Data Sharing Throughout the Research Lifecycle

The NIH data management and sharing plan (DMSP) requires researchers to plan for managing and sharing study data throughout the study lifecycle and beyond. Special considerations may apply for managing and sharing sensitive data, like identifiable human subjects data. The HEAL Initiative also has specific data sharing expectations.

Lessons learned: Each study is unique. Example DMSPs, templates, and boilerplate language are useful references, but researchers must take their study’s specific requirements, constraints, and resources into account when writing their DMSP. Failure to do so can result in DMSPs that are poorly aligned with HEAL data sharing expectations, difficult to implement, or disproportionately permissive or restrictive for the data being shared.

What to do:

• Align the DMSP with HEAL data sharing expectations. The HEAL Data Checklist includes guidance for multiple topics referenced in NIH DMSPs. These include: selecting a data repository, adopting appropriate data standards (like HEAL Common Data Elements (CDEs)), assigning persistent identifiers to shared data assets, and more. Contact the HEAL Data Stewards or the NIH Program Officer with questions.
• Seek feedback on DMSP drafts from your Office of Research or Library Data Services. They may be able to identify potential conflicts with organizational data policies or opportunities to utilize organizational resources.

Additional resources:

• Aligning the Checklist for HEAL-compliant Data with NIH DMSP Elements
• HEAL Data Checklist
• HEAL DMSP & Budget Guidance
• Complying With the HEAL Data Sharing Policy

Making data accessible and reusable may incur costs. Factors directly influencing costs include: data repository choice, curation or de-identification support, data management technology solutions, and staff effort. Many other factors can indirectly influence costs, such as organizational data management and sharing resources or data management practice maturity.

Lessons learned: Failure to budget appropriately for data management and sharing can result in difficulty securing resources needed to fulfill data sharing commitments. This can increase risk, decrease compliance, and negatively impact the reusability of shared data. For example, if professional de-identification services are needed but not budgeted for, studies may respond by not sharing data at all (decreased compliance) or having untrained staff attempt de-identification (increased risk). Researchers less experienced with sharing data or those using an unfamiliar repository may underestimate the effort needed to prepare data for sharing, and thus fail to budget for adequate staff time or curation support services.

What to do:

• Review NIH guidance on allowable costs for data management and sharing and include those applicable in the budget.
• Ensure budgeted costs align with activities and resources described in the DMSP, and vice versa.

Additional resources:

• Budgeting Resources for Data Management, Sharing, and Curation (HEAL Stewards)
• Budgeting for Data Management & Sharing (NIH)

Organizations often have various technical and human resources supporting data management and sharing. These may be found in library data services (e.g. data curators), ethics boards (e.g. IRBs), privacy offices (e.g. honest brokers and privacy law experts), IT units (e.g. data management software, data security experts), data or analysis cores, and elsewhere across the organization.

Lessons learned: Organizational resources can impact both the DMSP and the budget. For example, some organizations offer free data curation resources. In those that don’t, studies requiring curation support should budget for curation fees and consider naming a data repository that offers curation services in their DMSP.

What to do:

• Consult Offices of Research, Library Data Services, or other centralized data sharing support units to identify organizational resources your study can utilize. Remember to consider resources offered at collaborating organizations; for example, some organizations have data repository memberships with benefits like waived deposition fees.