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Toward Visualization in Policy Modeling

Kohlhammer, Jörn and Nazemi, Kawa and Ruppert, Tobias and Burkhardt, Dirk (2012):
Toward Visualization in Policy Modeling.
In: IEEE Computer Graphics and Applications, pp. 84-89, 32, (5), DOI: 10.1109/MCG.2012.107,
[Article]

Abstract

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.

Item Type: Article
Erschienen: 2012
Creators: Kohlhammer, Jörn and Nazemi, Kawa and Ruppert, Tobias and Burkhardt, Dirk
Title: Toward Visualization in Policy Modeling
Language: English
Abstract:

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.

Journal or Publication Title: IEEE Computer Graphics and Applications
Volume: 32
Number: 5
Uncontrolled Keywords: Business Field: Visual decision support, Research Area: Generalized digital documents, Policy modeling, Information visualization, Visual analytics, Semantics visualization
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Date Deposited: 12 Nov 2018 11:16
DOI: 10.1109/MCG.2012.107
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