Edge-stacked Timelines for Visualizing Dynamic Weighted Digraphs

Michael Burch, Tanja Munz, Daniel Weiskopf

2015

Abstract

We investigate the problem of visually encoding time-varying weighted digraphs to provide an overview about dynamic graphs. Starting from a rough overview of dynamic relational data an analyst can subsequently explore the data in more detail to gain further insights. To reach this goal we first map the graph vertices in the graph sequence to a common horizontal axis. Edges between vertices are represented as stacked horizontal and color-coded links starting and ending at their corresponding start and end vertex positions. The direction of each edge is indicated by placing it either above or below the horizontal vertex line. We attach a vertically aligned timeline to each link to show the weight evolution for those links. The order of the vertices and stacked edges is important for the readability of the visualization. We support interactive reordering and sorting in the vertex, edge, and timeline representations. The usefulness of our edge-stacked timelines is illustrated in a case study showing dynamic call graph data from software development.

References

  1. Archambault, D., Purchase, H., and Pinaud, B. (2011). Animation, small multiples, and the effect of mental map preservation in dynamic graphs. IEEE Transactions on Visualization and Computer Graphics, 17(4):539- 552.
  2. Beck, F., Burch, M., and Diehl, S. (2009). Towards an aesthetic dimensions framework for dynamic graph visualisations. In Proceedings of International Conference on Information Visualisation (IV), pages 592-597.
  3. Beck, F., Burch, M., and Diehl, S. (2013). Matching application requirements with dynamic graph visualization profiles. In Proceedings of International Conference on Information Visualisation (IV), pages 12-18.
  4. Beck, F., Burch, M., Diehl, S., and Weiskopf, D. (2014a). The state of the art in visualizing dynamic graphs. In EuroVis State-of-the-Art Reports, EuroVis STAR.
  5. Beck, F., Burch, M., Munz, T., Silvestro, L. D., and Weiskopf, D. (2014b). Generalized Pythagoras trees for visualizing hierarchies. In Proceedings of the International Conference on Information Visualization Theory and Applications, pages 17-28.
  6. Brandes, U. and Corman, S. R. (2003). Visual unrolling of network evolution and the analysis of dynamic discourse. Information Visualization, 2(1):40-50.
  7. Brandes, U. and Nick, B. (2011). Asymmetric Relations in Longitudinal Social Networks. IEEE Transactions on Visualization and Computer Graphics, 17(12):2283- 2290.
  8. Burch, M. and Diehl, S. (2008). TimeRadarTrees: Visualizing Dynamic Compound Digraphs. Computer Graphics Forum, 27(3):823-830.
  9. Burch, M., Raschke, M., and Weiskopf, D. (2010). Indented Pixel Tree Plots. In Proceedings of the International Symposium on Advances in Visual Computing, pages 338-349.
  10. Burch, M., Schmidt, B., and Weiskopf, D. (2013). A matrixbased visualization for exploring dynamic compound digraphs. In Proceedings of International Conference on Information Visualisation (IV), pages 66-73.
  11. Burch, M., Vehlow, C., Beck, F., Diehl, S., and Weiskopf, D. (2011). Parallel edge splatting for scalable dynamic graph visualization. IEEE Transactions on Visualization and Computer Graphics, 17(12):2344-2353.
  12. Burch, M. and Weiskopf, D. (2011). Visualizing dynamic quantitative data in hierarchies - TimeEdgeTrees: Attaching dynamic weights to tree edges. In Proceedings of the International Conference on Information Visualization Theory and Applications, pages 177-186.
  13. Cornelissen, B., Holten, D., Zaidman, A., Moonen, L., van Wijk, J. J., and van Deursen, A. (2007). Understanding execution traces using massive sequence and circular bundle views. In Proceedings of International Conference on Program Comprehension, pages 49- 58.
  14. Diehl, S. and Görg, C. (2002). Graphs, they are changing. In Proceedings of Graph Drawing, pages 23-30.
  15. Frishman, Y. and Tal, A. (2007). Online dynamic graph drawing. In Proceedings of EuroVis, pages 75-82.
  16. Garey, M. R. and Johnson, D. S. (1979). Computers and Intractability: A Guide to the Theory of NPCompleteness. W. H. Freeman.
  17. Holten, D., Cornelissen, B., and van Wijk, J. J. (2007). Trace visualization using hierarchical edge bundles and massive sequence views. In Proceedings of VISSOFT, pages 47-54.
  18. Jerding, D. F. and Stasko, J. T. (1995). The information mural: a technique for displaying and navigating large information spaces. In Proceedings of INFOVIS, pages 43-50.
  19. Jerding, D. F. and Stasko, J. T. (1998). The information mural: A technique for displaying and navigating large information spaces. IEEE Transactions on Visualization and Computer Graphics, 4(3):257-271.
  20. Kruskal, J. and Landwehr, J. (1983). Icicle plots: Better displays for hierarchical clustering. American Statistician, 37(2):162-168.
  21. Purchase, H. C., Hoggan, E., and Gö rg, C. (2007). How important is the “mental map”? - An empirical investigation of a dynamic graph layout algorithm. In Proceedings of Graph Drawing, pages 184-195.
  22. Rosenholtz, R., Li, Y., and Nakano, L. (2007). Measuring visual clutter. Journal of Vision, 7(2):1-22.
  23. Shneiderman, B. (1996). The eyes have it: A task by data type taxonomy for information visualizations. In Proceedings of the IEEE Symposium on Visual Languages, pages 336-343.
  24. Stein, K., Wegener, R., and Schlieder, C. (2010). Pixeloriented visualization of change in social networks. In Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, pages 233-240.
  25. Tufte, E. R. (1992). The visual display of quantitative information. Graphics Press.
  26. van den Elzen, S., Holten, D., Blaas, J., and van Wijk, J. (2013). Reordering massive sequence views: Enabling temporal and structural analysis of dynamic networks. In Proceedings of IEEE Pacific Visualization Symposium, pages 33-40.
  27. Vehlow, C., Burch, M., Schmauder, H., and Weiskopf, D. (2013). Radial layered matrix visualization of dynamic graphs. In Proceedings of International Conference on Information Visualisation, pages 51-58.
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Paper Citation


in Harvard Style

Burch M., Munz T. and Weiskopf D. (2015). Edge-stacked Timelines for Visualizing Dynamic Weighted Digraphs . In Proceedings of the 6th International Conference on Information Visualization Theory and Applications - Volume 1: IVAPP, (VISIGRAPP 2015) ISBN 978-989-758-088-8, pages 93-100. DOI: 10.5220/0005259200930100


in Bibtex Style

@conference{ivapp15,
author={Michael Burch and Tanja Munz and Daniel Weiskopf},
title={Edge-stacked Timelines for Visualizing Dynamic Weighted Digraphs},
booktitle={Proceedings of the 6th International Conference on Information Visualization Theory and Applications - Volume 1: IVAPP, (VISIGRAPP 2015)},
year={2015},
pages={93-100},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005259200930100},
isbn={978-989-758-088-8},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Information Visualization Theory and Applications - Volume 1: IVAPP, (VISIGRAPP 2015)
TI - Edge-stacked Timelines for Visualizing Dynamic Weighted Digraphs
SN - 978-989-758-088-8
AU - Burch M.
AU - Munz T.
AU - Weiskopf D.
PY - 2015
SP - 93
EP - 100
DO - 10.5220/0005259200930100