FOAs). In cases where the NIH or NIH ICO does not specify a particular repository, researchers should select a discipline or data type specific repository to deposit their data. In cases where there isn’t an appropriate discipline or data type specific repository, the Duke Research Data Repository or one of several generalist repositories may be used.

Please note that small datasets (up to 2 GB in size) may be included as supplementary material to accompany articles submitted to PubMed Central (instructions) rather than in a separate repository.

For more information on choosing the most appropriate data repository for your research please see Selecting a Data Repository or contact datamanagement@duke.edu for assistance selecting Duke-sponsored options.

Scientific Data involving Human Participants

Researchers and DMP Plans must comply with applicable laws, regulations, statutes, guidance, or institutional policies related to research with human participants. The NIH encourages DMS plans to address several factors around human participant research including:

  • Detailing in their plans how the privacy and confidentiality of human participants will be protected. Example of these include de-identification of data, and issuing Certificates of Confidentiality amongst others.
  • Making sure human participants understand how their data will be managed and shared during the informed consent process and that these details are listed on the informed consent form. Please note that the NIH DMS Policy does not mandate the type of sharing that should be done for human participant research, only that the NIH expects that researchers will try to maximize scientific data sharing.
  • Detailing if scientific data from human participants will be shared via controlled access (more information on controlled access repositories below) even if data has been deidentified.
  • Detailing certain factors (i.e., ethical, legal, or technical) may necessitate limiting sharing to some extent. (Examples include but are not limited to: informed consent will not permit or will limit the scope or extent of sharing and future research use; the privacy or safety of research participants would be compromised or place them at greater risk of re-identification; or restrictions imposed by existing or anticipated agreements or laws)
Repositories by Access Type

The NIH highly recommends using established data repositories for data sharing There are two main types of repository access you can choose when depositing your data after your project is completed.

  • Open access refers to a repository where research data are shared and accessed freely. Open access repositories can place licenses on the datasets to set limitations on the use of that data while still allowing it to be accessed freely by anyone. But for the most part these are used for unrestricted sharing.
  • Controlled access refers to a repository where research data will only be shared under certain criteria set by the depositor and repository. These often include a formal application and approval process; Such as terminal degree requirements, IRB approval, formal Data Use Agreement, and Data Security Plans (if requestor wants to hold data locally).  These are used for data in which there could be harm if the data were shared freely such as data with explicit limitations on sharing such as if the data pose particular risks to participants or groups, cannot be sufficiently de-identified or there are unanticipated risks are discovered after initial planning.

Please note that some repositories are both open access and controlled access repositories.

Deposit Fees and Curation

It is highly recommended that you contact the data repository you are interested in using during the proposal process in order to get details about that repository’s data deposit fees and data curation requirements in order to include those details in your DMS plan and budget. In addition, repositories can provide boilerplate language about them for your DMS Plan.

For questions around data curation or about repositories in general, please reach out to datamanagement@duke.edu

Data Management and Sharing Allowable and Unallowable Costs

Allowable

The new NIH DMS Policy allows for costs related to data management and sharing incurred during the performance period to be charged to the grant. These include:

  • Personnel costs regarding the curation and management of data and related documentation: this includes formatting data according to accepted community standards; de-identifying data; attaching metadata to foster discoverability, interpretation, and reuse; and formatting data for transmission and storage at a selected repository for long-term preservation and access. 
  • Fees for depositing and preserving data in repositories after the award is over. Please note that the costs of preserving and sharing the data in a repository must be paid in full during the performance period.
  • Fees for local data management considerations during the active phase of the award, such as specialized infrastructure (ex. PACE)
  • *For research involving genomic data/subject to the NIH GDS policy only: Fees or costs relating to genomic data management and sharing
Unallowable

Budget requests for Data Management and Sharing must not include:

  • Costs that are typically covered under Facilities and Administrative costs (aka. indirect costs)
  • Cost associated with the routine conduct of research.
  • Costs associated with collecting or otherwise gaining access to research data as these are considered costs of doing research.
  • Costs that are double charged or inconsistently charged as both direct and indirect costs
Budgeting

Additional Duke related tools coming soon.

External tools and resources to help you understand and create a budget can be found below:

 

Please note that for Duke related data services it is best practice to reach out to those services during the proposal development stage in order to get cost estimates for your budget.

Requesting Funds

Duke specific details coming soon. In the meantime please see the NIH webpage on Budgeting for Data Management & Sharing

Help & Frequently Asked Questions (FAQs)

Duke Resources to help

Regarding help with creating your DMSPs, writing informed consent language, data curation consultations and assistance and consultations around appropriate licensing and data sharing agreements for repositories, you can reach out to the Duke University Libraries at datamanagement.edu.

For questions around the NIH DMS policy or Duke implementation of the NIH DMS Policy please reach out to researchdata@duke.edu.

NIH Resources to help
FAQS