NCJ Number
217961
Journal
Law Enforcement Technology Volume: 34 Issue: 3 Dated: March 2007 Pages: 62,64-68,70
Date Published
March 2007
Length
7 pages
Annotation
This article discusses the importance and techniques of "data mining," the automated analysis of large datasets, based on an interview with Colleen "Kelly" McCue, a senior research scientist at RTI International and former program manager of the Richmond Police Department's Crime Analysis Unit (Virginia).
Abstract
Law enforcement agencies have become proficient at collecting and storing data due to the advent of computerized records management systems. Regional information-sharing initiatives and State-level fusion centers have added to the data that individual agencies can access. Law enforcement agencies are less proficient, however, in analyzing the data they have in order to improve their performance. The analysis of crime and offender data can reveal patterns that lead to crime prevention strategies and predictions of crime trends. There are tools available to assist in such data mining. Using an analytical overlay or filter with remote data entry, an investigator can enter relevant information while at a crime scene and receive a rapid analytical response. Specialized databases can be created for crime or intelligence analysis. Since software for data mining and predictive analysis is expensive, agencies that share information might pool their financial resources in order to purchase this software. Link analysis tools, on the other hand, are relatively inexpensive and can be used to identify relationships in data, such as telephone calls.