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Suggested Citation:"Appendix D: Biographical Sketches of Panel Members." National Academies of Sciences, Engineering, and Medicine. 2022. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies. Washington, DC: The National Academies Press. doi: 10.17226/26360.
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Appendix D

Biographical Sketches of Panel Members

DANIEL KASPRZYK (Chair) is a consultant and senior fellow at NORC at the University of Chicago. Prior to his appointment at NORC, he was vice president and managing director of surveys and statistics at Mathematica Policy Research, Inc. Kasprzyk has more than 30 years of experience in managing large-scale sample surveys in a variety of topic areas, including holding various positions on the staff of the Survey of Income and Program Participation at the U.S. Census Bureau and carrying out methodological research associated with federal survey programs. He has particular expertise in nonsampling error issues in surveys. Prior to his private-sector positions, he was program director of the Elementary and Secondary Sample Survey Studies Program at the National Center for Education Statistics, where he was responsible for the Schools and Staffing Survey System. He was a member of the Organisation for Economic Co-operation and Development (OECD) committee that developed and reported school and teacher data for national comparisons. He served as the U.S. Department of Education’s liaison to the National Academy of Sciences’ Panel on Estimates of Poverty for Small Geographic Areas. He was a member of the National Academy of Sciences’ Panel to Review the 2014 Redesign of the Survey of Income and Program Participation, a member of the National Academy of Sciences’ Panel to Review the National Children’s Study Research Plan, and a member of the Institute of Medicine’s Panel on Lesbian, Gay, Bisexual, and Transgender Health Issues and Research Gaps and Opportunities. He also served for 20 years on the Office of Management and Budget’s Federal Committee on Statistical Methodology and chaired committees on federal longitudinal surveys and data quality reporting and measurement at the Center for Excellence

Suggested Citation:"Appendix D: Biographical Sketches of Panel Members." National Academies of Sciences, Engineering, and Medicine. 2022. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies. Washington, DC: The National Academies Press. doi: 10.17226/26360.
×

in Survey Research at NORC at the University of Chicago. He is an elected member of the International Statistical Institute and fellow and former vice president of the American Statistical Association (ASA). He chaired the ASA Sections on Survey Research Methods and on Social Statistics, as well as serving as officer for other sections of the ASA and for the Washington Statistical Society, a chapter of the ASA. Kaspryzk has a B.S. in mathematics from Wayne State University and a Ph.D. in mathematical statistics from George Washington University.

PHILIP ASHLOCK leads the data and analytics portfolio at the GSA Technology Transformation Service and serves as the chief architect for Data.gov. At Data.gov, he oversees an open development process and a federated architecture supporting open data and application programming interfaces (APIs) across government. Recently, Ashlock launched the U.S. Data Federation, a new project exploring reusable tools and repeatable processes to support data standards and interoperability within government. Previously, he served as a presidential innovation fellow working with the GSA and the White House Office of Digital Strategy. In addition to overseeing metadata management and standards across both federal agencies and local government in the United States, he has actively participated in international efforts around data standards and open data. This includes work on the Open311 API standard for municipal service requests, the international standards for data catalog metadata like DCAT, support on the U.S. National Reporting Platform for the Sustainable Development Goals, and participation in the UN SDMX-SDGs Working Group. Ashlock has a B.A. in design with a concentration in new media and a computer science minor from Western Washington University.

DAVID BARRACLOUGH is a 29-year veteran of the information technology (IT) industry, the past 15 years working in official statistics on IT systems, architecture, and methodology. He is currently a smart data practices manager in the OECD Statistics and Data Directorate, where he leads a team and community that is remodeling all of the OECD’s disseminated data using the SDMX standard, and designing the accompanying methodology. He is chair of the SDMX statistical working group (held for 5 years), which maintains the Content-Oriented Guidelines, including how to implement SDMX, cross-domain concepts code lists, how to model statistical datasets, and many other instruments and guidelines. He also manages the SDMX for Labor Statistics Global Data Structure Definition project—the first Global DSD for social statistics, and is involved in other domains such as the Sustainable Development Goals, Education, and National Accounts. He is also involved with statistical modernization standards such as GSBPM, GSIM, and CSPA. Barraclough attended Barnsley College in the UK.

Suggested Citation:"Appendix D: Biographical Sketches of Panel Members." National Academies of Sciences, Engineering, and Medicine. 2022. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies. Washington, DC: The National Academies Press. doi: 10.17226/26360.
×

CHRISTOPHER CHAPMAN joined the National Center for Education Statistics (NCES), within the U.S. Department of Education’s Institute of Education Sciences, in 1997. Since joining NCES, he has held a number of positions, starting as project officer for household surveys conducted by NCES. During his career at NCES, he has led or contributed significant methodological guidance to dozens of large-scale sample surveys such as the early childhood longitudinal studies, surveys of school safety, recurring teacher surveys, and the American Community Survey. He is currently associate commissioner of NCES for their Sample Surveys Division. In addition to his work with NCES, Chapman is a member of the interagency Federal Committee on Statistical Methodology, where he is currently coauthoring a report on how agencies can best communicate complexities of mixed-source data products to the wide range of stakeholders who use and rely on federal data. Prior to joining the Department of Education, he worked at the American Institutes for Research (AIR) where he was the project lead on work with NCES to strengthen and improve its household surveys. Before AIR, he worked at the Ohio State University’s Center for Survey Research (then the Polymetrics Laboratory), where he collaborated with academic researchers, state and local government officials, and private firms to develop and field a large number of data collections. Chapman has a B.A. and an M.A. in political science from the Ohio State University.

DANIEL W. GILLMAN is a mathematical statistician at the U.S. Bureau of Labor Statistics (BLS) in the Office of Survey Methods Research. His research interests include metadata, standards, terminology, and classification. At BLS, he led the effort to build a taxonomy of terms describing all time-series data and was a member of the team to build a glossary of BLS technical terms. He is consultant to the Consumer Expenditure Surveys effort to build a metadata repository in support of the annual public-use microdata release, to the BLS output database redesign effort, and to data-governance modernization efforts at the U.S. Department of Labor. He is chair of the interagency SCOPE/Metadata interest group to develop guidance on metadata management for the statistical agencies. Previously, Gillman chaired the Federal Data Architecture Subcommittee/Open Government Vocabulary Working Group, the Statistical Data and Metadata Exchange/Statistical Working Group, and the International Committee for Information Technology Standards/Metadata Standards Technical Committee (L8). He is a member representative to the Data Documentation Initiative (DDI) Alliance and is a key developer of the DDI-4 (Cross-Domain Integration) model-driven standard. Under the United Nations Economic Commission for Europe (UNECE), he was a member and chair for the former Statistical Metadata Working Group, a key developer of several UNECE statistical metadata standards, and a member of the Supporting Standards Group.

Suggested Citation:"Appendix D: Biographical Sketches of Panel Members." National Academies of Sciences, Engineering, and Medicine. 2022. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies. Washington, DC: The National Academies Press. doi: 10.17226/26360.
×

Prior to working at BLS, he worked at the U.S. Census Bureau. Gillman has a B.S. and an M.A. in mathematics from the University of Maryland.

LINDA A. JACOBSEN is vice president of U.S. Programs at the Population Reference Bureau (PRB). She is a demographer with more than 30 years of experience analyzing population trends and their implications for professional, policy, and media audiences. Her research has focused on family and household change, child and family well-being, and population estimates and projections. In partnership with the U.S. Census Bureau, Jacobsen leads several projects to increase knowledge and use of the American Community Survey (ACS) and to collect data-user feedback on ACS and decennial census products. She also directs PRB’s Center for Public Information on Population Research, funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development. Jacobsen has been a featured speaker on U.S. demographic trends at Harvard University’s Program for Newly Elected Members of Congress, the Knight Center for Specialized Journalism, and many other professional meetings and conferences. She has served on the Census Bureau’s Scientific Advisory Committee, a National Academy of Sciences’ Panel on the ACS, and as chair of the Population Association of America (PAA) Committee on Government and Public Affairs. She currently chairs the board of directors of the Council of Professional Associations on Federal Statistics and serves on PAA’s Committee on Population Statistics. She was elected a fellow of the American Statistical Association in 2015. Before joining PRB in 2005, she served as a senior executive and chief demographer for two leading marketing information companies; the research director at American Demographics; and a faculty member at both Cornell University and the University of Iowa, where she conducted research and taught graduate studies in sociology and demography. Jacobsen holds an M.S. and a Ph.D. in sociology from the University of Wisconsin–Madison and a bachelor’s degree in sociology from Reed College.

H.V. JAGADISH is Bernard A. Galler collegiate professor of electrical engineering and computer science in the Department of Computational Medicine and Bioinformatics at the University of Michigan and director of the Michigan Institute for Data Science. His research focuses on how to build database systems and query models so that they are truly usable, and how to design analytics processes so that they can deliver real insights to nontechnical decision makers. His current research is centered on usability of Big Data, particularly when the data involved come from multiple heterogeneous sources, and have undergone many manipulations. He is an elected fellow of the Association for Computing Machinery and serves on the board of the Computing Research Association. Jagadish has a Ph.D. in electrical engineering from Stanford University.

Suggested Citation:"Appendix D: Biographical Sketches of Panel Members." National Academies of Sciences, Engineering, and Medicine. 2022. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies. Washington, DC: The National Academies Press. doi: 10.17226/26360.
×

FRAUKE KREUTER is director of the Joint Program in Survey Methodology (JPSM) at the University of Maryland, College Park; professor of statistics and methodology at the University of Mannheim; and head of the Statistical Methods Research Department at the Institute for Employment Research in Nürnberg, Germany. Before joining the University of Maryland, she was a postdoc at the University of California, Los Angeles, Statistics Department. Her research focuses on sampling and measurement errors in complex surveys. In her work at JPSM, she maintains strong ties to the federal statistical system, and serves in advisor roles for the National Center for Education Statistics and the U.S. Bureau of Labor Statistics. She has served as a member on the Panel on Improving Federal Statistics for Policy and Social Science Research Using Multiple Data Sources and State-of-the-Art Estimation Methods at the National Academies of Sciences, Engineering, and Medicine. She is the author or coauthor of several books, including Data Analysis Using Stata and Practical Tools for Designing and Weighting Survey Samples. Kreuter has an M.A. in sociology from the University of Mannheim, Germany, and a Ph.D. in survey methodology from the University of Konstanz.

MARGARET LEVENSTEIN is director of the Inter-university Consortium for Political and Social Research at the University of Michigan, research professor for both the Survey Research Center and the School of Information, and adjunct professor of business economics and public policy at the Ross School of Business at the University of Michigan. Levenstein first joined the Institute for Social Research’s (ISR’s) Survey Research Center in 2003 as executive director of the Michigan Census Research Data Center, a joint project with the U.S. Census Bureau. She has taken an active role at ISR, joining the director’s advisory committee on diversity in 2009, and serving as chair of ISR’s Diversity, Equity, and Inclusion Strategic Planning Committee, and as the liaison to the larger university program. Her research and teaching interests include industrial organization, competition policy, business history, data confidentiality protection, and the improvement of economic statistics. She is associate chair of the American Economic Association’s Committee on the Status of Women in the Economics Profession and past president of the Business History Conference. Levenstein has a B.A. from Barnard College, Columbia University, and a Ph.D. in economics from Yale University.

PETER V. MILLER is a retired senior researcher for survey measurement at the U.S. Census Bureau. He joined the staff of the Census Bureau as chief of the Center for Survey Measurement in 2011. He was named chief scientist of the Bureau’s Center for Adaptive Design in 2013. Prior to joining the Census Bureau, he served on the faculty of Northwestern University

Suggested Citation:"Appendix D: Biographical Sketches of Panel Members." National Academies of Sciences, Engineering, and Medicine. 2022. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies. Washington, DC: The National Academies Press. doi: 10.17226/26360.
×

for 29 years. He also held faculty positions at the University of Michigan, the University of Illinois, and Purdue University. While in federal service, he served as a member of the Federal Committee on Statistical Methodology (FCSM). He co-chaired the FCSM nonresponse bias working group and the adaptive design interest group. He also co-chaired a task force on improving the climate for surveys, sponsored by the American Association for Public Opinion Research (AAPOR) and the American Statistical Association (ASA). Miller has held several elective offices in AAPOR, serving as president from 2009 to 2010. During his tenure as president, he launched the association’s Transparency Initiative. His research interests are centered in survey data collection methodology and transparency policies and procedures. He was named a fellow of the ASA in 2015. Miller has an A.B. and a Ph.D. both from the University of Michigan.

AUDRIS MOCKUS is Ericsson-Harlan D. Mills chaired professor of digital archeology in the Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. He also works part time at Avaya Labs Research. Mockus studies software developers’ culture and behavior through the recovery, documentation, and analysis of digital remains. These digital traces reflect projections of collective and individual activity. He reconstructs the reality from these projections by designing data mining methods to summarize and augment these digital traces, interactive visualization techniques to inspect, present, and control the behavior of teams and individuals, and statistical models and optimization techniques to understand the nature of individual and collective behavior. He is a member of the Institute of Electrical and Electronics Engineers and the Association for Computing Machinery. He served on the National Academies of Sciences, Engineering, and Medicine’s Steering Committee for Transparency and Reproducibility in Federal Statistics: A Workshop. Mockus has a B.S. and an M.S. in applied mathematics from the Moscow Institute of Physics and Technology, and a Ph.D. in statistics from Carnegie Mellon University.

SARAH M. NUSSER is professor of statistics at Iowa State University and affiliated with its Center for Survey Statistics and Methodology (CSSM), which she directed for 15 years. She is visiting professor at University of Virginia’s Social and Decision Analytics Division of the Biocomplexity Institute and senior fellow with the Association of American Universities (AAU). She previously served as Iowa State University vice president for research for 6 years. Nusser’s current research focuses on improving the reusability and impact of publicly accessible research data. Her prior research focused on survey statistics and methodology for land-based and population-based surveys, including sampling and estimation for longitudinal

Suggested Citation:"Appendix D: Biographical Sketches of Panel Members." National Academies of Sciences, Engineering, and Medicine. 2022. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies. Washington, DC: The National Academies Press. doi: 10.17226/26360.
×

natural resource surveys, measurement error models for dietary intake and physical activity data, and geospatial methods for sample frame listing and natural resource surveys. She directed statistics and methodology research and development for the annual U.S. Department of Agriculture’s National Resources Inventory Program for 22 years through her affiliation with CSSM. Nusser is actively involved in efforts to promote open science, transparency, and public access to research data. She serves as chair of the National Academies of Sciences, Engineering, and Medicine’s Board on Research Data and Information and is a former member of the Committee on National Statistics. She is a member of the National Institutes of Health’s Director Advisory Committee Working Group on Enhancing Rigor, Transparency and Translatability in Animal Research. She has played leadership roles in the AAU’s Association of Public and Land-grant Universities initiative on Accelerating Public Access to Research Data since its inception in 2017. Nusser is fellow of the American Statistical Association and elected member of the International Statistical Institute and has served on numerous scientific panels, advisory committees and governing boards. Nusser has a B.S. in botany from the University of Wisconsin, an M.S. in botany from North Carolina State University, and a Ph.D. in statistics from Iowa State University.

ERIC RANCOURT is director general of the Modern Statistical Methods and Data Science Branch at Statistics Canada, where he has been for 30 years. He has occupied several roles, such as director general of strategic data management, director of international cooperation, director of corporate planning, head of research, production manager of Survey Methodology Journal, and researcher. His main areas of work have been on treatment of nonresponse, estimation, gathering, safeguarding, and use of administrative and alternate data in statistical programs. He has been involved in many professional associations and is an International Statistical Institute elected member. He has a B.A. in statistics from the Université Laval.

LARS VILHUBER is on the faculty of the Department of Economics at Cornell University, a senior research associate at the Industrial and Labor Relations (ILR) School at Cornell University, and executive director of ILR’s Labor Dynamics Institute. He is also senior research associate (IPA) at the Center for Economic Studies and LEHD Program at the U.S. Census Bureau. Vilhuber has worked in both research and government and he has consulted with government and statistical agencies in Canada and the United States. Currently, he conducts research on using and making available highly detailed longitudinally linked data to analyze the effects and causes of mass layoffs, worker mobility, and the dynamics of (local) labor

Suggested Citation:"Appendix D: Biographical Sketches of Panel Members." National Academies of Sciences, Engineering, and Medicine. 2022. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies. Washington, DC: The National Academies Press. doi: 10.17226/26360.
×

markets. These data are generally subject to severe access restrictions. In order to make such data available to other researchers, he also conducts research on statistical disclosure limitation issues, including the creation and dissemination of synthetic data, and investigates novel methods and tools to disseminate metadata on such data. He is currently principal investigator on numerous grants, including those that fund activities at the National Science Foundation-Census Research Network (NCRN) node at Cornell University. He is the lead principal investigator on the NCRN Coordinating Office. Vilhuber has an undergraduate degree in economics from Universität Bonn, Germany, and a Ph.D. in economics from Université de Montréal, Canada.

Suggested Citation:"Appendix D: Biographical Sketches of Panel Members." National Academies of Sciences, Engineering, and Medicine. 2022. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies. Washington, DC: The National Academies Press. doi: 10.17226/26360.
×
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Suggested Citation:"Appendix D: Biographical Sketches of Panel Members." National Academies of Sciences, Engineering, and Medicine. 2022. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies. Washington, DC: The National Academies Press. doi: 10.17226/26360.
×
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Suggested Citation:"Appendix D: Biographical Sketches of Panel Members." National Academies of Sciences, Engineering, and Medicine. 2022. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies. Washington, DC: The National Academies Press. doi: 10.17226/26360.
×
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Suggested Citation:"Appendix D: Biographical Sketches of Panel Members." National Academies of Sciences, Engineering, and Medicine. 2022. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies. Washington, DC: The National Academies Press. doi: 10.17226/26360.
×
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Suggested Citation:"Appendix D: Biographical Sketches of Panel Members." National Academies of Sciences, Engineering, and Medicine. 2022. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies. Washington, DC: The National Academies Press. doi: 10.17226/26360.
×
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Suggested Citation:"Appendix D: Biographical Sketches of Panel Members." National Academies of Sciences, Engineering, and Medicine. 2022. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies. Washington, DC: The National Academies Press. doi: 10.17226/26360.
×
Page 238
Suggested Citation:"Appendix D: Biographical Sketches of Panel Members." National Academies of Sciences, Engineering, and Medicine. 2022. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies. Washington, DC: The National Academies Press. doi: 10.17226/26360.
×
Page 239
Suggested Citation:"Appendix D: Biographical Sketches of Panel Members." National Academies of Sciences, Engineering, and Medicine. 2022. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies. Washington, DC: The National Academies Press. doi: 10.17226/26360.
×
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Widely available, trustworthy government statistics are essential for policy makers and program administrators at all levels of government, for private sector decision makers, for researchers, and for the media and the public. In the United States, principal statistical agencies as well as units and programs in many other agencies produce various key statistics in areas ranging from the science and engineering enterprise to education and economic welfare. Official statistics are often the result of complex data collection, processing, and estimation methods. These methods can be challenging for agencies to document and for users to understand.

At the request of the National Center for Science and Engineering Statistics (NCSES), this report studies issues of documentation and archiving of NCSES statistical data products in order to enable NCSES to enhance the transparency and reproducibility of the agency's statistics and facilitate improvement of the statistical program workflow processes of the agency and its contractors. Transparency in Statistical Information for the National Center for Science and Engineering Statistics and All Federal Statistical Agencies also explores how NCSES could work with other federal statistical agencies to facilitate the adoption of currently available documentation and archiving standards and tools.

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