Merging governance studies and data science, this Handbook provides a comprehensive overview of how these fields interact with each other, driving a greater understanding of and guidance for the data-driven transformation of government.

Bringing together contributions from leading scholars and practitioners, the Handbook shows how data science can improve decision-making, enhance services, and increase transparency and accountability in government. The authors cover a broad spectrum of techniques, such as predictive modelling and analyzing public sentiments in real time, which are useful tools for today's public administrators. They also address the ethical challenges, privacy issues, and need for transparency when automating decisions. The Handbook provides in-depth analysis and insights into both the benefits and complexities of employing data science in public settings, creating a dialogue on the responsible use of data science in governance.

The Handbook on Governance and Data Science is a vital resource for students and scholars of technology and data science, regulation and governance, public policy and political science, and public administration. It is also valuable for policymakers working in innovation policy and data science governance and management.

About the Author

Edited by Sarah Giest, Professor of Public Policy, Innovation, and Sustainability, Bram Klievink, Professor of Public Policy and Digitization, Alex Ingrams, Assistant Professor of Public Administration and Matthew M. Young, Assistant Professor of Public Administration, Institute of Public Administration, Leiden University, the Netherlands

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