NIH SBIR
NIH SBIR Data Management and Sharing Plan: What Startups Must Include
Learn what an NIH SBIR Data Management and Sharing Plan must cover, including repositories, proprietary data, sharing deadlines, and allowable costs.
Determine which project data fall under NIH’s sharing policy
An NIH SBIR Data Management and Sharing Plan explains how your company will manage scientific data, preserve supporting documentation, and make appropriate data available to others. NIH’s Data Management and Sharing Policy applies to NIH-funded research that generates scientific data, including SBIR and STTR projects. For a startup developing a diagnostic, therapeutic, medical device, or research tool, the plan should connect the proposed experiments to specific datasets and realistic sharing commitments.
NIH defines scientific data as recorded factual material of sufficient quality to validate and replicate research findings, regardless of whether those data support a publication. In a diagnostic development project, that could include assay measurements, specimen characteristics, and performance results. NIH’s definition excludes items such as laboratory notebooks, preliminary analyses, drafts, and physical specimens. Map the data your project will generate against this definition before deciding what to preserve and share.
Create a working inventory with each dataset’s source, format, estimated volume, sensitivity, and responsible owner. Include data generated by contract research organizations and university subawardees. Check the funding opportunity and relevant NIH Institute or Center requirements for additional expectations. Genomic data, clinical trial information, and certain specialized datasets can trigger policies that operate alongside the general sharing policy. A clear inventory makes those obligations easier to identify before submission.
Address all six elements with project-specific commitments
NIH organizes the plan around six elements: data type; related tools, software, and code; standards; data preservation, access, and associated timelines; access, distribution, or reuse considerations; and oversight. Use the current NIH application instructions and any opportunity-specific directions to structure your attachment. Within each element, identify actual project decisions. A useful data-type statement names the measurements, expected file formats, and supporting metadata that another researcher would need to interpret the results.
For tools and standards, explain how others can open, understand, and analyze the shared files. An imaging project might preserve images in an established format and provide acquisition settings, annotation definitions, and analysis code where appropriate. An assay project might provide machine-readable result tables, units, calibration information, and a data dictionary. When specialized software is required, describe how users can obtain it and identify any licensing or access conditions.
For preservation and oversight, identify the intended repository, the expected deposit schedule, and the person responsible for implementing the plan. Describe who will review datasets for completeness, remove or protect sensitive information, and confirm that deposits meet repository requirements. Assigning oversight to the principal investigator while naming a scientist or data manager for operational tasks creates a practical division of responsibility. Ensure these responsibilities also appear in relevant collaborator agreements and internal procedures.
Explain how proprietary information and participant privacy affect sharing
NIH recognizes that ethical, legal, and technical factors can affect data sharing. Its policy also recognizes legitimate proprietary interests and applicable SBIR/STTR data protections. A startup should explain the specific limitations affecting each dataset and the sharing arrangements it can support. Separate scientific measurements from confidential manufacturing details, patent-sensitive disclosures, licensed datasets, and identifiable participant information. This classification helps NIH assess your proposal and helps your team implement the approved plan consistently.
For patent-sensitive findings, coordinate the sharing schedule with intellectual property counsel early enough to support timely patent filings. For third-party data, review license terms before promising public redistribution. If proprietary restrictions affect sharing, describe their basis, scope, and expected duration in the plan. An agreement with a testing vendor should address your company’s access to underlying results and supporting documentation so that the company can meet its NIH commitments.
Human participant data require particular care because consent language, privacy protections, and repository access rules must align. Explain whether data will be de-identified, whether controlled access is appropriate, and what restrictions apply to secondary use. NIH encourages consideration of controlled access for sensitive human data, including some de-identified datasets. Projects subject to the NIH Genomic Data Sharing Policy have additional requirements that should be coordinated with the institutional review board and relevant institutional officials.
Choose a repository and budget for the full sharing workflow
NIH encourages established repositories that provide appropriate expertise, metadata support, persistent identifiers, and access controls. Some data types have designated or strongly preferred destinations under applicable policies. Sequence datasets, for example, may fit resources within the National Center for Biotechnology Information, while other projects may need a discipline-specific or generalist repository. NIH’s repository guidance is a useful starting point. Confirm that your selected repository accepts your dataset type, size, and proposed access conditions.
Budget for the work required to make the deposit usable. NIH permits reasonable, allowable costs for activities such as data curation, documentation, de-identification, formatting, and repository deposition. Include those expenses in the appropriate application budget categories and explain them in the budget justification using current NIH instructions. General infrastructure expenses need appropriate treatment under the company’s accounting practices, including allocation through indirect costs when applicable. Keep each cost tied to an identifiable project activity.
Build estimates from staff effort and repository pricing. For example, calculate the hours required to validate result tables, prepare a data dictionary, review privacy risks, and complete repository submission. Storage and preservation costs vary with file volume, retention arrangements, and access services. NIH allows certain preservation and sharing costs for periods beyond the award when those costs are incurred during the award period. Obtain repository terms early enough to support both the estimate and the proposed schedule.
Turn the approved plan into an award-management checklist
NIH generally expects scientific data to be shared as soon as possible, no later than the associated publication or the end of the award’s performance period, whichever comes first, subject to applicable requirements and justified limitations. Set internal deadlines before those events. A manuscript acceptance date can arrive while the team is still cleaning files or reviewing patent disclosures. A project calendar should connect experiment completion, quality checks, privacy review, intellectual property review, and repository deposit.
NIH program staff assess the plan, and compliance with an approved plan becomes a term and condition of award. Track implementation throughout the project and report progress through the applicable Research Performance Progress Report requirements. If the selected repository closes, consent restrictions change, or the research generates a materially different dataset, discuss the change with your NIH program officer and follow the required approval process for revisions. Maintain records of deposits, identifiers, access restrictions, and associated expenses.
Before submission, review the plan alongside the research strategy, human subjects materials, vendor agreements, and budget. The documents should describe the same datasets, responsibilities, and timelines. This cross-check helps a startup make sharing commitments it can fulfill while supporting commercialization and participant protections. For help assessing NIH program fit and preparing a coordinated SBIR or STTR application, book a free eligibility call with GrantUp.
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