A

Digital & data-driven transformations in governance: a landscape review

Data & Policy, vol. 7

Abstract

Abstract Data for Policy (dataforpolicy.org), a global community, focuses on policy–data interactions by exploring how data can be used for policy in an ethical, responsible, and efficient manner. Within its journal, six focus areas, including Data for Policy Area 1: Digital & Data-driven Transformations in Governance, were established to delineate the evolving research landscape from the Data for Policy Conference series. This review addresses the absence of a formal conceptualization of digital and data-driven transformations in governance within this focus area. The paper achieves this by providing a working definition, mapping current research trends, and proposing a future research agenda centered on three core transformations: (1) public participation and collective intelligence; (2) relationships and organizations; and (3) open data and government. The paper outlines research questions and connects these transformations to related areas such as artificial intelligence (AI), sustainable smart cities, digital divide, data governance, co-production, and service quality. This contribution forms the foundational development of a research agenda for academics and practitioners engaged in or impacted by digital and data-driven transformations in policy and governance.

Authors 4

  1. Leiden University

    Affiliation as printed

    Public Administration Institute, University of Leiden, Leiden, The Netherlands

  2. University of Oxford

    Affiliation as printed

    Oxford Internet Institute, University of Oxford, Oxford, UK

  3. University of Tartu

    Affiliation as printed

    Faculty of Science and Technology, Institute of Computer Science, University of Tartu, Tartu, Estonia

  4. Leibniz Institute of Ecological Urban and Regional Development

    Affiliation as printed

    Leibniz Institute of Ecological Urban and Regional Development, Dresden, Germany

Cited by 20 stored of 21

20 results

No patents citing this paper on Lens.org (checked 2026-10-11).

References 100