Evaluating multivariate visualizations as multi-objective decision aids

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Abstract

When choosing a solution, decision makers are often required to account for multiple conflicting objectives. This is a situation that can result in a potentially huge number of candidate solutions. Despite the wide selection of multivariate visualizations that can potentially help decide between various candidates, no designated means exist to assess the effectiveness of these visualizations under different circumstances. As a first contribution in this work, we developed a method to evaluate different types of multivariate visualization. The method focuses on the visualization's ability to facilitate a better understanding of inter-objective trade-offs as a proxy to more sensible decision making. We used the method to evaluate two existing visualization aids: Parallel-Coordinates and an adaptation of Self Organizing Maps (SOM). Both visualizations were compared with tabular data presentation. Our results show that the first visualization is more effective than a plain tabular visualization for the purpose of multi-objective decision making. © 2013 IFIP International Federation for Information Processing.

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APA

Taieb-Maimon, M., Limonad, L., Amid, D., Boaz, D., & Anaby-Tavor, A. (2013). Evaluating multivariate visualizations as multi-objective decision aids. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8117 LNCS, pp. 419–436). https://doi.org/10.1007/978-3-642-40483-2_29

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