Data for peace: how novel data sources and technology can enhance peace?
Abstract In this editorial, we draw insights from a special collection of peer-reviewed papers investigating how new data sources and technology can enhance peace. The collection examines local and global practices that strive towards positive peace through the responsible use of frontier technologies. In particular, the articles of the collection illustrate how advanced techniques—including machine learning, network analysis, specialised text classifiers, and large-scale predictive analytics—can deepen our understanding of conflict dynamics by revealing subtle interdependencies and patterns. Others assess innovative approaches reinterpreting peace as a relational phenomenon. Collectively, they assess ethical, technical, and governance challenges while advocating balanced frameworks that ensure accountability alongside innovation. The collection offers a practical roadmap for integrating technical tools into peacebuilding to foster resilient societies and non-violent conflict transformations.
Authors
- Stefaan Verhulst (ORCID: https://orcid.org/0000-0002-0107-2984)
- Evelyne Tauchnitz (ORCID: https://orcid.org/0009-0003-4376-6989)
- Kalypso Nicolaïdis (ORCID: https://orcid.org/0000-0002-4596-3148)
- Innar Liiv (ORCID: https://orcid.org/0000-0001-5236-0145)
- Michele Giovanardi (ORCID: https://orcid.org/0000-0001-6491-5371)
- Martin Wählisch
Institutions
- Tallinn University of Technology (EE)
- City College of New York (US)
- University of Lucerne (CH)
- United States Institute of Peace (US)
- Statistics Belgium (BE)
- Government of the United Kingdom (GB)
- Centre for International Governance Innovation (CA)
- University for Peace (CR)
- New York University (US)
- Lucerne University of Applied Sciences and Arts (CH)
- European University Institute (IT)
Publication Details
- Journal
- Data & Policy
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1017/dap.2025.10006
- Primary Topic
- Peacebuilding and International Security
- Type
- article
- Field-Weighted Citation Impact
- 0.00