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Issue No.06 - November/December (2009 vol.15)
pp: 1009-1016
Gerald Penn , University of Toronto
Christopher Collins , University of Toronto
ABSTRACT
While many data sets contain multiple relationships, depicting more than one data relationship within a single visualization is challenging. We introduce Bubble Sets as a visualization technique for data that has both a primary data relation with a semantically significant spatial organization and a significant set membership relation in which members of the same set are not necessarily adjacent in the primary layout. In order to maintain the spatial rights of the primary data relation, we avoid layout adjustment techniques that improve set cluster continuity and density. Instead, we use a continuous, possibly concave, isocontour to delineate set membership, without disrupting the primary layout. Optimizations minimize cluster overlap and provide for calculation of the isocontours at interactive speeds. Case studies show how this technique can be used to indicate multiple sets on a variety of common visualizations.
INDEX TERMS
clustering, spatial layout, graph visualization, tree visualization
CITATION
Gerald Penn, Christopher Collins, "Bubble Sets: Revealing Set Relations with Isocontours over Existing Visualizations", IEEE Transactions on Visualization & Computer Graphics, vol.15, no. 6, pp. 1009-1016, November/December 2009, doi:10.1109/TVCG.2009.122
REFERENCES
[1] M. Balzer, and O. Deussen, Level-of-detail visualization of clustered graph layouts. In Proc. of the Asia-Pacific Symp. on Visualization, pages 133–140, 2007.
[2] D. Bauer, P. Fastrez, and J. Hollan, Spatial tools for managing personal information collections. In Proc. of the Hawaii Int. Conf. on System Sciences(HICSS), page 104.2, 2005.
[3] J. Bertin, Semiology of Graphics: Diagrams, Networks, Maps. University of Wisconsin Press, 1983.
[4] J. F. Blinn, A generalization of albegraic surface drawing. ACM Transactions on Graphics, 1 (3): 235–256, 1982.
[5] C. Buchheim, M. Jünger, and S. Leipert, Improving walker's algortihm to run in linear time. In Proc. of the Int. Symp. on Graph Drawing, number 2528 in LNCS, pages 344–353. Springer, 2002.
[6] H. Byelas and A. Telea, Visualization of areas of interest in software architecture diagrams. In Proc. of SOFTVIS, pages 105–114. ACM, 2006.
[7] C. Collins and S. Carpendale, VisLink: Revealing relationships amongst visualizations. IEEE Transactions on Visualization and Computer Graphics (Proc. of the IEEE Conf. on Information Visualization), 13 (6), 2007.
[8] T. Dwyer, K. Marriott, F. Schreiber, P. J. Stuckley, M. Woodward, and M. Wybrow, Exploration of networks using overview+detail with constraint-based cooperative layout. IEEE Transactions on Visualization and Computer Graphics, 14 (6): 1293–1300, 2008.
[9] N. Elmqvist, P. Dragicevic, and J.-D. Fekete, Rolling the dice: Multidimensional visual exploration using scatterplot matrix navigation. IEEE Transactions on Visualization and Computer Graphics, 14 (6): 1141–1148, 2008.
[10] J.-D. Fekete, D. Wang, N. Dang, A. Aris, and C. Plaisant, Overlaying graph links on Treemaps. In Proc. of IEEE Symp. on Information Visualization, Poster Session, pages 82–83, 2003.
[11] W. Freiler, K. Matković, and H. Hauser, Interactive visual analytics of set-typed data. IEEE Transactions on Visualization and Computer Graphics (Proc. of the IEEE Conf. on Information Visualization), 14 (6): 1340–1347, 2008.
[12] J. Heer, S. K. Card, and J. A. Landay, prefuse: a toolkit for interactive information visualization. In Proc. of the SIGCHI Conf. on Human Factors in Computing Systems. ACM Press, 2005.
[13] J. Heer and danahboyd., Vizster: Visualizing online social networks. In Proc. of the IEEE Symp. on Information Visualization, 2005.
[14] C. Heine and G. Scheuermann, Manual clustering refinement using interaction with blobs. In Proc. of Eurographics/IEEE-VGTC Symp. on Visualization. The Eurographics Association, 2007.
[15] W. E. Lorensen and H. E. Cline, Marching cubes: A high resolution 3d surface construction algorithm. In Proc. of the Int. Conf. on Computer Graphics and Interactive Techniques (SIGGRAPH), pages 163–169, 1987.
[16] K. Misue, P. Eades, W. Lai, and K. Sugiyama, Layout adjustment and the mental map. J. Visual Languages and Computing, 6: 183–210, 1995.
[17] A. Perer and B. Shneiderman, Balancing systematic and flexible exploration of social networks. IEEE Transactions on Visualization and Computer Graphics, 12 (5): 693–700, 2006.
[18] D. Phan, L. Xiao, R. Yeh, P. Hanrahan, and T. Winograd, Flow map layout. In Proc. of the IEEE Symp. on Information Visualization, pages 219–224, 2005.
[19] H. Rosling, Gapminder [online]. 2009 [cited 31 March, 2009]. Available from: http://www.gapminder.org/.
[20] A. Tat, Visualizing digital communication. Master's thesis, University of Calgary, 2007.
[21] C. Ware, Information Visualization: Perception for Design. Morgan Kaufmann, 2nd edition, 2004.
[22] N. Watanabe, M. Washida, and T. Igarashi, Bubble clusters: An interface for manipulating spatial aggregation of graphical objects. In Proc. of ACM Symp. on User Interface Software and Technology. ACM, Oct. 2007.
[23] M. Wybrow, K. Marriott, and P. J. Stuckey, Incremental connector routing. In P. Healy, and N. S. Nikolov editors, Proc. of the 13th Int. Symp. on Graph Drawing, volume 3843 of Lecture Notes in Computer Science, pages 446–457. Springer, 2005.
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