The Community for Technology Leaders
RSS Icon
Issue No.12 - Dec. (2011 vol.17)
pp: 2268-2275
Juhee Bae , North Carolina State University
Benjamin Watson , North Carolina State University
Traditional layered graph depictions such as flow charts are in wide use. Yet as graphs grow more complex, these depictions can become difficult to understand. Quilts are matrix-based depictions for layered graphs designed to address this problem. In this research, we first improve Quilts by developing three design alternatives, and then compare the best of these alternatives to better-known node-link and matrix depictions. A primary weakness in Quilts is their depiction of skip links, links that do not simply connect to a succeeding layer. Therefore in our first study, we compare Quilts using color-only, text-only, and mixed (color and text) skip link depictions, finding that path finding with the color-only depiction is significantly slower and less accurate, and that in certain cases, the mixed depiction offers an advantage over the text-only depiction. In our second study, we compare Quilts using the mixed depiction to node-link diagrams and centered matrices. Overall results show that users can find paths through graphs significantly faster with Quilts (46.6 secs) than with node-link (58.3 secs) or matrix (71.2 secs) diagrams. This speed advantage is still greater in large graphs (e.g. in 200 node graphs, 55.4 secs vs. 71.1 secs for node-link and 84.2 secs for matrix depictions).
Graph drawing, layered graphs, matrix based depiction, node-link diagram.
Juhee Bae, Benjamin Watson, "Developing and Evaluating Quilts for the Depiction of Large Layered Graphs", IEEE Transactions on Visualization & Computer Graphics, vol.17, no. 12, pp. 2268-2275, Dec. 2011, doi:10.1109/TVCG.2011.187
[1] G. Battista, P. Eades, R. Tamassia, and I. Tollis, Graph Drawing: Algorithms for the Visualisation of Graphs. Prentice Hall, 1999.
[2] J. Bertin, Semiologie Graphique : Les diagrammes - Les reseaux - Les cartes. Editions de l'Ecole des Hautes Etudes en Sciences, Paris, France, 1967.
[3] A. Bezerianos, P. Dragicevic, J.-D. Fekete, J. Bae, and B. Watson, Ge-neaquilts: A system for exploring large genealogies. IEEE Transactions on Visualization and Computer Graphics (TVCG / InfoVis'10), 2010.
[4] F. Campbell, J. Kulikowski, and J. Levinson, The effect of orientation on the visual resolution of gratings. J. Physiol , 187: 427–436, 1966.
[5] M. Eiglsperger, M. Siebenhaller, and M. Kaufmann, An efficient implementation of sugiyama's algorithm for layered graph drawing. J. Graph, Algorithms & Apps, 9: 305–325, 2005.
[6] E. Gansner, E. Koutsofios, S. North, and K.-P. Vo, A technique for drawing directed graphs. IEEE Transactions on Software Engineering, 19: 214–230, 1993.
[7] E. Gansner and S. North, An open graph visualization system and its applications to software engineering. Software: Practice and Experience, 30: 1203–1233, 2000.
[8] M. Ghoniem, J.-D. Fekete, and P. Castagliola, A comparison of the readability of graphs using node-link and matrix-based representations. Proceedings of the IEEE Symposium on Information Visualization, pages 17– 24, 2004.
[9] N. Henry and J.-D. Fekete, Matlink: Enhanced matrix visualization. IFIP TC13 International Conference on Human-Computer Interaction (Interact 2007), 2007.
[10] N. Henry, J.-D. Fekete, and M. McGuffin, Nodetrix: a hybrid visualization. IEEE Transactions on Visualization and Computer Graphics, 2007.
[11] I. Herman, G. Melancon, and M. Marshall, Graph visualization and navigation in information visualization: A survey. IEEE Transactions on Visualization and Computer Graphics, 6: 24–43, 2003.
[12] R. Keller, T. Eger, C. Eckert, and P. Clarkson, Matrices or node-link diagrams: which visual representation is better for visualising connectivity models? Information Visualization, 2006.
[13] Z. Shen and K. Ma, Path visualization for adjacency matrices. Proceedings of Eurographics/IEEE VGTC Symposium on Visualization, 2007.
[14] M. Stallmann, F. Brglez, and D. Ghosh, Heuristics, experimental subjects and treatment evaluation in bigraph crossing minimization. ACM J. Exp, Algorithmics, 6 (8): 1–42, 2001.
[15] K. Sugiyama, S. Tagawa, and M. Toda, Methods for visual understanding of hierarchical system structures. IEEE Trans. on Systems, Man, and Cybernetics, SMC- 11 (2): 109–125, 1981.
[16] B. Watson, D. Brink, M. Stallmann, R. Devarajan, M. Rakow, T. Rhyne, and H. Patel, Visualizing very large layered graphs with quilts. Proceedings of the IEEE Information Visualization. Conference Poster, 2007.
172 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool