Geography Reference
In-Depth Information
analysis, the product of which is a level of information processed and extracted
from the ''raw'' point data of WikiCrimes and is therefore in a more digestible and
therefore useful form for law enforcement officers and the public alike. Future plans
include the introduction of other data such as demographic and car ownership data
in an attempt to extract further meaning out of the WikiCrimes dataset
Keywords Web 2.0
Choropleth
Density
eXplorer
WikiCrimes
1 Introduction
Crime is rife and with only a finite amount of resources to control it, law
enforcement agencies need all the help they can get. Technology has stepped into
relieve some of the burden in recent years. The rise of the Internet (in particular
Web 2.0) and use of mobile devices has put effective spatiotemporal data
collection and storage mechanisms in the hands of ordinary people (Goodchild
2007
). For crime management the efforts of a small and finite number of law
enforcement officers have been augmented by information provided by citizen
volunteers. Not only does this give greater coverage but also elicits information
that police, for instance, may find hard to get (e.g. if people are ashamed or scared
of going to the police to report a crime).
WikiCrimes (Furtado et al.
2010
) in Brazil is one such system, a collaborative
Web 2.0 application using the Google Maps API (www.WikiCrimes.org). It has
three major aims—to make crime information more transparent and public; to
address the phenomenon of under-reporting and implicitly; and to prevent future
crime from occurring. However, as with other systems of this kind, there are
possible issues of data credibility due to its informal sources, though in countries
with high violence rates and unreliable reporting of crime, the benefits of such a
collaborative system outweigh any such issues and have been recognized politi-
cally. Since 2008 there have been over 200,000 crimes logged in this system.
The aim of this research is to take part of that dataset and apply geovisual
analytics to it. WikiCrimes beyond point data display can process crime incident
data into hotspots of density. However, the dataset is rich with attributes such as
type of crime, crime victim type, crime settings and reason for the crime as well as
the essential location and date/timestamp that are ripe for exploration. Straight-
forward pointwise display (and indeed density kernels) can give insight on
distribution (it is the intention that such information will have value in the hands of
the public) but misses much information of value.
We have applied eXplorer (Jern
2009
), a freely-available web-based geovisual
analytics tool to the WikiCrimes data. It was hoped that, in line with WikiCrimes'
first objective, the anticipated additional insights mined from the data would
enhance crime transparency and publicity more than the point display of crime
incidence. Furthermore, as a Web 2.0 tool in the public domain the exploration
