Visual Analytics for sense-making in Criminal Intelligence Analysis


VALCRI – Visual Analytics for sense-making in Criminal Intelligence Analysis – is a large–scale integrating project funded by the European Commission under the FP7-security programme starting on 1st of May 2014. It involves 18 partners from Europe and the US and is coordinated by Middlesex University, United Kingdom.
The purpose of Project VALCRI is to create a visual analytics-based reasoning and sense-making capability for criminal intelligence analysis by developing and integrating a number of advanced user interface technologies with powerful analytic software such as in knowledge extraction and spatial temporal analysis into a coherent working environment for the analyst. One of the key problems is to ‘connect the dots’ or to quickly find the few pieces of relevant information from a very large dataset and to piece them together so that the conclusion makes sense and can be justified. Much of this process is presently very labour intensive and inefficient. When completed, VALCRI will integrate advanced and powerful data analytic software for automated extraction of meaningful information and related text, documents, images and video, and for detecting signatures or patterns across multi-dimensional data that provide early warning or triggers of impending criminal or terrorist action.
In the development of these technical solutions, VALCRI will be strongly guided by human issues. These human issues include cognition and sense-making, how to visually support evidential reasoning, and the mitigation of cognitive bias. All these different human-related issues will be consolidated into a principled Human Issues Framework (HIF) that can be used to guide the how the software should be designed. The HIF is expected to be empirically-based, where guidelines generated will be based on studies to be conducted by partners on how the guidelines will affect design, and then feedback from those studies would lead to modifications to the HIF.

The main focus of TUGraz – besides leading the workpackage managing the development of the Human Issues Framework – is to understand how human cognitive biases are activated within different tasks and processes of intelligence and investigative systems, and how they can be mitigated. Work will be built on the work of the FP7-funded RECOBIA project ( by adapting and extending findings and solutions to address the challenges of criminal intelligence professionals.


Research Data: Albert et al. (2018). Effect of Clustering Illusion during the Interaction with a Visual Analytics Environment. Research data of the 2017 study.


Graz Partner: Institute of Interactive Systems and Data Science, Graz University of Technology, Austria/Europe

Duration: 01.05.2014 – 30.06.2018 (50 months)

Funding: Supported by the 7th framework (Security Research) programme (FP7-SEC, IP) of the European Commission. Grant No.: 608142

  • Total Budget: € 16,644,340.12
  • Total Funding: € 13,053,686.42
  • CSS Budget: € 602,900.00