The aim of this study is to test a technological solution to two traditional limitations of information sharing between law enforcement agencies: data quality and privacy concerns.
Entity Analytics Software (EAS) was tested in two studies with North American law enforcement agencies. In the first test, duplicated cases held in a police record system were successfully identified (4.0 percent) to a greater extent than the traditionally used software program (1.5 percent). This resulted in a difference of 11,954 cases that otherwise would not have been identified as duplications. In the second test, entity information held separately by police and border officials was shared anonymously between these two organizations. This resulted in 1,827 alerts regarding entities that appeared in both systems; traditionally, this information could not have been shared, given privacy concerns, and neither agency would be aware of the relevant information held by the other. Data duplication resulted in an additional 1,041 alerts, which highlights the need to use technological solutions to improve data quality prior to and during information sharing.
The current study demonstrated that EAS has the potential to merge data from different technologically based systems, while identifying errors and reducing privacy concerns through anonymization of identifiers.
While only one potential technological solution (EAS) was tested and organizations must consider the potential expense associated with implementing such technology, the implications resulting from both studies for improved awareness and greater efficiency support and facilitate information sharing between law enforcement organizations.
Plecas, D., McCormick, A., Levine, J., Neal, P. and Cohen, I. (2011), "Evidence‐based solution to information sharing between law enforcement agencies", Policing: An International Journal, Vol. 34 No. 1, pp. 120-134. https://doi.org/10.1108/13639511111106641Download as .RIS
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