A dynamic microsimulation framework for generating synthetic spatiotemporal crime patterns

The significance of synthetic crime datasets in criminological research cannot be underestimated, as real crime datasets are usually unavailable in many policing jurisdictions, due to reasons such as privacy concerns and the lack of shareable data formats. This study introduces a dynamic microsimulation framework by which a specified spatiotemporal crime pattern can be synthesised. A case study presented compares a real crime dataset with the synthesised datasets, and found certain spatiotemporal similarities between them. The developed model has the potential for wider applications in criminology, given some identified areas of improvement.