Utilizing compression and refinement to handle large cases in crime analysis

When large arguments are produced graph visualizations are often hard to read. Argument visualization software should therefore offer features that allow users to display their graphs in a readable way. More specialized software for crime analysts should also offer the ability to elaborate on graphs and to hide redundant nodes. While doing so, it should be easy to unfold all hidden information about a certain node if desired. Therefore, refinement and compression methods are implemented in the AVERs software for crime analysts. This paper presents the results of a study that tested the effect of compression and refinement on the quality of the users’ analysis of a simple crime case and their understanding of this case. In this study professional crime analysts and students who used these methods outperformed users that were only allowed to use conventional methods to handle large graphs.