Privacy-Preserving Data Integration for Recidivism Assessment

The emergence of Digital Justice in conjunction with advanced Data Analysis techniques presents the opportunity to advance the criminal justice system toward an innovative Data-Driven ap- proach. An important issue of public safety is the analysis of le- gal recidivism. Assessing recidivism is a complex measurement problem that necessitates reconstructing a subject’s criminal his- tory from criminal records, which usually reside in different au- tonomous databases. In addition, the collection and processing of sensitive legal-related data about individuals imposes consideration of privacy legislation and confidentiality implications. This paper presents the design and development of a Proof of Concept (PoC) for a Privacy-Preserving Data Integration (PPDI) framework to es- tablish a Data Warehouse across criminal and court sources within the Italian Justice Domain and a Data Mart to assess the recidivism phenomena.