Towards an evidence-based model for big data policing: Evaluating the statistical-methodological, criminological and legal and ethical conditions

01 September 2023 → 31 August 2028
European funding: framework programme
Principal investigator
Research disciplines
  • Natural sciences
    • Statistics
    • Machine learning and decision making
  • Social sciences
    • Causes and prevention of crime
    • Criminography and methods of criminological investigation
    • Police administration, procedures and practice
    • Safety, prevention and police
    • Human rights law
crime big data predictive policing police
Other information
Project description

Big data policing is an innovative strategy that uses historical data to forecast when and where there is a high risk of new crime events in order to use police resources more efficiently and proactively, and ultimately reduce crime rates. Big data policing models can consist of variables based on crime data available in police databases (e.g. previous crime events), socio-economic data (e.g. poverty index, residential mobility), opportunity characteristics (e.g. the presence of shops, distance to nearest highway), data from new technologies (e.g. intelligent cameras) and other known predictors of crime (e.g. police patrol intensity).

The overarching objective of this ERC project is to unite and integrate the statistical-methodological, criminological, legal and ethical dimensions of big data policing in an evidence-based model that will be tested by different randomized controlled trials and built on the principles of an international (i.e. European) and interdisciplinary approach.

Funded by the European Union. 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 Executive Agency (ERCEA). Neither the European Union nor the authority can be held responsible for them.