Toward a 21st Century National Data Infrastructure: Mobilizing Information for the Common Good
Language: English
Published by National Academies Press, 2023
- Softcover
- Used

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- Title
- Toward a 21st Century National Data Infrastructure: Mobilizing Information for the Common Good
- Author
- National Academies of Sciences, Engineering, and Medicine,Division of Behavioral and Social Sciences and Education,Committee on National Statistics,Panel on the Scope, Components, and Key Characteristics of a 21st-Century Data Infrastructure
- Publisher
- National Academies Press
- Publication year
- 2023
- Condition
- Fine
- Binding
- paperback
- Language
- English
- ISBN 10
- 0309692741
- ISBN 13
- 9780309692748
Historically, the U.S. national data infrastructure has relied on the operations of the federal statistical system and the data assets that it holds. Throughout the 20th century, federal statistical agencies aggregated survey responses of households and businesses to produce information about the nation and diverse subpopulations. The statistics created from such surveys provide most of what people know about the well-being of society, including health, education, employment, safety, housing, and food security. The surveys also contribute to an infrastructure for empirical social- and economic-sciences research. Research using survey-response data, with strict privacy protections, led to important discoveries about the causes and consequences of important societal challenges and also informed policymakers. Like other infrastructure, people can easily take these essential statistics for granted. Only when they are threatened do people recognize the need to protect them.
Toward a 21st Century National Data Infrastructure: Mobilizing Information for the Common Good develops a vision for a new data infrastructure for national statistics and social and economic research in the 21st century. This report describes how the country can improve the statistical information so critical to shaping the nation's future, by mobilizing data assets and blending them with existing survey data.
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