, pages 140–143, Uppsala, Sweden, August 2016. \n
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@inproceedings{seidler_design_2016,\n\taddress = {Uppsala, Sweden},\n\ttitle = {Design for {Intelligence} {Analysis} of {Complex} {Systems}: {Evolution} of {Criminal} {Networks}},\n\tshorttitle = {Design for {Intelligence} {Analysis} of {Complex} {Systems}},\n\tdoi = {10.1109/EISIC.2016.036},\n\tabstract = {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 force-prioritised, 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.},\n\tbooktitle = {2016 {European} {Intelligence} and {Security} {Informatics} {Conference} ({EISIC})},\n\tauthor = {Seidler, P. and Haider, J. and Kodagoda, N. and Wong, B. L. W. and Pohl, M. and Adderley, R.},\n\tmonth = aug,\n\tyear = {2016},\n\tkeywords = {Adjacency Matrix, Bars, Color, Complex systems, Context, Force, Law enforcement, Time-varying Data, User Interface, Visual analytics, Visualization, Visualization of Networks, complex system, criminal network analysis, data analysis, data visualisation, evaluation, force-prioritised weighted co-offender networks, graph, graph theory, law administration, matrix algebra, matrix visualisation, organisational aspects, tacit organisational knowledge, temporal dynamics, tool utility},\n\tpages = {140--143},\n}\n\n
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\n 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 force-prioritised, 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.\n