Data Governance and Privacy
The Data Governance and Privacy body of work aims to safely expand access to confidential data that advance evidence-based policymaking. We strive to develop innovative approaches that enable researchers and public policymakers to use higher-quality data while simultaneously protecting privacy and promoting equity.

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    The Statistics of Income (SOI) Division of the Internal Revenue Service collects and curates an enormously valuable trove of tax data, which researchers can use to assess the effects of tax policies and pursue other research questions, such as studying income inequality.





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    Senior Fellow
    Statistical Methods Group Lead
    Lead Data Scientist for Statistical Computing
    Research Associate
    Data Scientist
    About

    Who We Are

    The Data Governance and Privacy team at the Urban Institute is dedicated to developing and promoting data collection and analysis methodologies that prioritize accessibility, privacy, accuracy, and usability. We have established collaborations with both local and federal government agencies, as well as other organizations, to implement innovative statistical data privacy methods and uphold data governance principles. Our goal is to empower researchers and policymakers to access and leverage data for the betterment of society while protecting individual privacy.

    Impact Statement

    All people are responsibly represented in data.

    Our Approach

    Our team is working at the intersection of data governance and public policy to improve data access for researchers and policymakers to better evidence-based decisionmaking. We advance our goal under these four areas: 

    • accessibility: collaborating with partner agencies to improve data access (e.g., creating the Secure Transfer, Restricted-Use Data Lake to allow researchers improved access to Department of Labor confidential data)
    • privacy: developing and implementing cutting edge and practical privacy-preserving technologies and methodologies that safely expand data access (e.g., Safe Data Technologies, working with the Statistics of Income Division at the Internal Revenue Service and National Science Foundation National Center for Science and Engineering Statistics) 
    • accuracy: applying statistical methods to increase data quality and equity awareness in data access methods (e.g., Do No Harm Guide)
    • usability: creating data privacy and analysis tools as well as improving data privacy and access communications and education (e.g., creating tools or hosting training sessions for local, state, and federal government agencies, such as Allegheny County, Nebraska, and the Bureau of Economic Analysis)
    Staff
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    • Research Associate
    • Senior Fellow
      Statistical Methods Group Lead
    • Institute Fellow
    • Principal Research Associate
    • Chief Information Officer
      Vice President for Technology and Data Science
    • Senior Fellow
    • Director, Data and Analysis
    • Director, Web Development
    • Data Scientist
    • Research Analyst
    • Research Associate
    • Web Programmer Django/Python
    • Lead UX Designer
    • Associate Director, Software Engineering
    • Principal Research Associate
      Senior Survey Methodologist
    • Lead Data Engineer
    • Lead Data Scientist for Statistical Computing
    • Senior Fellow
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