This project investigates instances of convergent or translational research within and across the natural, engineering and social sciences. Scientific research increasingly relies on collaboration across many different areas of expertise. When there is a need to do research that translates expertise, tools, and analytic techniques across research areas or projects, it must be convergent and presents challenges for scientists who are trying to collaborate in new ways. This project aims to investigate new dynamics of collaboration emerging around processes and goals for convergent research, which has become a central plank of recent NSF efforts. This research will inform science policy and regulatory environments to help develop sustainable and productive research organizations, platforms, infrastructure, and convergent tools.
The focus of this research is on exemplary experts who conduct translational research, their practices, organizational forms, technical tools and architectures. It will study experts in ocean science, radio astronomy, and data science among others. The goal is to understand and analyze practices of convergence, recurrent challenges, and technological architectures, in order to support and enhance activities that advance science. The methods used are comparative, archival and ethnographic. The ethnographic work is both multi-sited (operating across multiple research locales) and multi-scalar (exploring phenomena nested at multiple scales). Both elements are crucial to the comparative analysis of convergence activities. At a higher and more general level, the research explores network-based dynamics and convergence actors operating within and across the sites of investigation. At a lower and more specific level, it drills down to consider in greater detail the local convergence adopted in select network micro-sites. Findings will contribute to the sociotechnical design of tools and infrastructure, the human-computer interaction field of computer supported cooperative work and science and technology studies.
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.