Crime in Chicago

Among the 11,363 crimes reported in Chicago during the first 9 months of 2015, theft, battery, criminal damage, narcotics and assault ranked highest, totaling 68% of all reported crime. The infographic below shows a snapshot of crime in Chicago during this period.

Click through to see the enlarged image.
ChicagoCrime_Final

Techniques Used
The above visualization includes 4 main types of visualization techniques:

Text Analysis: The first image is a visual a representation of text data, specifically the word count of the type of crimes (i.e. frequency) displayed as a word cloud.

Spatial Analysis (GIS): The map uses an Inverse Distance Weighted (IDW) interpolation method to identify crime hotspots (in red). It also allows one to predict the frequency of crime at an unknown location based on the known values.

Quantitative Analysis: Two chart types were used to visualize quantitative data – a bar chart showing the crime counts of the major crime types for the most affected ward/community, and a bubble chart showing the number of crime by ward and community.

Implementing visualization techniques in faculty research
The image above shows different visualization techniques that might be used to effectively convey data or research conclusions to different types of audiences in various disciplines or industries.  Visualizations can help identify existing or emerging trends, spot irregularities or obscure patterns, and even address or solve issues.

A good example of one such implementation is John Conroy’s Legal Clinic project in the College of Law. This research project used a multi-pronged approach in which first, various visualizations were created to compare exonerations and false convictions in major U.S. cities. Later, the SSRC trained Conroy’s research assistants how to create an exoneration database and clean and convert data into mappable formats using various techniques.

Ask us how to visualize your research
If you want help visualizing your own research findings or wonder if your research lends itself to similar techniques including data acquisition and preprocessing of both quantitative and qualitative data, contact Nandhini Gulasingam at mgulasin@depaul.edu.

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Author: Nandhini Gulasingam

Nandhini Gulasingam is a Senior Analyst for IT Solutions at the Social Science Research Center (SSRC) where she manages GIS, database, web development projects for the SSRC and is developing data visualization techniques for use in the social and behavioral sciences. She is also an adjunct faculty member in the Department of Geography where she teaches graduate and undergraduate courses on Geographic Information Systems (GIS).

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