A Bounded Measure for Estimating the Benefit of Visualization (Part I): Theoretical Discourse and Conceptual Evaluation

• Published in: Entropy (Basel, Switzerland) Vol. 24; no. 2; p. 228
• Main Authors: Chen, Min, Sbert, Mateu
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 31.01.2022; MDPI
• Subjects: Algorithms; benefit of visualization; Case studies; Cost benefit analysis; divergence measure; Evaluation; human knowledge in visualization; Information theory; Knowledge; Machine learning; Mathematical analysis; Multiple criterion; theory of visualization; Visualization; metro map; human knowledge in visualization; abstraction; divergence measure; cost–benefit analysis; deformation; theory of visualization; information theory; benefit of visualization; volume visualization

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...