Sorting visual complexity and intelligibility of information visualization forms

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Abstract

Faced with the challenge of information explosion, almost everyone have been exposed to some kind of information visualization in varies of forms. Understanding how people read, understand, interpret and distinguish various forms of visualizations helps designers and developers think about how to improve the designs from the perspectives of users. This paper applied a mixed research method of quantitative and qualitative to explore how the designs of visualization forms evolved, and whether those kinds of graphs and charts are easy for users to understand, and how much information the users can get from the visualization. By testing if users are able to easily and accurately reach the information and providing the scales of simple to complex, and easy to hard, we see that basic visualizations like bar, pie, bubble, line, and scatter charts have been distributed in areas which are relatively simple in design and easy to read. Nonetheless, visualizations like the tree, parallel coordinate, sunburst, heat map, box plot and Sankey graphs have been concentrated in the regions of relatively complex in design, and are difficult to understand. In addition, the visualizations, including stacked bar, word cloud, box plot, and theme river that frequently appeared in the middle region of the grid, embodied the transitions of visualization design from simple to complex, and easy to hard.

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APA

Li, M., Wu, W., Chen, Y. V., Niu, Y., & Xue, C. (2017). Sorting visual complexity and intelligibility of information visualization forms. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10273 LNCS, pp. 124–135). Springer Verlag. https://doi.org/10.1007/978-3-319-58521-5_9

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