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Managing Research Data: Data Management and Sharing Plans

The Scholarly Publishing and Academic Resources Coalition (SPARC) maintains a snapshot of Data Sharing and Article Sharing policies from U.S. federal agencies. The provided information may not necessarily reflect the most up-to-date agency policies, so researchers should always refer directly to the agency and the proposal solicitation for the most accurate policy information.

DMPTool provides a list of grant funders and their data management plan requirements.

Below are a few Data Management and Sharing Plan requirements from some larger federal funding agencies:

""If you have specific questions about your data management and sharing plan or would like feedback on the plan's contents, contact Dr. Dani Kirsch, Research Data Services Librarian.

While exact content requirements will vary between funding agencies and specific solicitations, many of the core components of a data management and sharing plan remain the same. Those components (along with some recommendations) are outlined below, based on a template from NIH.

The Data

Data To Be Collected

In your data management and sharing plan, you will describe what kinds of data will be collected or generated in your proposed project. Consider the types of data you will produce as well as the sources of those data. It is helpful to mention file formats as well as estimated volumes of data produced, particularly if you anticipate elevated data storage needs.

Open Research Recommendation: If your research will produce data in proprietary file formats and/or you use proprietary software or applications to conduct your research, think about what you can do to ensure maximum access to your research products. Is there an open source alternative to the software you use (e.g., open source QGIS instead of ArcGIS Pro)? Can you share your data in both the proprietary file format (which likely contains valuable information) as well as a non-proprietary alternative?

Metadata and Other Data Documentation

In addition to the data from your project, you should describe what other information is necessary to fully understand and interpret those data. Will you be using tools or applications that automatically produce metadata (such as EXIF metadata recorded with many digital photographs)? How will you document the protocols and other methodologies used in your project? When you conduct data cleaning and analysis, will you maintain records of the steps you took and why?

Related Tools, Software, and Code

This component is where you specify the kinds of tools, software, and/or code that will be used during your proposed project. This can include specific programs needed to visualize and work with particular types of data as well as more general statements about programs that can be used to access the data (e.g., common image viewing software, common spreadsheet-based software such as Microsoft Excel).

Open Research Recommendation: GitHub is a popular version control platform that many researchers use to collaborate and track changes. It works best at tracking plain text files such as .TXT, .JSON, .CSV, and coding scripts (e.g., .R, .IPYNB). GitHub content can be archived with Zenodo and given a DOI to cite.

Standards

Some disciplines or data types may follow particular standards for metadata, file formats, and even contents of the data itself. Some examples include the NIH's Common Data Elements (often used for recording data in clinical trials and other medical research), Cataloging Cultural Objects (used to create metadata for cultural artifacts like art and architecture as well as their visual representations), and the Federal Geographic Data Committee's geospatial metadata guidelines. Researchers may also mention any standard file formats they will use (e.g., .TIFF files for microscopy images, .PDF for page layouts of digital muscial scores).

Data Preservation, Access, and Associated Timelines

Preservation

For all research data, metadata, and other files (such as coding scripts) that will be shared as part of the proposed project, mention which data repositories have been selected for archiving those files. It is perfectly alright to list multiple repositories as your research files may have more than one appropriate destination. For example, Zenodo is equipped to handle all sorts of file formats and is a popular destination for software and code because of its partnership with GitHub, while repositories such as ICPSR and Databrary are more focused on sharing data from disciplines like behavioral, educational, and social sciences.

Open Research Recommendation: There are a LOT of data repositories out there! It can be difficult to figure out which of the hundreds of available repositories is reputable as well as applicable for your research. If you have questions about which one is a good fit for your data or are concerned about finding a free or low-cost option, contact the OSU Library's Research Data Services Librarian for assistance.

Access

Researchers should briefly describe ways in which the repositories chosen promote access to the shared data. Features such as providing persistent identifiers (e.g., DOIs) to data deposits, making data open access, and using unique identifiers (e.g., DOIs, accession numbers) to reference the data are all ways in which repositories and researchers can enhance access to the research data.

Timelines

The plan should mention not only when data will be made available, but also for how long. In general, U.S. federal funding agencies expect research data to be shared "as soon as possible" or "within a reasonable time" and they may set limits such as "no later than the time of an associated publication, or the end of performance period, whichever comes first" (NIH Policy for Data Management and Sharing). Reputable data repositories should guarantee a minimum duration of data access and preservation. For example, Zenodo promises long-term preservation for the lifetime of the repository, which it defines as "the next 20 years at least."

Access, Distribution, or Reuse Considerations

There may be certain factors (i.e., legal, ethical, or technical) that limit researchers' ability to share all data openly and publicly. Some examples include embargos related to patents coming from the research, national security concerns, or sensitive data that risk re-identification of human research participants. Federal funding agencies are typically willing to accommodate these limitations as long as they are disclosed in the data management and sharing plan and there are some data repositories that provide restricted access to data and authenticate prospective users.

Oversight of Data Management and Sharing

This final section clarifies which individuals are explicitly responsible for oversight of the data management and sharing plan. The Principal Investigator(s) for the project as well as the Vice President for Research are commonly mentioned as responsible parties. It is important to note that the data management and sharing plan is functionally a contract between the principal investigator, the institution, and the funding agency, so you should expect to be held to the standards set by your plan. Compliance with this plan may be evaluated annually and your progress toward data management and sharing activities may be expected as part of your annual progress report.

Major components based on contents of a sample NIH data management and sharing plan for non-human basic research.

""If you have specific questions about your data management and sharing plan or would like feedback on the plan's contents, contact Dr. Dani Kirsch, Research Data Services Librarian.

Many funding agencies allow researchers to include costs for data management and sharing in their budget proposal. After drafting the data management and sharing plan, you should have an idea of the tools, resources, and personnel needed for the proposed project. The funding agency website and/or solicitation should clarify allowable costs associated with data management and sharing. These allowable costs may include (but are not limited to):

Hardware, Software, and Other Computational Resources

There may be specific needs for data infrastructure during the project to accommodate data management and storage needs. Check out the Data Check-Up on "Data Storage and Security at OSU" (opens PDF) to learn more about resources and services provided at OSU or view IT's guidance information on what data may be stored on certain applications (Section 5.02). You can also visit webpages for OSU's High Performance Computing Center and Data Center and Cloud Services for more information about storage and computing options.

Services and Personnel Dedicated to Data

There may specialized personnel or particular services required (or desired) related to the documentation and cleaning of data, re-formatting and other curation of data to meet community standards, de-identification of sensitive data (such as from research involving human participants), and metadata preparation.

Fees for Data Centers, Data Curation, and Repositories

Repositories may charge fees for things such as data curation, data deposit, or open access to the data. There may also be charges associated with increased storage needs for projects that produce a large volume of data that need to be shared.

  • The generalist data repository Dryad charges a $150 USD data publishing charge per submission that covers costs of data curation and preservation and charges a storage fee for data exceeding their 50GB default.
  • Social science researchers looking to deposit data in the Inter-University Consortium of Political and Social Research (ICPSR) should budget for data curation services provided as part of the deposit process. Researchers can contact the ICPSR help email for a curation cost estimate to include in their grant proposal. Alternatively, researchers can publish in openICPSR for free, but data curation there is the responsibility of the researcher(s).

If your grant budget is tight, don't worry! Not all repositories charge you fees for depositing or making your data open access, so you won't necessarily incur costs associated with sharing your data in a data repository. The two repositories outlined below are more generalist (meaning they accept data from all disciplines) but there are also discipline-specific repositories that allow for free, open access data deposits.

  • Open Science Framework (OSF) is free by default, and public projects have a 50GB storage allotment. Storage needs beyond the 50GB threshold have costs based on the amount of additional storage needed, as outlined on OSF's storage tiers page.
  • Zenodo is also free to deposit in and provides storage for up to 50GB of data. Additional storage may be granted in some instances, but researchers should contact Zenodo with this request.
Don't forget: Allowable costs often must be incurred during the performance period, so you will need to plan ahead so that costs such as data deposit fees are paid before the end of the performance period.

You can learn more about allowable costs on websites for various funding agencies such as NSF and NIH.

Allowable cost suggestions sourced from NIH's page on Budgeting for Data Management and Sharing and the Other Direct Costs section of Chapter 2 of the NSF's Proposal & Award Policies & Procedures Guide.

""If you have specific questions about your data management and sharing plan or would like feedback on the plan's contents, contact Dr. Dani Kirsch, Research Data Services Librarian.

DMPTool provides a list of grant funders and their data management plan requirements which also includes some sample data management plans.

National Institutes of Health (NIH) provides several sample plans.

The Inter-university Consortium for Political and Social Research (ICPSR) provides example language for a data management and sharing plan when the PI intends to deposit data with ICPSR.

University of California San Diego provides numerous example data management plans from NSF project proposals submitted by their faculty.

""If you have specific questions about your data management and sharing plan or would like feedback on the plan's contents, contact Dr. Dani Kirsch, Research Data Services Librarian.

OSU is a participating institution with DMPTool. When you log in to DMPTool, log in with your okstate email so that you can select Oklahoma State University as your institutional affiliation. DMPTool provides templates and walk-throughs for data management and sharing plans from a variety of funding agencies and institutions.

Download the slide deck from the Data Bytes workshop "Drilling Down on Data Management and Sharing Plans" (last updated September 11, 2024)

The Inter-university Consortium for Political and Social Research (ICPSR) provides a Framework for Creating a Data Management Plan.

U.K. Data Service provides a Data Management Checklist with important considerations for your research project.

DataONE has a lesson and hands-on exercise that covers Data Management Planning.

""If you have specific questions about your data management and sharing plan or would like feedback on the plan's contents, contact Dr. Dani Kirsch, Research Data Services Librarian.