A Bounded Measure for Estimating the Benefit of Visualization (Part I): Theoretical Discourse and Conceptual Evaluation |
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Authors: | Min Chen Mateu Sbert |
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Institution: | 1.Oxford e-Research Centre (OeRC), Department of Engineering Science, University of Oxford, Oxford OX1 3QG, UK;2.Department of Informàtica i Matemàtica Aplicada, University of Girona, 17071 Girona, Spain; |
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Abstract: | Information theory can be used to analyze the cost–benefit of visualization processes. However, the current measure of benefit contains an unbounded term that is neither easy to estimate nor intuitive to interpret. In this work, we propose to revise the existing cost–benefit measure by replacing the unbounded term with a bounded one. We examine a number of bounded measures that include the Jenson–Shannon divergence, its square root, and a new divergence measure formulated as part of this work. We describe the rationale for proposing a new divergence measure. In the first part of this paper, we focus on the conceptual analysis of the mathematical properties of these candidate measures. We use visualization to support the multi-criteria comparison, narrowing the search down to several options with better mathematical properties. The theoretical discourse and conceptual evaluation in this part provides the basis for further data-driven evaluation based on synthetic and experimental case studies that are reported in the second part of this paper. |
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Keywords: | information theory theory of visualization cost– benefit analysis divergence measure benefit of visualization human knowledge in visualization abstraction deformation volume visualization metro map |
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