Science of Science and Innovation Policy

The National Science Foundation developed the Science of Science and Innovation Policy program (SciSIP) in 2006 to fund basic and applied research that bears on and can help guide public- and private-sector policy making for science and innovation. By design, SciSIP has engaged researchers from many domains in the development of a community of practice who work together to continually develop frameworks, tools, and datasets for implementing science and innovation policy. Since its inception, the SciSIP program has funded more than 150 researchers and their graduate students. The program also contributed to the initiation of the STAR METRICS (Science and Technology for America''s Reinvestment: Measuring the Effect of Research on Innovation, Competitiveness and Science) program, a collaborative effort between the National Science Foundation and the National Institutes of Health. The STAR METRICS program develops tools and mechanisms for measuring federal expenditures on scientific activities, with particular focus on quantifying productivity and employment outcomes.

Science of Science and Innovation Policy summarizes a public conference convened by the Committee on National Statistics of the National Academy of Sciences/National Research Council to present research funded by SciSIP and foster intellectual exchange among funded researchers, science, technology, and innovation policy practitioners, and other members of the science community. The conference highlighted advances in the emerging field of the science of science and innovation policy, in particular, models, frameworks, tools, and datasets comprising the evidentiary basis for science and innovation policy. This report focuses on return on investment models; organizational structures that foster accelerated scientific productivity; linkages between commercialized scientific knowledge and job creation; the roles of universities and government in technology transfer and innovation; technology diffusion and economic growth; non-economic impacts of science and innovation expenditures; regional and global networks of knowledge generation and innovation; mechanisms for encouraging creativity and measuring outputs and outcomes from transformative research; and development, manipulation and visualization of data representing scientific activities.