General questions and answers about the new DMS Policy that may not be covered on other pages, as well as questions pertaining to UNMC-specific elements and procedures are included below. We will continue to gather answers to new questions and update this page. Visit Writing Your Plan (DMPTool) for specific questions about DMPTool.
Many additional questions specific to the NIH policy have been compiled and disseminated by the NIH and can be found on their DMSP FAQ page.
Where can I get help at UNMC for the NIH Data Management and Sharing Policy?
Several groups on campus will play a role in assuring UNMC and its researchers are ready to meet these new policy changes. Please direct any questions you have to firstname.lastname@example.org.
Alternatively, set up a consultation with UNMC's Data Services Librarian, Lisa Chinn, PhD, MSLIS using the bookings page through the McGoogan Health Sciences Library.
Who is checking my data management and sharing plan?
The UNMC Sponsored Programs Office will check for presence of a plan within your application. They will not review your plan’s quality or confirm that all plan parts are present for your type of research. For a thorough review of your plan, please contact email@example.com.
Am I expected to share all data generated during my research?
No. Under the DMS Policy, researchers are expected to maximize the appropriate sharing of scientific data, which is defined as data commonly accepted in the scientific community as being of sufficient quality to validate and replicate the research findings.
How does the DMS Policy fit in with other NIH data sharing policies and requirements (e.g., individual NIH Institute/Center or Office (ICO) funding polices, the NIH Genomic Data Sharing (GDS) Policy, the NIH Policy on Dissemination of NIH-Funded Clinical Trial Information)?
The DMS Policy establishes the foundation for NIH’s data management and sharing expectations, which NIH ICOs and programs may build upon to meet their programmatic needs (e.g., designated repositories, specific data collection standards). Current NIH policies specific to certain types of research (e.g., clinical trials, research generating large-scale genomic data) continue to apply and complement the goals of the new DMS Policy.
If researchers are reusing existing, shared data to generate new datasets, are they expected to reshare the primary data they incorporated into their new analysis? Are the derived data generated considered scientific data and expected to be shared?
The DMS Policy applies to research that results in the generation of scientific data. Scientific data can result from secondary research, but researchers are not expected to share the existing, shared primary data used to conduct the secondary research. Researchers are, however, expected to maximize appropriate sharing of any new, derived data generated as a result of their research.
Does the DMS Policy apply to social and behavioral scientific research? Can qualitative data be “scientific data”?
Yes, NIH-supported social and behavioral scientific research that results in the generation of scientific data are subject to the DMS Policy. Qualitative data may constitute scientific data if it meets the definition in the DMS Policy.
What steps does the DMS Policy take to ensure institutions and researchers protect research participants?
Award recipients must comply with any applicable laws, regulations, statutes, guidance, or institutional policies related to research with human participants and that protect participants’ privacy.
Does the DMS Policy expect that research informed consent obtained from research participants must allow for broad sharing and the future use of data (either with or without identifiable private information)?
No. Informed consent for participation in research remains the cornerstone of trust between researchers and research participants and thus the DMS Policy does not dictate how this process is achieved. Rather, researchers’ intention for scientific data management and sharing, as proactively described in Plans, is strongly encouraged to be part of the informed consent process. The DMS Policy does not expect that informed consent given by participants will be obtained in any particular way.
How will noncompliance with the NIH DMS Policy be handled?
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.
What is a data or metadata standard?
The National Center for Data Services describes metadata as “information that describes, explains, locates, classifies, contextualizes, or documents an information resource.” In the context of data management, metadata allows you to track the provenance, or original source of a dataset, and help you to track which version of the data you are analyzing. Describing data in a machine-readable format allows you to search for data in a repository.
How will data management plans be assessed?
The evaluation of DMS Plans will be conducted by the agency, with input from the Contracting Officer’s Representative (COR) and other NIH subject matter experts as part of the proposal evaluation process.
Are projects establishing repositories or creating data infrastructure subject to the DMS Policy (i.e., establishing a data coordinating center with no research question proposed)?
No. Projects that only develop or support infrastructure resources (e.g., repository or knowledgebase establishment) and do not generate findings or scientific data are not subject to the DMS Policy. However, NIH recommends that the infrastructure developed with NIH resources comport with the desired characteristics for repositories (see “Selecting a Repository for Data Resulting from NIH-Supported Research”).
How should we handle situations where there are proprietary considerations about confidential data or intellectual property?
The NIH covered this briefly as part of a webinar, which can be found during this section of their recording. For more information specific to your situation, we would recommend you reach out to firstname.lastname@example.org.
How granular does the stored data have to be? Most of the time data are reduced from original capture to make it more manageable. Should it be original data or reduced data?
You should be storing all data, both raw and processed. The data management and sharing plan will ask where you plan to store data 1) during the lifetime of the project and 2) after the grant has ended. You will need to have a plan for storage during and beyond the life of the project. Thus, storing is only the first component. Secondly, you’ll need to think about preservation of the data. Where will this data live after the project is over? This is where data repositories—and finding and appropriate data repository in the grant application phase—is of the utmost importance. Thirdly, you’ll be asked about your data sharing plan. Do you plan to share the raw and processed data, or just the processed data? It is up to you to ask what “manageable” means for your project. That being said, the policy is about making your data replicable and reusable by other researchers, so if the data that you usually share is reduced data, then can another researcher re-use that data and replicate the results adequately? If not, then you may need to think about sharing the raw and reduced data. If so, then you are sharing the data adequately.
How are we addressing patent implications? My reading of the policy is that when the grant ends, data needs to be available.
If there are patent implications for an invention, we recommend reaching out to UNeMed at the point at which you are writing your data management and sharing policy. In terms of general intellectual property, PIs own rights in data resulting from sponsored projects. Sponsored projects are not works for hire, and thus the sponsor does not own the data.
Data sharing is essential for expedited translation of research results into knowledge, products, and procedures to improve human health. Sponsors generally endorses the sharing of final research data. One exception is personal health information.
Have agencies other than the NIH also mandated data management/sharing plans, and will these work via the same DMP tool we now have?
Yes. Almost every grant-funding agency—both federal and private—in the country is either in the process of developing a data management and sharing policy or has one in place. All grant-funding agencies have templates uploaded in to DMPTool. Simply choose the appropriate funding agency when creating a DMPTool data management and sharing policy and use the subsequent template.
How long should data be shared beyond the term of the NIH-funded grant? Can this be budgeted into the cost of Data Management and Sharing?
Data should be shared for at least 3-5 years after the award period. However, most repositories share data in perpetuity. Data repositories do not charge for ongoing storage of your data. Once the data is uploaded to the repository, a repository will not ask for further monetary assistance. Should you find a data repository that is asking for more funding after upload of data, please reach out to email@example.com.
Do K99/R00 grants require a plan?
No. At this time, the NIH is not requiring training grants to include a data management and sharing plan, because the DMSP is only required for the collection of scientific data. However, the NIH has made it clear that this exception may change in the near future.
Are there repositories for qualitative (narrative transcripts) data?
Absolutely. There are discipline-specific repositories, found here: re3data.org, and generalist repositories listed here: https://www.unmc.edu/spa/policies/nihdmsp/repository/index.html. You can also reach out to firstname.lastname@example.org for a consultation on qualitative data repositories.