Asensio, Omar Isaac;
Moore, Catherine E;
Ulibarri, Nicola;
Simsekler, Mecit Can Emre;
Lan, Tian;
Rivero, Gonzalo;
(2025)
Data technologies and analytics for policy and governance: a landscape review.
Data & Policy
, 7
, Article e25. 10.1017/dap.2024.49.
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Abstract
Data for Policy (dataforpolicy.org), a trans-disciplinary community of research and practice, has emerged around the application and evaluation of data technologies and analytics for policy and governance. Research in this area has involved cross-sector collaborations, but the areas of emphasis have previously been unclear. Within the Data for Policy framework of six focus areas, this report offers a landscape review of Focus Area 2: Technologies and Analytics. Taking stock of recent advancements and challenges can help shape research priorities for this community. We highlight four commonly used technologies for prediction and inference that leverage datasets from the digital environment: machine learning (ML) and artificial intelligence systems, the internet-of-things, digital twins, and distributed ledger systems. We review innovations in research evaluation and discuss future directions for policy decision-making.
| Type: | Article |
|---|---|
| Title: | Data technologies and analytics for policy and governance: a landscape review |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1017/dap.2024.49 |
| Publisher version: | https://doi.org/10.1017/dap.2024.49 |
| Language: | English |
| Additional information: | © The Author(s), 2025. Published by Cambridge University Press. This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited. |
| Keywords: | Social Sciences, Public Administration, digital data, digital twins, distributed ledger systems, internet of things, machine learning and artificial intelligence, BIG-DATA, DECISION-MAKING, DIGITAL TWINS, SCIENCE, TWITTER, SYSTEM, MODEL, CITY, REVOLUTION, BLOCKCHAIN |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL SLASH UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > UCL School of Management UCL > Provost and Vice Provost Offices > UCL SLASH > Faculty of S&HS > Dept of Geography |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10206328 |
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