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NEW NIH Data Management & Sharing Policy

New from NIH

May 12, 2022 NIH released Informed Consent for Research with Data and Biospecimens: Points to Consider and Sample Language for Future Use and/or Sharing. This document is intended to provide sample language to investigators and IRBs when developing consent for secondary use of data/biospecimens.

June 6, 2022 DataWorks! Prize – Incentives for building a culture of data sharing and reuse

DataWorks! is a $500,000 ($100,000 each for five winners) prize purse, to reward data sharing and reuse in biomedical research. It is a partnership between the NIH Office of Data Science Strategy and the Federation of American Societies for Experimental Biology (FASEB).

August 25, 2022 NIH Data Management & Sharing Webinar Series

NIH is providing webinars on the new policy around data management and sharing of data. One was held on August 11, but the recording and slide deck are available on the website. At the end of the slide deck are all the links to the resources discussed. The second webinar is on September 22, 2022. They last 1.5 hours.

August 25, 2022 The White House Office of Science and Technology Policy (OSTP) new sharing guidelines

OSTP announced an update to the policy on public access to publications and data resulting from Federally funded research. The 12-month embargo is to be removed and data needs to be made available at the time of the publication. Federal agencies have been asked to create a plan to accomplish this by 2026.

Readings

The National Academies Press has a number of publications related to research. Here they have listed under subject headings

Also from NAP

Articles

Contaxis, N. et al. 2022. Ten Simple rules for improving research data discovery. PLOS.
https://doi.org/10.1371/journal.pcbi.1009768

Author

This library guide was created by
Daureen Nesdill, MS MLIS
Research Data Mgmt Librarian
Daureen is retired as of August 31, 2022, and will no longer be updating this library guide. Please go to sharing.nih.gov for updates.

Final NIH Policy for Data Management and Sharing

Notice Number: NOT-OD-21-013

Major Changes

  • The policy applies to all NIH-funded grants producing scientific data.
  • Data management is now included—not just sharing
  • Sharing also includes the data not related to any publication, e.g. null data
  • Need to share the data at the time of publication or at the closeout of the project
  • The days of sharing data as it is requested are over. Data needs to be submitted to a repository.
  • Cost of data management and sharing can be included in the grant budget.

When does the policy go into effect?

The date is Jan 25, 2023, but some centers and institutes have earlier dates so check with them.

Who is affected by the new policy?

Any researcher submitting a proposal to NIH on or after January 25, 2023. This includes researchers from all over the University of Utah campus. All research funded (in part or entirely) by NIH, e.g. extramural grants, contracts, intramural research grants, or any other NIH funding mechanisms. The policy does not apply to grants not generating data, i.e., training grants and infrastructure development. In addition, new policies exist for specific situations:

à   Genomic Data Sharing Policy
à   Model Organisms Sharing Policy
à   Research Tools Policy
à   Human Data Sharing including the Requirements for Registering & Reporting NIH-funded Clinical Trials in ClinicalTrials.gov

In simple terms what is the policy?

The Data Management and Sharing Plan, DMS is documentation of how you will manage and share your scientific data and any accompanying metadata while taking into account any potential restrictions or limitations. The plan is expected to be dynamic, i.e., changes may need to be made while conducting the research. The funding institute or center will need to approve the changes. Speak to your Program Officer.

The 2003 NIH Data Sharing Policy required a plan for sharing the data or justification for not sharing the data. NIH has expanded that policy to include documentation of how you will manage research outcomes during the project and after it has been completed. In addition, the policy for sharing publications resulting from the research has been as is still in effect since 2003. For a refresher on sharing publications see When and How to Comply.

The DMS plan is the documentation of the work you have always performed prior to submitting any other NIH grant to determine costs and timeline, for example:

  • determine the type and amount of data being collected
  • how it will be stored and who has access during the research process
  • deciding who is responsible for overseeing the data management process and sharing
  • documentation associated with the research
  • related tools, software, and code
  • standards for the data and metadata
  • how the data, etc. will be shared and with whom both during and after the closeout of the project

Add data preservation considerations, select an appropriate subject-based repository, and develop timelines for sharing. NIH has assembled information on the best practices for scientific data management for your education.

Why is NIH initiating this change?

In short, the NIH believes that sharing scientific data accelerates biomedical research discovery, in part, by enabling validation of research results, providing accessibility to high-value datasets, and promoting data reuse for future research studies. In addition, the world has been moving towards open research/science which means freely sharing the results of all research. UNESCO signed the Recommendation on Open Science in November 2021.

What is scientific data?

It is the same as the White House, Office of Management and Budget definition recorded in Circular A-110: 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.

additional information

Read the NIH overall instructions for your Data Management and Sharing Plan. In addition (1) check the funding institute or center to see if they have additional requirements, (2) determine where you will publish articles resulting from the work and check the journal’s requirements for the data and metadata, and (3) determine which repository you will submit your data/metadata to and learn of their requirements (see Repositories for Sharing Scientific Data).

The DMS plan should be included in the proposal as follows:

  • Extramural (grants): as part of the Budget Justification section of the application
  • Extramural (contracts): as part of the technical evaluation
  • Intramural: determined by the Intramural Research Program
  • Other funding agreements: prior to the release of funds

Allowable costs include:

  • Data curation and the development of documentation
  • Data management during the project
  • Preservation and sharing in repositories (funding must be spent before the closeout of the project)

Supplemental Information to the NIH Policy for Data Management and Sharing: Allowable Costs for Data Management and Sharing Notice Number: NOT-OD-21-015

The National Academies of Sciences Engineering and Medicine produced a report Life-Cycle Decisions for Biomedical Data: The Challenge of Forecasting Costs you can acquire from the National Academies Press. You can pay for a hard copy or download a free pdf. Login required.

In addition, NIH has produced a guide notice, Supplemental Policy Information: Allowable Costs for Data Management and Sharing Notice Number: NOT-OD-21-015 describing allowable costs. Also see Budgeting for Data Management and Sharing

From the NAP report: ASSESSING RESEARCH DATA COSTS A Checklist for Administrators at Research Institutions

A 10 minute video about the report

On August 11, 2022, NIH announced that they are working on a template for the DMS. It is still in the planning stages but a draft is available. The DMPTool will be updated when the draft is finalized. See PREVIEW: Data Management and Sharing Plan Format Page at NIH Forms & Applications for updates.

The University has access to the California Digital Library DMPTool to assist in writing the NIH DMS. Quick Start Guide is provided. Sign in with your UU email. Plans are listed under:

  • NIH-GEN DMSP (Forthcoming 2023)
  • NIH-GDS: Genomic Data Sharing

WARNING: NIH will still be finalizing their policy, therefore the DMPTool templates will be updated to reflect the changes. Do not assume once you have created a template you can use it for all grant submissions in the future.

Checklist for the Data Management and Sharing Plan

In general the plan should describe what data will be generated and how the research group will manage, store, and disseminate data generated (from Notice Number: NOT-HS-20-011):

  1. Types of primary data, samples, physical collections, software, curriculum materials, etc., (e.g., digital numeric data, photographs, video, acoustic records, database tables, spreadsheets, paper records, physical samples, etc.), which are produced during the project; necessary data flow, and produces the data entry/tracking plan.
  2. What metadata the proposed research will generate and how the metadata will be captured and structured (e.g., in a Word document, tab on data spreadsheet).
  3. Tools, e.g., a template that will be employed to capture metadata consistently through the search.
  4. The metadata standard(s) or formats to be used or considered to represent data and metadata elements in the data collection, including any modifications of the standard(s).
  5. The volume of data that is anticipated to be collected and growth to help understand the amount of digital storage space required during the course of the research.
  6. The anticipated time frame of the research effort in relation to the duration when digital storage space will be required.
  7. Indicate how the scientific data will be made discoverable and whether a persistent unique identifier or other standard indexing tools will be used, and whether the data contain Personally Identifiable Information or any information whose distribution may be restricted by law or national security.
  8. Indicate whether scientific data generated from humans or human biospecimens will be available through unrestricted (made publicly available to anyone) or restricted access (made available after the requestor has received approval to use the requested scientific data for a particular project or projects). If the scientific data will be shared through a restricted access mechanism, describe the terms of access for the data.
  9. If applicable, any documentation on specific terminology or guidance on valid values (e.g., “t” = time), and include or reference that documentation.
  10. Where and how the data will be stored initially (i.e., prior to being sent to a long-term archive facility), such as the use of data repositories.
  11. The minimum preservation time afforded by the proposed budget.
  12. Describe any future decision points regarding continued preservation, archiving, or retiring the data
  13. Describe any provisions for maintaining the security and integrity of the scientific data (e.g., encryption and backups, how the data will be protected from accidental or malicious modification or deletion, including data back-up, disaster recovery/contingency planning, and off-site storage relevant to the data collection).
  14. The quality control procedures, and the overall lifecycle of the data from collection or acquisition to making it available to the public and other researchers.
  15. The plan for addressing the study participants’ consent process to enable the de-identified data to be shared broadly for future research.
  16. The copyright and the intellectual property rights of the data. If applicable, indicate how intellectual property, including invention or other proprietary rights, will be managed in a way to maximize sharing of scientific data. Include any information relevant to the intellectual property rights associated with the scientific data, such as whether the intellectual property stems from an existing agreement or is anticipated to arise from the proposed research project itself.
  17. An estimated cost to implement the data management plan. This cost is allowable as part of the grant award direct costs or contract award price. Any costs associated with implementing the DMP should be explained in the Budget Justification.
  18. Address the roles and responsibilities of all parties with respect to the management of the data (including contingency plans for the departure of key personnel from the project) after the grant or research contract ends.
  19. Explain how the recipient plans to manage and disseminate data generated by the project.
  20. Describe how you will check for adherence to this DMP. Indicate the party responsible for managing the data.
  21. If data will not be available to the public, describe why data will be closed or limited. Note any ethical or legal reasons for limited public access.
  22. Describe any existing data sharing agreement(s), outlining the responsibilities of each party, as well as how scientific data can and cannot be used.
  23. Describe any existing general licensing terms, and any limitations on the scientific data use and reuse based on these terms. Describe whether the licensing is imposed by the applicant institution or whether it comes from any existing agreement(s).
  24. Describe alternative plans for maintaining, preserving, and providing access to scientific data should the original Plan not be achieved.
  25. Other Considerations: Indicate whether additional considerations are needed to preserve and make accessible implement the scientific data. Plan (e.g., prior permission to use a specific repository

After submission of the grant proposal peer reviewers may comment on the plan as part of the budget, but no score will be provided. Instead NIH program staff will assess the submitted plan.

At this point in time the NIH is saying:

NIH will monitor compliance with Plans over the course of the funding period during regular reporting intervals (e.g., at the time of annual Research Performance Progress Reports (RPPRs)). Noncompliance with Plans may result in the NIH ICO adding special Terms and Conditions of Award or terminating the award. If award recipients are not compliant with Plans at the end of the award, noncompliance may be factored into future funding decisions.

Both the University and the PI are responsible for complying with the new policy.

NIH expects researchers to maximize the sharing of their data but realizes ethical, legal, or technical concerns may limit sharing. NIH presents potential examples of justifiable factors including:

  • informed consent will not permit or will limit the scope or extent of sharing and future research use
  • existing consent (e.g., for previously collected biospecimens) prohibits sharing or limits the scope or extent of sharing and future research use
  • privacy or safety of research participants would be compromised or place them at greater risk of re-identification or suffering harm, and protective measures such as de-identification and Certificates of Confidentiality would be insufficient
  • explicit federal, state, local, or Tribal law, regulation, or policy prohibits disclosure
  • datasets cannot practically be digitized with reasonable efforts

Examples of reasons that would generally not be justifiable factors limiting scientific data sharing include:

  • data are considered to be too small
  • data that researchers anticipate will not be widely used
  • data are not thought to have a suitable repository

NIH respects and recognizes Tribal sovereignty and American Indian and Alaska Native (AI/AN) communities’ data sharing concerns, and NIH has proposed additional considerations when working with Tribes and AI/AN communities.

These DMS plans are not expected to be long narratives so 2-pages or less is appropriate.

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