Analytic provenance for criminal intelligence analysis

Abstract

In criminal intelligence domain where solution discovery is often serendipitous, it demands techniques to provide transparent evidences of top-down and bottom-up analytical processes of analysts while sifting through or transforming sourced data to provide plausible explanation of the fact. Management and tracing of such security sensitive analytical information flow originated from tightly coupled visualizations into visual analytic system for criminal intelligence that triggers huge amount of analytical information on a single click, involves design and development challenges. In this research paper, we have introduced a system called “PROV” to capture, visualize and utilize analytical information named as analytic provenance by considering such challenges. A video demonstrating its features is available online at https://streamable.com/r8mlx. Prior to develop this system for criminal intelligence analysis, we conducted a systematic research to outline the requirements and technical challenges. We gathered such information from real police intelligence analysts through multiple sessions who are the end users of a large heterogeneous event-driven modular Analyst’s User Interface (AUI) of the project VALCRI (Visual Analytics for Sensemaking in Criminal Intelligence), developed by using visual analytic technique. We have proposed a semantic analytic state composition technique to trigger new insight by schematizing captured reasoning states. To evaluate the system we carried out few subjective feedback sessions with the end-users of the project and found very positive feedback. We also have tested our event triggered analytic state capturing protocol with an external geospatial and temporal crime analysis system and found that our proposed technique works generically for both small and large complex visual analytic systems.

Keywords

• analytic provenance
• visual analytics
• transparency
• visualization design and sensemaking