Creating a Data Infrastructure for R&D Workforce Analysis

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Baker, David
Ginther, Donna
Haak, Laurel L
Hammond, Joel
Kannankutty, Nirmala
Probus, Matt
Saul, Joseph
Weinberg, Bruce
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To understand how research and development leads to creation of knowledge and then to track the impact of that knowledge requires a comprehensive model of the research ecosystem that incorporates inputs, outputs, activities, and external factors, and the data to support longitudinal and network analysis. To date, most research has focused on those activities and outputs that are readily accessible, including publication output and follow-on citations, as well as patents and patent citations. While these outputs are robust and can be normalized by field of research, additional data are needed to capture important aspects of research not published in journals or patents. Moreover, efforts to assemble systematic information on researchers, including their biographic information, institutions, support, and networks, are in a fledgling stage. We propose a workshop to discuss considerations in creating a data infrastructure to support quantitative analysis of the research workforce, its outputs, and impacts. The workshop is organized around three overarching themes: data linkages, data standards, and data privacy. Each theme will be explored as a moderated conversation among panel participants with implementation expertise, providing perspectives from academic, industry, and non-profit organizations.
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