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Unlocking data to improve public policy

Published:24 September 2019Publication History
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Abstract

When properly secured, anonymized, and optimized for research, administrative data can be put to work to help government programs better serve those in need.

References

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  1. Unlocking data to improve public policy

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          Shrisha Rao

          Data-driven decision-making is all the rage these days. Government and public sector organizations, as well as industry and private enterprise, are keen to leverage the flood of data available in the Information Age to make better decisions. Data analytics and data visualization are critical topics in management, during design and setup, as well as in both normal and crisis functioning. All said and done, it is of course better that policies be made based on a sound understanding of all available data, rather than just based on politics or vested interests. It is in this context that the present article describes the authors' approach to using administrative data for policymaking in organizations. This is mainly based on their insights from RI 360, a large aggregated database specific to Rhode Island, developed by the authors and their collaborators. The article contains some interesting insights about the use of RI 360 for policymaking, and hopefully will spur further work in a similar direction. While the authors' work in this instance is doubtless of the highest order, it is not clear how well their ideas will translate to larger settings (for example, larger and more diverse US states such as California or Texas, rather than tiny Rhode Island). The downsides of large aggregated data, including privacy [1] and ethics [2] concerns, especially in the context of emerging legal frameworks such as the European General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA), need to be carefully understood and addressed as well.

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          • Published in

            cover image Communications of the ACM
            Communications of the ACM  Volume 62, Issue 10
            October 2019
            89 pages
            ISSN:0001-0782
            EISSN:1557-7317
            DOI:10.1145/3363418
            Issue’s Table of Contents

            Copyright © 2019 ACM

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            New York, NY, United States

            Publication History

            • Published: 24 September 2019

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