The notion of cause and effect is pervasive in human thinking and plays a significant role in our perception of time. The human mind is especially well-suited to detect instances of this concept of causality. However, as the number of actions and reactions in a system grows, it quickly becomes difficult to follow and gain an understanding of its general flow. We have developed a number of novel visualization techniques for causal relations based on animation, colors and patterns to provide an alternate graphical representation of causality in a system that facilitates quick overview. The Growing Squares and Growing Polygons techniques map the temporal parameter to geometric size and dependencies and information to color and texture, forming interactive influence maps of the system under execution.
We have empirically evaluated the performance of users solving tasks related to causal relations using both our techniques as well as standard Hasse (time-space) diagrams. Our results indicate a significant improvement using our techniques, both in terms of completion time as well as effectiveness. Moreover, our subjects showed strong preference for the new methods over standard tools.
|(2007): CiteWiz: A Tool for the Visualization of Scientific Citation Networks. In: Information Visualization, 6 (3), pp. 215–232, 2007.|
|(2004): Animated Visualization of Causal Relations Through Growing 2D Geometry. In: Information Visualization, 3 (3), pp. 154–172, 2004.|
|(2003): Growing Squares: Animated Visualization of Causal Relations. In: Proceedings of the ACM Symposium on Software Visualization, pp. 17–26, 2003.|
|(2003): Causality Visualization Using Animated Growing Polygons. In: Proceedings of the IEEE Symposium on Information Visualization, pp. 189–196, 2003.|