Affiliations: United Kingdom Office for National Statistics,
Strategy and Standards Directorate, Hampshire PO15 5RR, UK | United Kingdom Office for National Statistics,
Strategy and Standards Directorate, 1 Drummond Gate, London, UK
Abstract: Kernel smoothing methods can be used to visualise complex point
event data that are distributed geographically. The visualisations generated by
these methods allow users to observe trends in the data which may not be
apparent from numerical summaries or by visualising the point data themselves.
Crime data in the UK has recently been made available to the public for the
smallest postal delivery areas in the country (postcodes). Visualisations of
the number of recorded events at each postcode for a given area are provided
online. In this paper we apply some widely used kernel smoothing methods to
this data, to assess the use of kernel smoothing methods as applied to open
access data. Kernel smoothing methods are applied to crime data from the
Greater London metropolitan area using freely available packages for the open
source R program. We also investigate the utility of using simple methods to
smooth the data over time. The kernel smoothers used are demonstrated to
provide effective and useful visualisations of the data, and it is proposed
that these methods should be more widely applied in exploratory data
visualisation in the future.
Keywords: Data smoothing, kernel density estimation, recorded crime statistics, open source tools
