Making human derived data FAIR: feedback from NCI office of data sharing workshop

Area of Science:

• Biomedical research
• Data science
• Cancer research

Background:

• US federal policies, including NIH Data Management and Sharing (DMS) and Public Access Policies, mandate responsible sharing of publicly funded research outputs.
• Ensuring scientific data is FAIR (findable, accessible, interoperable, reusable) is crucial for maximizing its usability and impact.
• The National Cancer Institute (NCI) Office of Data Sharing (ODS) convened workshops to address clinical data sharing challenges.

Purpose of the Study:

• To identify high-value clinical data features for collection and sharing in cancer research.
• To explore data use challenges and propose solutions for effective scientific data sharing.
• To establish consensus on minimum patient-derived clinical information for comprehensive cancer research.

Main Methods:

• Conducted a series of workshops involving researchers and stakeholders.
• Summarized workshop discussions on data use challenges and potential solutions.
• Identified consensus on essential patient-derived clinical data for cancer research.

Main Results:

• Highlighted the need for structured outputs for various data types and methodologies to enable FAIR sharing.
• Outlined attendee consensus on minimum patient-derived clinical information required for diverse cancer research.
• Identified data use challenges and proposed potential solutions for effective data sharing.

Conclusions:

• Workshop outputs provide a foundation for best practice recommendations on collecting and sharing impactful clinical data.
• Proposed preliminary guidance for policymakers and researchers on consistent and effective management of human-derived clinical data.
• Emphasized the importance of FAIR data principles for enhancing the sharing process and outcomes for data end-users in cancer research.