Science of Science and Innovation Policy

archived

The Directorate for Social, Behavioral and Economic Sciences (SBE) at the National Science Foundation (NSF) aims to foster the development of the knowledge, theories, data, tools, and human capital needed to cultivate a new Science of Science and Innovation Policy (SciSIP). The SciSIP program underwrites fundamental research that creates new explanatory models, analytic tools and datasets designed to inform the nation’s public and private sectors about the processes through which investments in science and engineering (S&E) research are transformed into social and economic outcomes. SciSIP’s goals are to understand the contexts, structures and processes of S&E research, to evaluate reliably the tangible and intangible returns from investments in research and development (R&D), and to predict the likely returns from future R&D investments within tolerable margins of error and with attention to the full spectrum of potential consequences. Specifically, the research, data collection and community development components of SciSIP’s activities will: (1) develop usable knowledge and theories of creative processes and their transformation into social and economic outcomes; (2) develop, improve and expand models and analytical tools that can be applied in the science policy decision making process; (3) improve and expand science metrics, datasets and analytical tools; and (4) develop a community of experts across academic institutions and disciplines focused on SciSIP. For purposes of this solicitation, the term “science metrics” refers to quantitative measures or indicators that provide summary information on the size, scope, quality, and impact of science and engineering activities, with particular focus on inputs and outputs of the science, technology and innovation system. Characterizing the dynamics of discovery and innovation is important for developing valid metrics, for predicting future returns on investments, for constructing fruitful policies, and for developing new forms of workforce education and training.The FY 2009 competition includes three emphasis areas: Analytical Tools, Model Building, and Data Development and Augmentation. The emergent body of research will develop and utilize techniques for retrospective and prospective analyses. In addition, research will provide insight into factors that propagate new ideas at levels from the molecular functioning of the human brain to the organizational, state, national and international levels as well as advances the analysis and visualization of datasets describing complex social relationships and networks.In addition to these three emphasis areas, the FY 2009 competition particularly encourages the submission of proposals that demonstrate the viability of collecting and analyzing data on knowledge generation and innovation in organizations. In addition to providing innovative and scientifically based ways of describing and analyzing knowledge generation and innovation in organizations, these demonstration projects should address three specific aspects of the data collection approach: scalability and sustainability; protection of the confidentiality of respondents in computerized, widely accessible databases; and evaluation and assessment of the project's progress towards its scientific goals

High