ABSTRACT

People rely on visualizations to understand and communicate patterns in data, processes in diagrams, or routes within maps, in domains including journalism, education, business, and security. These visualizations are increasingly dynamic, using moving objects or animated patterns to show trends and interactions in the data. In many cases these dynamic displays can help people understand these relationships, but in some cases these dynamic elements can overwhelm people or lead them to incorrect conclusions. Across all of these domains, even expert designers have trouble predicting which displays will work. Through psychology-based experiments and interviews with expert visualization designers, this project will explore the power and limits of dynamic visualization. It will result in a set of guidelines that will enable designers from diverse backgrounds and levels of experience to create more effective displays that lead to better understanding, education, and decisions.

To understand how people process and interpret these dynamic displays, the investigators will catalog an abstracted set of intended uses for animation across data displays (e.g., track a value across an axis change in a graph) by interviewing designers of data displays and validating how well their designs meet their stated goals. In collaboration with these designers, the research team will conduct a series of empirical tests of the power and limits of the human visual system to process the intended patterns, with an initial set of experiments that will test the ability of dynamic visualizations to support viewers in seeing statistics, making comparisons, tracking objects, and drawing attention. The investigators will use these findings to generate a practitioner?s guide for designing effective displays for common goals. In ongoing consultations with our team of designers and advisors, the investigators will incorporate their feedback about (a) whether our abstracted displays, tasks, and measures remain relevant to their in-context case studies, and (b) whether our practitioner?s guide is consistent with their expectations and captures rules that should generalize across most case-study contexts.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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