By Peter Langman and Frank Traub

The Police Foundation, in collaboration with the COPS Office, implemented the Averted School Violence (ASV) database to provide a platform for sharing information about averted incidents of violence in institutions of elementary, secondary, and higher education. As a companion to the preliminary report on the ASV database (Daniels 2018), this report compares 51 completed with 51 averted incidents of school violence from the ASV database and analyzes both sets. It includes findings on the demographics of individuals who plan attacks, victims' demographics in completed attacks, and community characteristics; it also provides important recommendations to minimize school violence and improve student and school safety.

Washington, DC: Office of Community Oriented Policing Services, 2019. 42p.

By T. K. Cocx.

The increase in capabilities of information technology of the last decade has led to a large increase in the creation of raw data. Data mining, a form of computer guided, statistical data analysis, attempts to draw knowledge from these sources that is usable, human understandable and was previously unknown. One of the potential application domains is that of law enforcement. This thesis describes a number of efforts in this direction and reports on the results reached on the application of its resulting algorithms on actual police data. The usage of specifically tailored data mining algorithms is shown to have a great potential in this area, which forebodes a future where algorithmic assistance in "combating" crime will be a valuable asset.

Leiden: Leiden University, 2009. 179p.