Diane Watson, George Fitzmaurice, Justin Matejka
Diane Watson, George Fitzmaurice, Justin Matejka
Graphics Interface Conference
2021
How Tall is that Bar Chart? (3:31 min.)
As virtual reality (VR) technology becomes more available, VR applications will be increasingly used to present information visualizations. While data visualization in VR is an interesting topic, questions remain about how effective or accurate visualization can be. One known phenomenon with VR environments is that people tend to unconsciously compress or underestimate distances. However, it is unknown if or how this effect will alter the perception of data visualizations in VR. To this end, we replicate portions of Cleveland and McGill’s foundational perceptual visualization studies in VR. Through a series of three studies, we find that distance compression negatively affects estimations of actual lengths (heights of bars), but does not appear to impact relative comparisons. Additionally, by replicating the position-angle experiments, we find that (as with traditional 2D visualizations) people are better at relative length evaluations than relative angles. Finally, by looking at these open questions, we develop a series of best practices for performing data visualization in a VR environment.
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Visual data representations leverage the power of human perception to process complex information, and through interaction, garner new insights. Our research focuses on visualizing data from a wide variety of domains and fundamentally tackles the question, what makes a visualization effective? We explore novel visual encodings and interaction techniques, multiscale approaches, and even simulation to bridge human and automated analysis of multivariate, time-series, and graph data, ultimately aiding in hypothesis generation, testing, and sense making.