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Using Human Resource Data to Track Innovation: Summary of a Workshop APPENDIXES

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Using Human Resource Data to Track Innovation: Summary of a Workshop Appendix A Workshop Program 8:30 Welcome and Introduction Mark Myers, Xerox Corporation and Board on Science, Technology and Economic Policy 8:45 Session I: Framing the Issues and Objectives Paula Stephan, Georgia State University Discussant: James Adams, University of Florida 9:30 Session II: Research on Biotechnology Walter Schaeffer, NIH, Chair Susanne Huttner, University of California Maryann Feldman, Johns Hopkins University Walter (Woody) Powell, Stanford University Eric Campbell, Harvard Medical School and Massachusetts General Hospital 11:00 Session III: Research on Collaborations and Partnerships Kathie Olsen, NASA, Chair Donald Siegel, Arizona State University West Al Link, University of North Carolina, Greensboro Diana Hicks, CHI Research

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Using Human Resource Data to Track Innovation: Summary of a Workshop   Sample questions for Sessions II and III: What innovation analysis using human resource data has been done and what issues has it illuminated? What have been the sources of data and difficulties encountered? What linkages among data sets have been possible and productive? What opportunities are there for other uses? What difficulties do you anticipate? 12:30 Lunch 1:15 Session IV: Opportunities and Obstacles to New Data Uses and Coordination Nancy Kirkendall, Energy Information Agency, Chair Brad Jensen, Center for Economic Studies, Bureau of the Census Mary Golladay, National Science Foundation Michael McElroy, Bureau of Labor Statistics Julia Lane, Bureau of the Census, American University, and the Urban Institute 2:30 Breakouts What’s Possible? Where Do We Go From Here? Sample questions for Breakout Groups: To assess differences in the role of human capital in innovation, should the analysis and techniques applied to biotechnology be applied to other industries or technologies? Which? What HR data have been collected but not exploited? What linkages can be made between HR and other data sets? How? Can this be done without disrupting time series or losing other valuable information? Should federal agencies or supported institutions track personnel (laboratory employees, PIs, trainees, graduate assistants, research fellows and associates, etc.)? What aspects of program evaluation would benefit from use of HR data? 4:30 Session V: Reporting and Summation