Ongoing research on information visualization has produced an ever-increasing number of visualization designs. Despite this activity, limited progress has been made in categorizing this large number of information visualizations. This makes understanding their common design features challenging, and obscures the yet unexplored areas of novel designs. With this work, we provide categorization from an evolutionary perspective, leveraging a computational model to represent evolutionary processes, the phylogenetic tree. The result - a phylogenetic tree of a design corpus of hierarchical visualizations - enables better understanding of the various design features of hierarchical information visualizations, and further illuminates the space in which the visualizations lie, through support for interactive clustering and novel design suggestions. We demonstrate these benefits with our software system, where a corpus of two-dimensional hierarchical visualization designs is constructed into a phylogenetic tree. This software system supports visual interactive clustering and suggesting for novel designs; the latter capacity is also demonstrated via collaboration with an artist who sketched new designs using our system.
Li, S., Crouser, R. J., Griffin, G., Gramazio, C., Schulz, H.-J., Childs, H., & Chang, R. (2015). Exploring hierarchical visualization designs using phylogenetic trees. In D. L. Kao, M. C. Hao, M. A. Livingston, & T. Wischgoll (Eds.) (p. 939709). https://doi.org/10.1117/12.2078857