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

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.

Temporal Multivariate Networks

“…Empirical studies to compare the advantages and drawbacks of these approaches ("Animation" vs. "Small Multiples") have been performed by Archambault et al [7] as well as Farrugia and Quigley [38]. And even more recently, Rufiange et al have developed a hybrid approach that lets the user interactively combine or switch between animations, small multiples, and plots that explicitly indicate what has changed [90].…”

“…Even small motions on each vertex are too much to perceive if they are chaotic, but if vertices move coherently, they can be perceived as a single group [94]. In a series of papers Archambault and Purchase evaluate various approaches for dynamic graph visualization and consider how they affect mental map preservation [7,4,6], also summarized in a recent survey [5].…”

Difference Map Readability for Dynamic Graphs

“…A number of dynamic graph drawing algorithms have looked at effective ways of preserving the mental map [16,8,7,9,14,11,13,5], and various experiments have investigated the effect of preserving the mental map [17,20,18,1].…”

“…The assigned strength of these inter-timeslice edges controls the amount of mental map preservation between timeslices: the higher the strength of the inter-timeslice edges, the shorter the distance nodes can move, increasing the degree of mental map preservation. Informed by previous experiments [18,1], we use a relatively low level of mental map preservation over all conditions and factors in this experiment.…”

“…Archambault et al [1] compare small multiples and animation in addition to the effect of the mental map. In this experiment, small multiples was significantly faster overall and for most tasks.…”