Advancing Science Policy: Innovations, Partnerships, and Tools

1. Science of Science and Innovation Policy(SciSIP) Presentation to: SBE Advisory Committee By: Dr. Kaye Husbands Fealing National Science Foundation November 8, 2007

2. Dr. Marburger’s Priority Areas • Comprehensive datacollection, data taxonomy and stewardship • New metrics,models,tools, and frameworks • International partnerships that promote science and technology advancements

3. SciSIP GoalsDevelopment of an evidence-based platformfor science policy • Understanding: develop usable knowledge and theories • Measurement: improve and expand science metrics, datasets and analytical models and tools • Community development: cultivate a community of practice focusing on SciSIP across the academy, the public sector and industry

4. Community of Practice Interdisciplinary International Innovative Inclusive

5. Grand Challenges (1) • Full systems approach to mapping science, technology and innovation • Portfolio models of investment in science and technology • Behavioral and dynamic models of the relationship between scientific discovery and policy decisions • Mapping and cyber tools linking the evolving taxonomy of S&E to policy decision-making • Full accounting of intangible assets and international workforce flows, and their contributions to science and technology outcomes

6. Grand Challenges (2) • Real-time evaluative and decision-making tools for assessing public sector investments in fundamental science and technology on economic growth and social well-being • Measures of spillover effects between scientific discovery and technological innovation, particularly among universities, firms and government labs • Evaluative measures of disciplinary cultures on transformative work • Computational models of creativity • Evaluative approaches to measuring diversity and its impact on science and technology developments

7. SciSIP-Funded Investigator Initiated Research (1) • Human capital development and the collaborative enterprise related to STI outcomes: • Trandisciplinary research teams (NIH-CERN; biomedical; nano) • Collaboration between academic and non-academic scientists (hydrology, soil and water science) • Virtual social networks (Internet) • Domain and culturally based evaluation tools (U.S., Mexico, Brazil) • Returns to international knowledge flows: • Benefits from international collaboration (bio-fuels) • Contributions of foreign graduate students and postdocs to knowledge creation and diffusion • Creativity and innovation: • Cognitive models of scientific discovery and innovation • Tools for innovative design based on core cognitive processes

8. SciSIP-FundedInvestigator Initiated Research (2) • Knowledge production system: • Gap analysis of the Idea Innovation Network (normal v. high risk; small v. large science) • Complexity systems modeling of technological evolution (low-carbon energy technologies) • Mapping tool of science for correlating funding with research outputs • International database of inter-organizational collaborative agreements (OECD) • Science policy implications: • Theoretical framework for assessing science and technology policies and social welfare outcomes (OECD) • Evaluative tools for assessing the distributional consequences of policy initiatives (intellectual property rights; life sciences) • State science and innovation policy initiatives evaluation tools • Public-values-based model of science and innovation policies

9. Broader Impacts • Simulation models of the knowledge creation and transfer system • Organizational designs and social networks that incubate, enrich and accelerate innovation • Tools for policymakers to optimize funding potential • Database of international research and technology partnerships, with indicators • Video database on tools and artifacts in innovative design • Performance evaluations tools enabled by cyberinfrastructure • Frontier methods of program evaluation • Theoretical foundations of the knowledge creation and innovation system and linkages to economic growth and social well-being

10. Lessons Learned from Solicitation I • Proposals from a variety of fields and varied methodologies performed well in the competition. • Multidisciplinary studies performed well if all of the necessary areas of expertise were well represented by engaged researchers. • Requests for small grants to do pilot studies were underutilized. • Research studies outperformed infrastructural development. • Research agenda should focus on Grand Challenges—development, organization and mobilization of productive resources in the creation and diffusion of new knowledge. • Data development and community building are two important emphasis areas to be added next competition.

11. SciSIP Milestones • Near term: • SciSIP Solicitation II • Add new methods, models and tools specifically informing the data-collection process • Add data development including new surveys, datasets, indicators, and benchmarks • Stakeholder forum—academics, policymakers, industry tech managers • Collaboratories—virtual organizations • Medium term: • New S&E indicators • Domain-specific models • Summer institute • Longer term: • An evidence-based understanding of the impacts of the S&E enterprise • A capacity to better nourish and harness the capabilities of the national STEM workforce • The development of a Community of Practice

12. Thank you! Comments and questions invited. For more information please contact: Dr. Kaye Husbands Fealing khusband@nsf.gov