Towards analytical provenance visualization for criminal intelligence analysis

In criminal intelligence analysis to complement the information entailed and to enhance transparency of the operations, it demands logs of the individual processing activities within an automated processing system. 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. To lead to a believable story by using scientific methods, reasoning for getting explicit knowledge of series of events, sequences and time surrounding interrelationships with available relevant information by using human perception, cognition, reasoning with database operations and computational methods, an analytic visual judgmental support is obvious for criminal intelligence. Our research outlines the requirements and development challenges of such system as well as proposes a generic way of capturing different complex visual analytical states and processes known as analytic provenance. The proposed technique has been tested into a large heterogeneous event-driven visual analytic modular analyst’s user interface (AUI) of the project VALCRI (Visual Analytics for Sensemaking in Criminal Intelligence) and evaluated by the police intelligence analysts through it’s visual state capturing and retracing interfaces. We have conducted several prototype evaluation sessions with the groups of end-users (police intelligence analysts) and found very positive feedback. Our approach provides a generic support for visual judgmental process into a large complex event-driven AUI system for criminal intelligence analysis

©2016 The Author(s) Eurographics Proceedings © 2016 The Eurographics Association. Permission granted on 19/01/2017, by the Publisher to make the full text of the published version available in the Middlesex University Research Repository.
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Islam, J., Anslow, C., Xu, K., Wong, W., and Zhang, L. (2016), 'Towards Analytical Provenance Visualization for Criminal Intelligence Analysis', in Computer Graphics and Visual Computing (CGVC), Eurographics Association, pp. 17-24. ISBN 978-3-03868-022-2, DOI: 10.2312/cgvc.20161290