Filtering and Brushing with Motion

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Abstract
Visualizing information in user interfaces to complex, large-scale systems is difficult due to visual fragmentation caused by an enormous amount of inter-related data distributed across multiple views. New display dimensions are required to help the user visually integrate and filter such spatially distributed and heterogeneous information. Motion holds promise in this regard as a perceptually efficient display dimension. It has long been known to have a strong grouping effect, suggesting it has potential for filtering and brushing techniques. However, there is little known about which properties of motion are most effective. This paper reviews the prior literature relating to the use of motion for display and discusses the requirements for how motion can be usefully applied to these problems, especially for visualizations incorporating multiple groups of data objects. Results from previous research by the authors suggested motion type was a strong distinguishing feature. Three types of motions in pairwise combinations were compared: linear, circular and expansion/contraction. Combinations of linear directions were also compared to evaluate how great angular separation needs to be to enforce perceptual distinction. The results showed that motion can effectively group objects that are otherwise dissimilar. Type differentiation is more effective than directional differences (except for 90°). Of the three types studied, circular demands the most attention. Angular separation must be 90° to be equally effective. These results suggest that motion can be usefully applied to both filtering and brushing. They also provide the beginnings of a vocabulary of simple motions that can be applied to information visualization.

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