FASEB Issues Statement on Data Management and Access

March 10, 2016

Quality data management and appropriate data access are essential to scientific progress and achieving the maximal benefits of research. With the expanding ways investigators collect, utilize, and share data, it has been difficult to identify strategies to enhance data practices that are practical and relevant for all life science fields.

FASEB issued a statement to help guide stakeholder efforts to advance data management and access in the biological and medical science. It sets forth a set of guiding principles that balance the costs and benefits of increased access, taking into consideration dataset utility, resource needs, and administrative burden.

Recognizing the diversity of data types and research areas, FASEB advocates flexible and customizable approaches that allow investigators and research sponsors to establish reasonable expectations for a particular research project. As research sponsors expand data access requirements, FASEB calls upon them to provide commensurate financial and staff support, including investments in the underlying infrastructure.

The statement also addresses the use and contents of data management plans, which are increasingly required by U.S. federal funding agencies. FASEB recognizes that these plans are important tools and advises that they remain short summary documents focused on the most essential aspects of data management. Sponsors are encouraged to delay compliance actions until major barriers are addressed and requirements are well-vetted and harmonized.

Each stakeholder group can uniquely contribute to improved data practices and thus to scientific progress. Therefore, FASEB also provides recommendations for improving data management and access that are specific to research sponsors, investigators, scientific journals, and research institutions. The varied roles of stakeholder groups detailed in the statement demonstrate the long-term need to develop integrated community-based solutions.

Categories: Science Policy & Advocacy; Data Science and Informatics;