Toward a 21st Century National Data Infrastructure: Managing Privacy and Confidentiality Risks with Blended Data - National Academies of Sciences Engineering and Medicine; Division of Behavioral and Social Sciences and Education; Committee On National Statistics; Panel on Approaches to Sharing Blended Data in a 21st Century Data Infrastructure
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Protecting privacy and ensuring confidentiality in data is a critical component of modernizing our national data infrastructure. The use of blended data - combining previously collected data sources - presents new considerations for responsible data stewardship. Toward a 21st Century National Data Infrastructure: Managing Privacy and Confidentiality Risks with Blended Data provides a framework for managing disclosure risks that accounts for the unique attributes of blended data and poses a series of questions to guide considered decision-making. Technical approaches to manage disclosure risk…mehr

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Produktbeschreibung
Protecting privacy and ensuring confidentiality in data is a critical component of modernizing our national data infrastructure. The use of blended data - combining previously collected data sources - presents new considerations for responsible data stewardship. Toward a 21st Century National Data Infrastructure: Managing Privacy and Confidentiality Risks with Blended Data provides a framework for managing disclosure risks that accounts for the unique attributes of blended data and poses a series of questions to guide considered decision-making. Technical approaches to manage disclosure risk have advanced. Recent federal legislation, regulation and guidance has described broadly the roles and responsibilities for stewardship of blended data. The report, drawing from the panel review of both technical and policy approaches, addresses these emerging opportunities and the new challenges and responsibilities they present. The report underscores that trade-offs in disclosure risks, disclosure harms, and data usefulness are unavoidable and are central considerations when planning data-release strategies, particularly for blended data.
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