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

• Contents1 Introduction to the Handbook on Governance and Data Science 1 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 14 Simon Vydra 3 Data science meets political economy: applications to legislative favouritism around the world 41 Cyril Benoît, Dominik Brenner and Mihály Fazekas 4 Data science from a national statistics institute perspective: limits and challenges illustrated by historical events 59 Koen van ’t Boveneind, Darius Keijdener, Pedro Lemlijn, Jolien Oomens and Eveline Vandewal 5 Soft OR, Big Data: use and limitations in policy-making 75 Michael Howlett, Leong Ching and Tay Swee Kiat 6 Data and digitalization in energy efficiency policy design: the case of Singapore 93 Ishani Mukherjee and Diandrea Ho 7 Examining the cost of living crisis: insights from e-petitions and constituency groupings 109 Stephen D. Clark and Nik Lomax 8 Platform-based coordination for cross-agency collaboration in public service production 124 Yiwei Gong and Marijn Janssen 9 Implementing social media monitoring in the public sector: a four-model approach 141 Julián Villodre 10 Towards a framework for data science governance in the post-pandemic context: an analysis of three initiatives 158 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 179Janis Wong, Deborah Morgan, Vincent J. Straub, Youmna Hashem and Jonathan Bright12 Artificial intelligence and governance challenges in Latin America – the game between decolonization and dependence 198Fernando Filgueiras13 Proactive algorithmic transparency in government: the case of the Colombian repositories of public algorithms 222Juan David Gutiérrez and Sarah Muñoz-Cadena14 Decoding the privacy puzzle: a study on AI deployment in public governance 239Jose Ramon Saura, Belem Barbosa and Sudhir RanaPART III RESPONSIBLE AND PARTICIPATORY DATA USE BY GOVERNMENT 15 Intersecting digital governance and data science: preparing for communication to strengthen citizen-government partnerships 265Jae-Seong Lee16 Delivering on transparency’s good governance promise? The state of government data against political corruption 282Kristen Rose and Joseph Foti17 System update: emerging transparency and oversight functions for responsible data use 298Joseph Foti, Tara Davis and Divij Joshi18 Classificatory versus transformative data regimes: towards a positive right to data production and analysis 316Willie Gin19 The Janus face of personal data agency in public and private use applications 332Dale Mineshima-Lowe, Roxana Bratu and Sarah Giest20 A social capital perspective to building sustainable data centers for science 346Federica Fusi and Eric W. Welch21 Public sector innovation labs as an approach to data-driven innovation 365Francesco Leoni22 Conclusion, research agenda, and policy recommendations for governance and data science 379Bram Klievink and Sarah GiestIndex 385

‘Big data analysis may not have the answer, and a knowledge of what such an approach can offer (and what it cannot) is important – that alone is justification for the book’s existence.’