Summary report: Driving forward data-informed approaches to policing
22.01.2020
Susan McVie
In October 2019, Understanding Inequalities held a joint event with the Scottish Centre for Administrative Data Research (SCADR) and Police Scotland to discuss data-informed approaches to policing, looking at the use of police data to assess demand, inform deployment and address priorities.
We have produced a short summary report which draws together themes from the presentations and facilitated discussion. These themes included the data priorities for policing in Scotland, the various different data sources that are currently being used to inform policing, the challenges associated with accessing and linking types of data, while the report also highlights the potential solutions and ways of working across organisations to mitigate some of these challenges.
In October 2019, Understanding Inequalities held a joint event with the Scottish Centre for Administrative Data Research (SCADR) and Police Scotland to discuss data-informed approaches to policing, looking at the use of police data to assess demand, inform deployment and address priorities.
We have produced a short summary report which draws together themes from the presentations and facilitated discussion. These themes included the data priorities for policing in Scotland, the various different data sources that are currently being used to inform policing, the challenges associated with accessing and linking types of data, while the report also highlights the potential solutions and ways of working across organisations to mitigate some of these challenges.
Read the report in full here.
You can also find the presentations from the day online below:
Understanding & Addressing Demand: Insights from Data Analytics - Professor Jon Bannister - Director of the Crime & Well-Being Big Data Centre, Manchester Metropolitan University.
Using data to examine spatial and temporal patterns of crime and policing in Scotland - Professor Susan McVie, Director of the Understanding Inequalities Project, University of Edinburgh.