The Role of Blended Data in a New National Data Infrastructure
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.
Melissa Chiu (National Academies of Science, Engineering, and Medicine)
Robert Groves (Georgetown University), invited
Sharon Lohr (Arizona State University, emerita), invited
Jerome Reiter (Duke University), invited
(to be determined)
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