The increasing availability of large-scale data to capture major activities in science---publications, patents, citations, grant proposals, as their associated meta-data---has created an unprecedented opportunity to quantitatively explore the patterns of scientific production and reward. This workshop brings together social, computational and natural scientists to discuss the science of science and innovation policy and its potential to transform the practice of science, the redesign of institutions, and the practice of science policy. Participants include leading researchers from various disciplines, program directors from the Department of Defense, and private philanthropic foundations, scientific publishers and companies that conduct R&D and provide scientific services.
Researchers from a wide range of disciplines have begun to use science as an observatory to probe social phenomena that are more universal and widely applicable than the institutions of science themselves. As such, the tools and perspectives vary, involving social scientists, information and computer scientists, economists, physicists and mathematicians, with results published in venues with non-overlapping readership. In contrast with standard bibliometric studies, the recent surge in quantitative studies of science is characterized by a few distinct qualities: (i) They typically rely on large-scale datasets to study science, ranging from hundreds of thousands to millions of authors, papers and citations; and, (ii) Instead of only evaluating metrics, they also use models to more deeply probe the mechanisms driving science, from knowledge production to scientific and social impact, systematically distinguishing predictable from random patterns
This event is free of registration fees thanks to the generous support from the NSF, AFOSR, Thomson Reuters.