Crime and disorder information systems: theory and practice

The need for timely and relevant information on crime and disorder has never been more crucial. The statutory
requirement in Britain for the police and local authorities to produce crime audits and strategies for their areas coupled
with the drive towards evidence-based policy has placed data sharing and analysis at centre stage. Considerable efforts
are often expended on the identification of data sets on crime, command and control incidents and contextual
information (e.g. population, levels of deprivation, administrative boundaries, road networks) needed to build such
systems. Progress has also been made on defining workable data exchange protocols to enable a wide number of
agencies to share information. There is now a growing number of regional and sub-regional crime information systems
in Britain. Not surprisingly, where systems have been put in place there are often high expectations of what they will
achieve. However, this level of enthusiasm is often met with disappointment because the (often implicit) expectations
far exceed the capabilities of systems to deliver in terms of their data sets and functionality. The problem appears to
stem from a failure to identify the expected outcomes of data sharing and information system development and the
processes or mechanisms through which these can be achieved. Thus, whilst the expected outcome from a burglary
initiative (e.g. target hardening) is to reduce burglary, the anticipated outcomes from a crime and disorder information
system are not as easily identifiable and are rarely made explicit. This paper begins by discussing the rationale behind
sharing and analysing crime data and then goes on to explore the theory (or lack of it) that underpins the development of
crime and disorder information systems. A number of key issues are explored drawing on the author’s experience in the
development and use of information systems (including GIS) in crime research and policy evaluation. Particular
attention is paid to the role of theory in the selection of relevant data sets (hypothesis-driven data capture) and to the
notion of ‘decision support’ in relation to crime and disorder (e.g. What does ‘support’ mean? What types of decision
need supporting? Can tools be designed to help people make decisions? What would they be like?). The paper
concludes with a checklist of considerations to bear in mind in creating a crime and disorder information system