The Role of Blended Data in a New National Data Infrastructure

The Role of Blended Data in a New National Data Infrastructure

Session Description:

Blended data–that is, data combined from multiple sources of previously collected data–can enable rich and timely analyses not possible with any one data set alone in ways that reduce burden and cost to the public. Indeed, much recent federal legislation, regulation, and guidance has sought to outline key roles and responsibilities in the stewardship of blended data. Yet, despite the opportunity and progress made, many challenges remain to achieve the promise of modern national data infrastructure that accounts for the unique challenges of blended data.

This panel discusses the work of three committees appointed by the National Academies of Sciences, Engineering, and Medicine to develop a vision for a new data infrastructure for national statistics and social and economic research. The committees of experts with diverse backgrounds, ranging from statistics to public policy, produced a series of three reports focused on separate aspects of the new data infrastructure. The panelists will present key takeaways from the work of the committees. They will discuss the opportunity for a new data infrastructure, present the vision, and describe expected outcomes and key attributes of a new data infrastructure. The panelists will also discuss the key role of surveys in the blending of data from multiple sources, provide examples from the areas of income, health, crime, and agriculture statistics, and reflect on the implications for data equity. In addition, the session will describe how technical and policy controls can be used to address the unique privacy challenges in blended data and provide a framework for making practical decisions when designing and evaluating approaches for sharing, using, and analyzing blended private and confidential data.

Speakers:

Moderator:

Melissa Chiu, National Academies of Science, Engineering, and Medicine

Discussant:  (to be determined)

Erica Groshen

Senior Economics Advisor, Institute for Compensation Studies, Cornell University

Dr. Groshen is Senior Economics Advisor at the Cornell University School of Industrial and Labor Relations and Research Fellow at the Upjohn Institute for Employment Research. From 2013 to 2017, she served as the 14th Commissioner of the US Bureau of Labor Statistics, the principal federal agency responsible for measuring labor market activity, working conditions, and inflation. Before that she was Vice President in the Research and Statistics Group of the Federal Reserve Bank of New York. Her research has centered on jobless recoveries, wage rigidity and dispersion, and the role of employers in the labor market. She is the lead author of “Preparing U.S. Workers and Employers for an Autonomous Vehicle Future,” with Susan Helper, John Paul MacDuffie and Charles Carson. She also co-authored How New is the “New Employment Contract”? from W.E. Upjohn Institute Press and co-edited Structural Changes in U.S. Labor Markets: Causes and Consequences, from M.E. Sharpe, Inc. Dr. Groshen received the 2017 Susan C. Eaton Outstanding Scholar-Practitioner Award from the Labor and Employment Relations Association. She holds a Ph.D. in economics from Harvard University and a B.S. in mathematics and economics from the University of Wisconsin-Madison.

Sharon L. Lohr

Emeritus Distinguished Professor, Arizona State University & Vice President and Senior Statistician, Westat (ret.)

Sharon Lohr is a professor emerita at Arizona State University, where she was Dean's Distinguished Professor of Statistics until 2012. From 2012 to 2017, as a vice president at Westat, she developed survey designs and statistical analysis methods for use in transportation, public health, crime measurement, and education. Her research interests include sample surveys, design of experiments, hierarchical models, and combining multiple sources of data. She is the author of numerous research articles as well as the books Sampling: Design and Analysis and Measuring Crime: Behind the Statistics. She is an elected fellow of the American Statistical Association, an elected member of the International Statistical Institute, and the inaugural recipient of the Gertrude M. Cox Statistics Award for contributions to the practice of statistics. Her invited presentations include the Morris Hansen, Deming, and Waksberg lectures. Lohr currently serves on the National Academies’ Committee on National Statistics, and chaired the Panel on the Implications of Using Multiple Data Sources for Major Survey Programs. She earned her B.S. degree in mathematics from Calvin College, and her Ph.D. in statistics from the University of Wisconsin-Madison.

Jerry Reiter

Department Chair and Professor of Statistical Science, Department of Statistical Science, Duke University

Dr. Reiter graduated from Duke University with a BS in mathematics in 1992. After working for two years as an actuary, he received his Ph.D. in statistics from Harvard University in 1999. He landed back at Duke in the Department of Statistical Science in Fall 2002. Between 2010 and 2015, he was the Mrs. Alexander Hehmeyer Professor of Statistical Science, having been appointed as a Bass Chair in recognition of "excellence in undergraduate teaching and research." His was the recipient of the Alumni Distinguished Undergraduate Teaching Award for 2007. This annual award is given by Duke undergraduates to a member of the Duke faculty. He was also honored as the recipient of the Outstanding Postdoc Mentor award for 2016 and the inaugural Distinguished Faculty Award for the Duke Master's in Interdisciplinary Data Science program in 2020. He participates in both applied and methodological research in statistical science. Reiter is most interested in applications involving social science and public policy, although he enjoys working with researchers in all disciplines. His methodological research focuses mainly on statistical methods for protecting data confidentiality, for handling missing data, for combining information from multiple data sources, and for modeling complex data including methods for causal inferences. In 2015, The Atlantic published a story about his research on methods for protecting data confidentiality. He was the Principal Investigator of the Triangle Census Research Network, a research center funded by the National Science Foundation to improve the practice of data dissemination among federal statistical agencies. Until July 2019, he was the Deputy Director of the Information Initiative at Duke, an institute dedicated to research and applications in the analysis of large-scale (and not large-scale) data. He was appointed the Chair of the Department of Statistical Science in 2019. He stepped down from that position for the 2022/2023 academic year to serve as the interim Dean of Natural Sciences and returned to complete his term in 2023.