Science and innovation policy makers have long had a keen interest in obtaining quantitative data and qualitative information they can use to support decisions they make, such as whether and how much to invest in graduate training programs or in research and development. (Box 1-1 lists some of the issues of concern to science policy makers.)
Selected Illustrative Issues for Science and Innovation Policy
Competitiveness What internal and external factors help predict competitiveness of a nation or region? What are the effects of gain or loss of productive capacity in an industry on basic scientific infrastructure? What may be the long-term effects in the United States of the disappearance of big private-sector research labs doing basic research?
Data Extraction and Manipulation What is the value of new data, metrics, and indicators that are becoming available to illuminate science and engineering policy questions?
Geospatial Clusters Where are regional and international hot spots for basic research and innovative activities? What metrics of science and engineering resources and networks reliably indicate regions and countries to watch for scientific and technological breakthroughs?
Innovation What is known about the dynamics of innovation? What speeds or slows the diffusion of new ideas and new applications across countries or across firms? Under what circumstances, if at all, can public policy or infrastructure affect the speed of diffusion?
Role of Government What are the effects of government efforts to promote innovation in the manufacturing sector and in the service sector? When can public policy or infrastructure affect the speed of diffusion of new scientific knowledge? Are there sectors where the long-term social and economic benefits are great enough to justify major government investment in “jump-starting” a given sector? What is the expected employment yield (jobs, wages, and occupational mobility) of public expenditures on science and technology?
Strategic Policy Design What can be learned from successful and unsuccessful efforts to coordinate federal science and technology policy? What can be learned from analogous private sector activities, such as the creation of cross-functional teams?
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1 Introduction and Background Science and innovation policy makers have long had a keen interest in obtaining quantitative data and qualitative information they can use to support decisions they make, such as whether and how much to invest in graduate training programs or in research and development. (Box 1-1 lists some of the issues of concern to science policy makers.) BOX 1-1 Selected Illustrative Issues for Science and Innovation Policy Competitiveness What internal and external factors help predict competitiveness of a nation or region? What are the effects of gain or loss of productive capacity in an industry on basic scientific infrastructure? What may be the long-term effects in the United States of the disappearance of big private-sector research labs doing basic research? Data Extraction and Manipulation What is the value of new data, metrics, and indicators that are becoming available to illuminate science and engineering policy questions? Geospatial Clusters Where are regional and international hot spots for basic research and innovative activities? What metrics of science and engineering resources and networks reliably indicate regions and countries to watch for scientific and technological breakthroughs? Innovation What is known about the dynamics of innovation? What speeds or slows the diffusion of new ideas and new applications across countries or across firms? Under what circumstances, if at all, can public policy or infrastructure affect the speed of diffusion? Role of Government What are the effects of government efforts to promote innovation in the manufacturing sector and in the service sector? When can public policy or infrastructure affect the speed of diffusion of new scientific knowledge? Are there sectors where the long-term social and economic benefits are great enough to justify major government investment in “jump-starting” a given sector? What is the expected employment yield (jobs, wages, and occupational mobility) of public expenditures on science and technology? Strategic Policy Design What can be learned from successful and unsuccessful efforts to coordinate federal science and technology policy? What can be learned from analogous private sector activities, such as the creation of cross-functional teams? 1
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2 INTRODUCTION AND BACKGROUND Technology Transfer Under what circumstances is academic research effectively translated into private-sector applications? Can universities do more to transfer technology to the marketplace? What institutional and legal changes are needed to bridge the “valley of death” between the university and private industry? What is the link between scientific discoveries at academic institutions and private sector job creation? Transformative Research What mechanisms can encourage researchers to identify high- impact multidisciplinary research opportunities that are being underfunded? SOURCE: Compiled by Kaye Husbands Fealing, workshop summary rapporteur and original NSF program director for SciSIP. At the same time, researchers in many disciplines—including chemistry, computer science, economics, engineering, physics, political science, psychology, sociology, and visual analytics—have worked to understand the factors underlying scientific discovery and technological innovation, but researchers and policy makers have not always communicated or collaborated effectively. In 2005, U.S. Science Advisor John Marburger, III, called for a multidisciplinary approach to both create an evidentiary platform for science policy and develop a formal field of study (Marburger, 2005). 1 Heeding this call, as well as heightened interest from both policy makers and researchers, the National Science Foundation developed the Science of Science and Innovation Policy program (SciSIP) in 2006. 2 This program funds 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 in this new field—that is, a cadre of experts 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. Having made five rounds of research awards, the SciSIP program directors recognized the need for a summative showcase of the productivity and contributions of 1 Dr. Marburger was U.S. science advisor and director of the White House Office of Science and Technology Policy (OSTP) in the second Bush administration, a position he held from 2001–2009. He delivered the address where he effectively called for the emergence of the science of science policy field at the American Association for the Advancement of Science Forum on science and technology policy in Washington, DC, on April 21, 2005. To read the content of the speech, see http://scienceofsciencepolicy.net/reference/marburger-speech-aaas-forum-science-and-technology-policy [January 2014]. Dr. Marburger passed away in July 2011. To read a brief biography, see http://www.stonybrook.edu/sb/marburger/obit.shtml [January 2014]. 2 For more information about SciSIP, see http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=501084 [January 2014].
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SCIENCE OF SCIENCE AND INNOVATION POLICY 3 SciSIP researchers, who have investigated many long-standing questions regarding investment in and organization of science, engineering, and innovation in the United States and in other nations. As part of that activity, the program directors asked the Committee on National Statistics (CNSTAT) of the National Academy of Sciences/National Research Council to convene a two-day public conference. CNSTAT formed the Steering Committee on the SciSIP Principal Investigators’ Conference. The committee was charged to plan a conference that would 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 was the largest gathering of SciSIP principal investigators since the program’s inception. (See Box 1-2 for the steering committee charge.) BOX 1-2 Statement of Task for the SciSIP Conference Steering Committee An ad hoc committee will plan and conduct a two-day public workshop to foster intellectual exchange among funded researchers of the National Science Foundation’s (NSF) Science of Science and Innovation Policy Program (SciSIP) and between these researchers and science, technology and innovation policy practitioners. In keeping with the goals of the SciSIP program, this workshop will facilitate scholarly exchanges between SciSIP award recipients. It is intended to be the largest gathering of SciSIP principal investigators since the inception of the program in 2006. The fifth year of the program is the opportune time to showcase its research productivity and contributions to many long-standing questions regarding investment in and organization of science, engineering and innovation activities in the U.S. and in other nations. The workshop will feature invited presentations and discussions. It may also include poster sessions. The committee will develop the agenda for the workshop, select and invite speakers and discussants, and moderate the discussions. Topics to be addressed at the event will highlight 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 will be the focus of the event. The workshop, therefore, will not only facilitate interdisciplinary discourse between researchers from a variety of academic disciplines and fields, it will also foster communication and learning between academicians and policymakers, thereby advancing the development of the SciSIP community of practice. Presentations by SciSIP researchers will focus on several themes, such as: 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. A designated rapporteur will prepare an independently-authored summary of the workshop.
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4 INTRODUCTION AND BACKGROUND ORGANIZATION OF THE CONFERENCE AND THIS SUMMARY The SciSIP Principal Investigators’ Conference included presentations and roundtable discussions, data use demonstrations, and poster sessions. 3 It highlighted models, frameworks, tools, and datasets that are in varying stages of development towards the goal of improving the evidentiary basis for science and innovation policy. Three plenary sessions brought together policy makers from different scientific domains and areas of influence, experts from the natural sciences that are often studied by SciSIP researchers, and SciSIP researchers who have produced results that have been useful in the policy domain. Nine concurrent sessions highlighted advances in various substantive and methodological domains of the emerging field of the science of science and innovation policy. Topics addressed included: implementing science policy; scientific discovery processes; human capital; organizations, institutions, and networks; innovation (two sessions); data extraction and measurement; mapping science; and assessment and program evaluation. The agenda was structured to allow ample opportunities for informal discussion and collaboration. This report has been prepared by the conference rapporteurs as a factual summary of what occurred at the conference. The steering committee’s role was limited to planning and convening the conference. The views contained in the report are those of individual conference participants and do not necessarily represent the views of all conference participants, the steering committee, or the National Research Council. The summary is organized as follows. Because a basic grasp of the history of the SciSIP program is helpful to understanding the role of the SciSIP Principal Investigators’ Conference and where the field stands at present, the remainder of this first chapter summarizes that history. Chapter 2 summarizes points made by invited policy makers about SciSIP and its context and goals. Chapters 3 through 5 summarize presentations of the SciSIP researchers who described their work. 4 Rather than be presented sequentially according to the workshop agenda, these summaries have been arranged according to three broad themes—incentives, governance, and innovation, work and collaboration, and 21st century data—but it is important to note that the projects discussed were completely independent of one another. The closing chapter summarizes the perspectives of speakers who were invited to reflect on the SciSIP-funded research and its significance. The conference agenda and participant list appear in Appendix A. Papers commissioned for the conference, presentations, and other materials are available on the CNSTAT website. 5 3 The steering committee endeavored to identify a representative group of PIs, reflecting a range of topics, who had findings to share, could be accommodated within the limited time of the conference, and who were available on the scheduled dates. The opportunity to make a poster presentation was offered to all PIs who were not giving formal presentations. 4 Poster session discussions are not summarized in this report. Lists of all SciSIP awards appear in Appendix B. Abstracts of these research projects are readily available on NSF’s website at http://nsf.gov/awardsearch/ [January 2014]. 5 See http://sites.nationalacademies.org/DBASSE/CNSTAT/CurrentProjects/DBASSE_072054 [January 2014]. The three commissioned papers are: Erin Leahey, “Shaping Scientific Work: The Organization of Knowledge Communities”; Dean Simonton, “Assessing Scientific Creativity: Conceptual Analyses of Assessment Complexities”; and Albert Teich, “Making Policy Research Relevant to Policy.”
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SCIENCE OF SCIENCE AND INNOVATION POLICY 5 HISTORY OF SciSIP The 2005 path-breaking speech by U.S. Science Advisor John Marburger, III, provided the impetus for bringing together what were previously scattered areas of research on the drivers of science and innovation in order to develop a full-fledged field of study with appropriate frameworks, tools, and datasets. 6 NSF responded immediately by taking steps to set up SciSIP. (See the timeline in Figure 1-1.) FIGURE 1-1 Timeline of the SciSIP program’s development, 2006-2012. At the outset, research communities within the purview of the NSF Directorate of Social, Behavioral, and Economic Sciences (SBE) were asked for input on the possible development of this new funding activity. This bottom-up approach is what NSF follows to ensure that the goals and objectives of new activities are commensurate with what researchers foresee as feasible and within their purview. The three divisions within SBE—Behavioral and Cognitive Sciences (BCS), Science Resources Statistics (SRS, now known as the National Center for Science and Engineering Statistics, NCSES), and Social and Economic Sciences (SES)—each convened a workshop during the spring- summer of 2006. 7 Although the three workshops addressed opportunities for different 6 Several conference participants reflected on the importance of Marburger’s speech in light of long- standing discussions on funding priorities among scientific disciplines and other difficult issues of science policy (see Chapter 2). 7 BCS and SES are research-sponsoring divisions, while SRS, now NCSES, is the data repository of national science and engineering statistics. At the time of SciSIP’s development, David Lightfoot was SBE
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6 INTRODUCTION AND BACKGROUND strains of research, their purposes were the same: to obtain input on how research communities would approach the task of developing scientific platforms for deliberative science and innovation policy decisions. The BCS workshop focused on the possible contributions to a science of science and innovation policy of an emerging field of research in which psychologists and engineers collaborate on models of the engineering design process (Schunn et al., 2006). This work can guide the development of creativity models and provide explanations of “the scientific bases of individual and team innovation and discovery” (the title of the workshop report). It also provides a basis for optimizing the organization of science labs and other collaborative basic research and innovation activities. This research community expected their contribution to the science of science and innovation policy to be: • studies that expand understanding of the cognitive mechanisms of innovation/creativity and the ways in which strategies and external tools influence these cognitive mechanisms; • computational modeling and agent simulations of innovation/creativity that allow for theoretical development for analysis at multiple levels (individuals, groups, and organizations); • empirical studies and computational models that explore the temporal dynamics of individual and group factors on innovation/creativity; • interdisciplinary programs of research that coordinate experiments in psychology laboratories and engineering design; and • empirical studies that examine the cognitive, social, and motivational factors of group cognition in more realistic group settings. SES convened a workshop to determine the potential contributions of its research community to a science of science and innovation policy (Cozzens, Regan, and Rubin, 2007). Attendees represented several disciplines, including economics, ethics, history of science, science and technology studies, and sociology. Collectively, they articulated the following areas that are ripe for research that could assist science and innovation decision making: • linkages of scientific advances and innovation to economic growth, productivity, and other measures of economic and social well-being; • institutional and organizational environments that foster or forestall innovation and creativity; • the political economy of science, technology, and innovation policy; • evidence and expertise in science-intensive decision making; and • the impact of science, technology, and innovation on global economic, social, and environmental change. assistant director and Mark Weiss, Edward Hackett, and Lynda Carlson directed the BCS, SES, and SRS divisions, respectively. SRS became the National Center for Science and Engineering Statistics in January 2011.
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SCIENCE OF SCIENCE AND INNOVATION POLICY 7 Marburger’s call for a science of science policy included a clear appeal for more comprehensive, directly applicable, and timely datasets in science, engineering, technology, and innovation inputs, outputs, outcomes, and practices at the sub-national, national, and international levels. The Science Resources Statistics Division hosted a workshop entitled “Advancing Measures of Innovation: Knowledge Flows, Business Metrics, and Measurement” (NSF, 2006). That workshop yielded several areas for which metrics are in need of further development or are not yet in existence, including: • innovation activities in and outside of research and development (R&D) labs; • key drivers, inputs, and institutional mechanisms for R&D, such as spending decisions, market demand, social needs, and knowledge management; • outputs, outcomes, adoption, and diffusion of innovations; • effects of government policies on innovation; • relationships, knowledge flows, and networks, particularly between universities and industry; • measurement of intangible assets and disembodied knowledge; • mobility of individual scientists and graduate students; and • means by which data can be made accessible in a timely fashion and in a secure environment that protects privacy and confidentiality to researchers and other data users. The information gathered through these three workshops was digested and ultimately incorporated in a prospectus for the SciSIP program issued by NSF at the launch of the program in the fall of 2006. SciSIP initially had three goals: (1) develop usable knowledge and theories of creative processes and their transformation into social and economic outcomes; (2) improve and expand science metrics, datasets, and analytical tools, yielding changes in the biannual science and engineering indicators and other data collections; and (3) develop a community of experts across the federal government, industry, and universities focused on SciSIP. 8 In February 2007, SciSIP issued its first solicitation for research proposals, and the first awards (19 in all) were made in August 2007. The projects can be categorized as follows: human capital development and the collaborative enterprise; returns to international knowledge flows; creativity and innovation; knowledge production systems; and implications of science policy. The program has grown in subsequent years. In 2008, eight of the 24 funded projects focused on innovation, specifically the role of firms in innovation and measuring and tracking innovation. The 2009 and 2010 solicitations included specific requests for proposals on data development, manipulation, and visualization. At the time of the conference, SciSIP had funded 91 projects based on its core solicitation and 12 RAPID awards in response to its 2009 “dear colleague” letter regarding measures of impacts related to the American Recovery and Reinvestment Act (ARRA or Stimulus Package). 9 SciSIP principal investigators have also published dozens of peer-reviewed articles and contributed several datasets to the general research 8 See the project prospectus, http://www.nsf.gov/sbe/scisip/scisip_prospectus.pdf [January 2014]. 9 Since the conference, SciSIP funded two more rounds of awards, bringing the total number of awards to 155, including RAPID awards.
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8 INTRODUCTION AND BACKGROUND community. The results of these projects were the focus of the conference, for which the proceedings are summarized in the remainder of this report.