Unfolding Dynamic Networks for Visual Exploration

Visualization builds on the human capacity to quickly process parallel visual inputs and to offload cognitive processes. Interactive visualizations can become interfaces between humans, their data, and the phenomena represented by the data. Such interfaces can allow for exploration, enable serendipitous discoveries, and serve as a mental metaphor to help us remember and reason about the data. This article gives a brief overview of the author's dissertation research, which is concerned with creating and evaluating novel interfaces to explore dynamic networks, supporting analysts in formulating hypotheses, and discussing proper analysis methods.