Michael Burch
ABSTRACT
Visualizing dynamic graphs is challenging due to the many data dimensions to be displayed such as graph vertices and edges with their attached weights or attributes and the additional time dimension. Moreover, edge directions with multiplicities and the graph topology are also important inherent features. However, in many dynamic graph visualization techniques each graph in a sequence is treated the same way, i.e., it is visually encoded in the same visual metaphor or even in the same layout. This visualization strategy can be problematic if the graphs are changing topologically over time, i.e., if a sparse graph becomes denser and denser over time or a star pattern is changing into a dense cluster of connected vertices. Such a dynamic graph data scenario demands for a visualization approach which is able to adapt the applied visual metaphor to each graph separately. In this paper we show an idea to solve this problem by using multiple visual metaphors for dynamic graphs which are computed automatically by algorithms analyzing each individual graph based on a given repertoire of graph features. The biggest issue in this technique for the graph dynamics, however, is the preservation of the viewer's mental map at metaphor changes, i.e., to guide him through the graph changes with the goal to explore the data for time-varying patterns. To reach this goal we support the analyst by an interactive highlighting feature.
- F. Beck, M. Burch, and S. Diehl. Towards an aesthetic dimensions framework for dynamic graph visualisations. In Proceedings of the 13th International Conference on Information Visualisation, pages 592--597, 2009. Google Scholar
Digital Library
- F. Beck, M. Burch, and S. Diehl. Matching application requirements with dynamic graph visualization profiles. In Proceedings of 17th International Conference on Information Visualisation, pages 11--18, 2013. Google ScholarDigital Library
- F. Beck, M. Burch, S. Diehl, and D. Weiskopf. The state of the art in visualizing dynamic graphs. In EuroVis State-of-the-Art Reports, EuroVis STAR, 2014.Google Scholar
- M. Burch, C. Vehlow, F. Beck, S. Diehl, and D. Weiskopf. Parallel edge splatting for scalable dynamic graph visualization. IEEE Transactions on Visualization and Computer Graphics, 17(12):2344--2353, 2011. Google ScholarDigital Library
- M. Burch, C. Vehlow, N. Konevtsova, and D. Weiskopf. Evaluating partially drawn links for directed graph edges. In Proc. of Graph Drawing, pages 226--237, 2011. Google ScholarDigital Library
- M. Burch and D. Weiskopf. A flip-book of edge-splatted small multiples for visualizing dynamic graphs. In The 7th International Symposium on Visual Information Communication and Interaction, VINCI, page 29, 2014. Google ScholarDigital Library
- T. F. Coleman and J. J. More. Estimation of sparse Jacobian matrices and graph coloring problems. SIAM Journal on Numerical Analysis, 20(1):187--209, 1983.Google ScholarCross Ref
- S. Diehl and C. Görg. Graphs, they are changing. In Proceedings of 10th International Symposium on Graph Drawing, pages 23--30, 2002. Google ScholarDigital Library
- L. Euler. Solutio problematis ad geometriam situs pertinentis. Commentarii Academiae Scientiarum Petropolitanae, 8:128--140, 1741.Google Scholar
- Y. Frishman and A. Tal. Dynamic drawing of clustered graphs. In Proceedings of 10th IEEE Symposium on Information Visualization, pages 191--198, 2004. Google ScholarDigital Library
- T. M. J. Fruchterman and E. M. Reingold. Graph drawing by force-directed placement. Software, Practice, and Experience, 21(11):1129--1164, 1991. Google ScholarDigital Library
- M. Ghoniem, J. Fekete, and P. Castagliola. On the readability of graphs using node-link and matrix-based representations: a controlled experiment and statistical analysis. Information Visualization, 4(2):114--135, 2005. Google ScholarDigital Library
- N. Henry and J. Fekete. Matlink: Enhanced matrix visualization for analyzing social networks. In Proc. of Conference on Human-Computer Interaction - INTERACT, pages 288--302, 2007. Google ScholarDigital Library
- N. Henry, J. Fekete, and M. J. McGuffin. Nodetrix: Hybrid representation for analyzing social networks. CoRR, abs/0705.0599, 2007.Google Scholar
- M. Hlawatsch, M. Burch, and D. Weiskopf. Visual adjacency lists for dynamic graphs. IEEE Transactions on Visualization and Computer Graphics, 20(11):1590--1603, 2014.Google ScholarCross Ref
- D. Holten. Hierarchical edge bundles: Visualization of adjacency relations in hierarchical data. IEEE Transactions on Visualization and Computer Graphics, 12(5):741--748, 2006. Google ScholarDigital Library
- D. Holten, P. Isenberg, J. J. van Wijk, and J. Fekete. An extended evaluation of the readability of tapered, animated, and textured directed-edge representations in node-link graphs. In Proc. of IEEE Pacific Visualization Symposium, pages 195--202, 2011. Google ScholarDigital Library
- D. Holten and J. J. van Wijk. A user study on visualizing directed edges in graphs. In Proc. of the Int. Conference on Human Factors in Computing Systems, pages 2299--2308, 2009. Google ScholarDigital Library
- W. Huang, P. Eades, S. Hong, and C. Lin. Improving multiple aesthetics produces better graph drawings. Journal of Visual Languages and Computing, 24(4):262--272, 2013. Google ScholarDigital Library
- K. Kuratowski. Sur le probleme des courbes gauches en topologie. Fund. Math. (in French), 15:271--283, 1930.Google Scholar
- B. Lee, C. Plaisant, C. S. Parr, J.-D. Fekete, and N. Henry. Task taxonomy for graph visualization. In Proc. of the AVI Workshop on BEyond time and errors: novel evaluation methods for information visualization, pages 1--5, 2006. Google ScholarDigital Library
- H. C. Purchase, R. F. Cohen, and M. I. James. Validating graph drawing aesthetics. In Proceedings of the International Symposium on Graph Drawing, pages 435--446, 1995. Google ScholarDigital Library
- H. C. Purchase, E. Hoggan, and C. Görg. How important is the mental map? An empirical investigation of a dynamic graph layout algorithm. In Proceedings of the International Symposium on Graph Drawing, pages 262--273, 2007. Google ScholarDigital Library
- R. Rosenholtz, Y. Li, J. Mansfield, and Z. Jin. Feature congestion: a measure of display clutter. In Proceedings of Conference on Human Factors in Computing Systems, pages 761--770, 2005. Google ScholarDigital Library
- K. Sugiyama, S. Tagawa, and M. Toda. Methods for visual understanding of hierarchical system structures. IEEE Transactions on Systems, Man, and Cybernetics, 11(2):109--125, 1981.Google ScholarCross Ref
- B. Tversky, J. B. Morrison, and M. Bétrancourt. Animation: can it facilitate? International Journal of Human-Computer Studies, 57(4):247--262, 2002. Google ScholarDigital Library
- T. von Landesberger, A. Kuijper, T. Schreck, J. Kohlhammer, J. J. van Wijk, J. Fekete, and D. W. Fellner. Visual analysis of large graphs: State-of-the-art and future research challenges. Computer Graphics Forum, 30(6):1719--1749, 2011.Google ScholarCross Ref
- K. Wagner. Über eine Eigenschaft der ebenen Komplexe. Math. Ann., 114:570--590, 1937.Google ScholarCross Ref
- Dynamic Graph Visualization with Multiple Visual Metaphors
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