Animation, Small Multiples, and the Effect of Mental Map Preservation in Dynamic Graphs

Daniel Archambault 1 Helen Purchase 2 Bruno Pinaud 3, 4
4 GRAVITE - Graph Visualization and Interactive Exploration
Université Sciences et Technologies - Bordeaux 1, Inria Bordeaux - Sud-Ouest, École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB), CNRS - Centre National de la Recherche Scientifique : UMR
Abstract : In this paper, we present the results of a human computer interaction experiment that compared the performance of the animation of dynamic graphs to the presentation of small multiples and the effect that mental map preservation had on the two conditions. Questions used in the experiment were selected to test both local and global properties of graph evolution over time. The data sets used in this experiment were derived from standard benchmark data sets of the information visualization community. We found that small multiples gave significantly faster performance than animation overall and for each of our five graph comprehension tasks. In addition, small multiples had significantly more errors than animation for the tasks of determining sets of nodes or edges added to the graph during the same timeslice, although a positive time-error correlation coefficient suggests that, in this case, faster responses did not lead to more errors. This result suggests that, for these two tasks, animation is preferable if accuracy is more important than speed. Preserving the mental map under either the animation or the small multiples condition had little influence in terms of error rate and response time.
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Daniel Archambault, Helen Purchase, Bruno Pinaud. Animation, Small Multiples, and the Effect of Mental Map Preservation in Dynamic Graphs. IEEE Transactions on Visualization and Computer Graphics, Institute of Electrical and Electronics Engineers, 2011, 17 (4), pp.539-552. ⟨http://doi.ieeecomputersociety.org/10.1109/TVCG.2010.78⟩. ⟨10.1109/TVCG.2010.78⟩. ⟨inria-00472423⟩

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