Handbook on governance and data science / 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).

Format:

Book

Contributor:

Giest, Sarah, editor.

Klievink, Bram, editor.

Ingrams, Alex, editor.

Young, Matthew, editor.

Edward Elgar Publishing, publisher.

Series:

Elgar handbooks in public administration and management

Language:

English

Subjects (All):

Corporate governance.

Data curation.

Database management.

Genre:

Electronic books.

Physical Description:

1 online resource (414 pages).

Place of Publication:

Northampton : Edward Elgar Publishing, 2025.

Summary:

"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"-- Provided by publisher.

Contents:

Contents: 1. Introduction to the handbook on governance and data science / Sarah Giest, Bram Klievink, Alex Ingrams and Matthew M. Young

Part I. Data applications for policy challenges

2. Does it hold up? Testing big data's promise of novel information on labour market policymaking / Simon Vydra

3. Data science meets political economy: Applications to legislative favouritism around the world / Cyril Benoît, Dominik Brenner and Mihály Fazekas

4. Data science from a national statistics institute perspective: Limits and challenges illustrated by historical events / Koen van 't Boveneind, Darius Keijdener, Pedro Lemlijn, Jolien Oomens and Eveline Vandewal

5. Soft or, big data: Use and limitations in policy-making / Michael Howlett, Leong Ching and Tay Swee Kiat

6. Data and digitalization in energy efficiency policy design: The case of singapore / Ishani Mukherjee and Diandrea Ho

7. Examining the cost of living crisis: Insights from e-petitions and constituency groupings / Stephen D. Clark and Nik Lomax

8. Platform-based coordination for cross-agency collaboration in public service production / Yiwei Gong and Marijn Janssen

9. Implementing social media monitoring in the public sector: A four-model approach / Julián Villodre

10. Towards a framework for data science governance in the post-pandemic context: An analysis of three initiatives / Rodrigo Sandoval-Almazan and David Valle-Cruz

Part II. AI governance and innovation

11. Key challenges for the participatory governance of AI in public administration / Janis Wong, Deborah Morgan, Vincent J. Straub, Youmna Hashem and Jonathan Bright

12. Artificial intelligence and governance challenges in Latin America - the game between decolonization and dependence / Fernando Filgueiras

13. Proactive algorithmic transparency in government: The case of the colombian repositories of public algorithms / Juan David Gutiérrez and Sarah Muñoz-Cadena

14. Decoding the privacy puzzle: A study on AI deployment in public governance / Jose Ramon Saura, Belem Barbosa and Sudhir Rana

Part III. Responsible and participatory data use by government

15. Intersecting digital governance and data science: Preparing for communication to strengthen citizen-government partnerships / Jae-Seong Lee

16. Delivering on transparency's good governance promise? The state of government data against political corruption / Kristen Rose and Joseph Foti

17. System update: Emerging transparency and oversight functions for responsible data use / Joseph Foti, Tara Davis and Divij Joshi

18. Classificatory versus transformative data regimes: Towards a positive right to data production and analysis / Willie Gin

19. The janus face of personal data agency in public and private use applications / Dale Mineshima-Lowe, Roxana Bratu and Sarah Giest

20. A social capital perspective to building sustainable data centers for science / Federica Fusi and Eric W. Welch

21. Public sector innovation labs as an approach to data-driven innovation / Francesco Leoni

22. Conclusion, research agenda, and policy recommendations for governance and data science / Bram Klievink and Sarah Giest

Index.

Notes:

Includes bibliographical references and index.

ISBN:

9781035301348 (e-book)

Access Restriction:

Restricted for use by site license.