Evaluation of visualization heuristics

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Abstract

Multiple sets of heuristic have been developed and studied in the Human Computer Interaction (HCI) domain as a method for fast, lightweight evaluations for usability problems. However, none of the heuristics have been adopted by the information visualization or the visual analytics communities. Our literature review looked at heuristic sets developed by Nielsen and Molich [7] and Forsell and Johansson [1] to understand how these heuristics were developed and their intended applications. We also reviewed heuristic studies conducted by Hearst and colleagues [2] and Väätäjä and colleagues [10] to determine how individuals apply heuristics to evaluating visualization systems. While each study noted potential issues with the heuristic descriptions and the evaluator’s familiarity with the heuristics, no direct connections were made. Our research looks to understand how individuals with domain expertise in information visualization and visual analytics could use heuristics to discover usability problems and evaluate visualizations. By empirically evaluating visualization heuristics, we can identify the key ways that these heuristics can be used to inform the visual analytics design process. Further, they may help to identify usability problems that are and are not task specific. We hope to use this process to also identify missing heuristics that may apply to designs for different analytic purposes.

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APA

Williams, R., Scholtz, J., Blaha, L. M., Franklin, L., & Huang, Z. (2018). Evaluation of visualization heuristics. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10901 LNCS, pp. 208–224). Springer Verlag. https://doi.org/10.1007/978-3-319-91238-7_18

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