Planning for a project involves making decisions about data resources and potential products. A data management sharing plan describes data that will be acquired or produced during research; how the data will be managed, described, and stored, what standards you will use, and how data will be handled and protected during and after the completion of the project.
For assistance with your data management plans, please contact Michelle Leonard or the Strategic Research Development Team.
For assistance with the proposal budgeting process, please review the DMS section of DSP’s Other Direct Costs webpage, or contact the DSP Proposal Team.
Jump ahead to the Repositories.
The image of the data management sharing plan provides an overview of how to incorporate FAIR (Findable, Accessible, Interoperable, Reusable) principles while meeting the requirements of the data management sharing plans. To save time and effort, it is important to develop your data management sharing plan at the beginning of your project. Consult with the UF Strategic Research Development team to set a timeline, discuss the new requirements, and determine what campus data services you may need.
Data should be shared no later than the time of a publication of findings in a peer-reviewed journal OR at the end of the award, whichever comes first.
NIH has a longstanding commitment to making the results of NIH-funded funded research available. Responsible data management and sharing has many benefits, including accelerating the pace of biomedical research, enabling validation of research results, and providing accessibility to high-value datasets.
NIH defines scientific data 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, (e.g., laboratory specimens).
Scientific data will vary depending on the project and the context.
Do you need a DMS Plan?
A complete list of NIH grant programs can be found here. Or, you can use the NIH decision tool to determine what sharing polices apply to your research in 5 minutes or less.
|DMS Policy applies to all research that generates scientific data||DMS Policy does not apply to research and other activities that do not generate scientific data|
|Research Projects||Training (T)|
|Some Career Development Awards (Ks)||Fellowships (F)|
|Small Business SBIR/STTR||Construction (C06)|
|Research Centers||Conference Grants (R13)|
|Research-related Infrastructure Programs (S06)|
Once you determine that your NIH grant requires a DMS plan, follow these five basic steps:
Writing a Data Management & Sharing Plan
This information includes the expectations of NIH, and the required information. Click on the image to download the sample format. Download this DMS checklist to verify you have addressed all the required elements. (Source: Ye, H., et al. (2022), https://doi.org/10.17605/OSF.IO/UADXR). Another option for writing a DMS plan is to use the DMPTool.
Budgeting for Data Management & Sharing Plan
This information includes allowable & unallowable costs, request & justify data management and sharing costs, and an assessment of the budget during the performance periods, including subsequent periods.
Proposal budgets should include estimated funds needed for data management and sharing activities. These should include all allowable costs for DMS for all data types. These costs should be budgeted under Other Direct Costs and best practice is to plan on full storage costs being incurred during the period of performance. For additional information on budget guidance, please review the UF DSP webpage.
|Allowable costs||Unallowable costs
|Creating data||Infrastructure costs (F&A)|
|Developing supporting data||Cost for routine conduct of research|
|Formatting data||Costs charged as both direct and indirect|
|Preparing metadata to support FAIR principles|
|Local data management considerations|
|Deposit fees for established repositories|
|Sample||Description||Institute or Center|
|Sample Plan A||Clinical and/or MRI data from human research participants||NIMH|
|Sample Plan B||Genomic data from human research participants||NIMH|
|Sample Plan C||Genomic data from a non-human source||NIMH|
|Sample Plan D||Secondary Data Analysis||NIMH|
You may need to review the best practices for protecting privacy when sharing human research participant data (NOT-OD-22-213):
Be sure to check the NIH Scientific Data Sharing FAQs regularly for updates.
As outlined in NIH’s Supplemental Policy Information: Selecting a Repository for Data Resulting from NIH-Supported Research, using a quality data repository generally improves the FAIRness (Findable, Accessible, Interoperable, and Re-usable) of the data. For that reason, NIH strongly encourages the use of established repositories to the extent possible for preserving and sharing scientific data.
When selecting a repository, some programs such as NIH and/or Institute, Center, Office (ICO) policy, and Funding Opportunity Announcements (FOAs) identify a particular repository (or multiple repositories) to be used. Check out the list of NIH-supported scientific data repositories.
NIH supports the Generalist Repository Ecosystem Initiative (GREI) that includes seven established generalist repositories that collaborate to establish consistent metadata, develop use cases for data sharing, train and educate researchers on FAIR data, and the importance of data sharing. These recommended generalist repositories are a great tool for all types of data sets.
Not sure which generalist repository to choose? Download this comparison chart.
Check out the GREI Collaborative Webinar Series on data sharing.
If you feel like exploring more repositories, check out the Registry of Research Data Repositories.
Data sets are scholarly activities.
Citing data is as important as citing any type of publication. Styles differ depending on the citation style but the following information is usually required:
Example of cited data sets
APA 7th edition:
Lastname, F. M. or Name of Group (Year). Title of dataset (Version No.) [Data set]. Publisher.
DOI or URL
Use a citation manager to help manage, organize, and store all your citations.
Need additional help choosing a citation manager? Reach out to the UF librarians: LIBD-CitationManagers@uflib.ufl.edu