MISSION

The BIGDATPOL research programme is developing an evidence-based big data policing model that will be tested in several European cities.

The machine learning model will use (big) data sources (e.g. crime data available in police databases, crime opportunity indicator data such as number of shops, street connectivity, socio-economic data such as age, median income) to anticipate the risk of where and when a residential burglary is likely to occur.

BIGDATPOL is based on previous research, such as key contributions on theory testing of crime concentration at micro places, crime indicators, deterrence, and crime prevention interventions. A suitable model is intended to support law enforcement and crime prevention via an informed allocation of police patrols and the suitability should be determined through robust evaluations.

OUR APPROACH

Knowledge and expertise in the field of big data policing are currently dispersed, hindering the development of effective law enforcement strategies. Interdisciplinary research is essential for a comprehensive understanding of this complex topic, spanning statistical-methodological, criminological, legal, economic, and ethical dimensions.

This groundbreaking research initiative addresses crucial gaps in the existing study of big data policing and will translate it into a European context. The research results will be compatible with modern EU regulations such as the AI act.