The BIGDATPOL research programme addresses one of the central challenges in European security: how to use big data and artificial intelligence responsibly and effectively for crime prevention. Police and security organisations operate in data-rich environments where digital traces, mobility data, and algorithmic tools increasingly shape practice. Without a coherent framework, these initiatives risk remaining fragmented, difficult to compare across jurisdictions, and potentially harmful to public trust.
The programme responds to this challenge by developing predictive models that are rigorous from a methodological perspective, grounded in criminological theory, and fully compliant with legal and ethical requirements. Its ambition is not only to advance academic knowledge, but also to deliver practical tools and guidelines that support big data policing across Europe.
The research programme is led by Prof. Wim Hardyns at Ghent University and supported by a prestigious ERC Consolidator Grant from the European Research Council (ERC, BIGDATPOL, 101088156).
Towards an evidence-based
model for big data policing
Big data policing is an approach to law enforcement that uses advanced analytical techniques and diverse (big) data to understand, predict and tackle crime. It involves collecting, analysing and interpreting different types of data, such as crime statistics, demographic information, spatial markers, mobile phone data and more.
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“Funded by the European Union (ERC, BIGDATPOL, 101088156). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them.”