UK – Valcri https://valcri.org VALCRI is a European Union project Fri, 07 Oct 2016 09:43:37 +0000 en-US hourly 1 https://wordpress.org/?v=5.2.2 IEEE Infovis 2016 Best Paper Honorable Mention https://euprojectvalcri.org/valcri/ieee-infovis-2016-best-paper-honorable-mention/ Thu, 06 Oct 2016 13:11:57 +0000 https://euprojectvalcri.org/?p=1421 ...]]> A VALCRI research paper has been awarded Best Paper Honorable Mention at IEEE InfoVis, the premier venue for research in Data Visualization. The paper, entitled Map Lineups: Effects of Spatial Structure on Graphical Inference, considers perceptual biases introduced by Choropleth maps. As well as providing new evidence around how well humans are able to discern structure in maps, the paper contributes towards an emerging theory in data analysis of graphical inference. The award places the work amongst the top 3 of 165 papers submitted to this year’s InfoVis conference. The full paper, along with experiment data and analysis code, can be accessed from the paper’s website.

The paper will be presented on Tuesday, 25th Octoberin the InfoVis: Geovisualization paper session at IEEE InfoVis 2016 in Baltimore, US.

]]> Design for Intelligence Analysis of Complex Systems: Evolution of Criminal Networks. https://euprojectvalcri.org/publications/design-for-intelligence-analysis-of-complex-systems-evolution-of-criminal-networks/ Fri, 19 Aug 2016 09:42:48 +0000 https://euprojectvalcri.org/?p=1432 ...]]> Design for Intelligence Analysis of Complex Systems: Evolution of Criminal Networks. Seidler, P.; Haider, J.; Kodagoda, N.; Pohl, M.; and BL William, W. In European Intelligence and Security Informatics Conference, 2016.

Abstract—Intelligence analysts are at the forefront to provide decision makers with a greater picture of current situational context. Their main task is to identify relevant pieces of information from disparate systems and growing amounts of data while often lacking the appropriate tools. We propose a visual analytics approach to support analysts in monitoring and reasoning about the dynamics in a complex system. In our approach, we systematically map relations onto the user interface and support both overview and provenance over temporal dynamics. We further map explicitly otherwise tacit organisational knowledge. Our use case is based on a crime system taking the perspective of criminal network analysis tasks. Our analytics extract forceprioritised, weighted co-offender networks, which are represented through both a graph and a matrix visualisation, incorporating the evolution of relationships between offenders. The developed tools were evaluated in a study with domain experts, with the goal to assess tool utility and to investigate the appropriateness of the tool with the end user.

Keywords–Visualization of Networks; Graph; Time-varying Data; Adjacency Matrix; Evaluation

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