RAPID: Linking institutional logics and data sharing to research outputs before and after SARS-CoV-2 peak infection

The ability of scientists to access and share data relevant for COVID-19 research (e.g., genomics data, sequences and strains, surveillance data, protein structures) is critical for understanding the virus and ultimately developing therapeutics and vaccines. Access to and sharing of data will have a significant effect on the amount of knowledge produced and the speed of discovery, both of which impact public health in the US. Early reports attest to record-breaking scientific collaboration and data sharing, but in the long run data access and sharing will greatly depend on the confluence of scientists? values, beliefs and practices, as well as the governance and management of the repositories curating the data. This research investigates how scientists? data access and sharing preferences and behaviors change over the course of the COVID-19 pandemic, as research moves from early crisis response to concrete opportunities for visibility, reputation, and innovation. Early in the crisis, we expect that the research community will use repositories with governance models that maximize open sharing of data. But as knowledge builds, general understanding of the virus increases, and the number of cases plateaus, we expect to see a shift, with researchers becoming more selective in how, when, and where they share their data. This project investigates how and why these change occur in order to design data governance solutions that maximize the community response to public crises, minimize delays in global collaboration and data sharing, and ultimately lead to research production and innovation.

This research takes advantage of the unique opportunity window offered by the COVID-19 crisis to understand how and why institutional determinants of data access and sharing evolve over the course of a public health crisis and how data repositories can act as facilitators (or barriers) for rapid research response to societal challenges. We ask: How do researchers perceive and integrate different, often conflicting, rationales for data sharing when faced with public emergencies? How do researchers adjust their actions and decisions as the crisis evolves? How do data repositories react to global challenges by adjusting, integrating, or disrupting conflicting institutional logics regarding data sharing? Why do researchers converge around certain data repositories but not others? What governance models are more successful in integrating conflicting logics in a way that maximize researchers? response to public crises? To frame the inquiry, we integrate institutional work and open community theories to link 1) individual-level decisions and actions regarding data access, exchange, and use with 2) collective governance systems of data repositories. The study undertakes a mixed-method research design that uses interviews and survey data to understand the decisions, actions, and outputs of researchers before and after peak infection levels. Findings will contribute practical insights to funding agencies, data repository management teams, universities, and research communities by showing how researchers and data repositories respond to the need for rapid research and data sharing at a global level.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.