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Toward visualization in policy modeling

: Kohlhammer, Jörn; Nazemi, Kawa; Ruppert, Tobias; Burkhardt, Dirk


IEEE Computer Graphics and Applications 32 (2012), No.5, pp.84-89
ISSN: 0272-1716
ISSN: 1558-1756
Journal Article
Fraunhofer IGD ()
policy modeling; information visualization; visual analytic; semantic visualization

Information visualization and visual analytics have become widely recognized research fields applied to a variety of domains and data-related challenges. This development's main driver has been the rapidly increasing amount of data that must be dealt with daily. At the same time, citizens, shareholders, and customers expect highly efficient, informed decision-making based on increasingly complex, dynamic, and interdependent data and information. All this applies in many ways to public-policy modeling. As the recent financial crisis has shown, policy making and regulation are highly challenging tasks. The outcomes of policy choices and individual behavior aren't easily predictable in our complex society. Ubiquitous computing, crowd sourcing, and open data, to name just a few examples, are creating masses of data that governments struggle to make sense of for policy modeling. Increasingly, policy makers are perceiving visualization and data analysis as critical to this sense-making process. This article examines the current and future roles of information visualization, semantics visualization, and VA in policy modeling.