ABSTRACT
We explore the relative merits of matrix, node-link and combined side-by-side views for the visualisation of weighted networks with three controlled studies: (1) finding the most effective visual encoding for weighted edges in matrix representations; (2) comparing matrix, node-link and combined views for static weighted networks; and (3) comparing MatrixWave, Sankey and combined views of both for event-sequence data. Our studies underline that node-link and matrix views are suited to different analysis tasks. For the combined view, our studies show that there is a perceptually complementary effect in terms of improved accuracy for some tasks, but that there is a cost in terms of longer completion time than the faster of the two techniques alone. Eye-movement data shows that for many tasks participants strongly favour one of the two views, after trying both in the training phase.
Supplemental Material
- Basak Alper, Benjamin Bach, Nathalie Henry Riche, Tobias Isenberg, and Jean-Daniel Fekete. 2013. Weighted graph comparison techniques for brain connectivity analysis. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems (CHI). ACM, 483--492. Google ScholarDigital Library
- Albert-László Barabási and Réka Albert. 1999. Emergence of scaling in random networks. Science 286, 5439 (1999), 509--512. Google ScholarCross Ref
- Jacques Bertin. 1973. Sémiologie graphique: Les diagrammes-Les réseaux-Les cartes. (1973).Google Scholar
- Anastasia Bezerianos, Pierre Dragicevic, Jean-Daniel Fekete, Juhee Bae, and Ben Watson. 2010. Geneaquilts: A system for exploring large genealogies. IEEE Transactions on Visualization and Computer Graphics 16, 6 (2010), 1073--1081.Google ScholarDigital Library
- Michael Bostock. 2012. D3. js. Data Driven Documents (2012).Google Scholar
- Stuart K Card, Jock D Mackinlay, and Ben Shneiderman. 1999. Readings in information visualization: using vision to think. (1999).Google Scholar
- Christopher Collins and Sheelagh Carpendale. 2007. VisLink: Revealing relationships amongst visualizations. IEEE Transactions on Visualization and Computer Graphics 13, 6 (2007), 1192--1199. Google ScholarDigital Library
- Antoine de Falguerolles, Felix Friedrich, Günther Sawitzki, and StatLab Heidelberg. 1997. A tribute to J. Bertin's graphical data analysis. SoftStat 97 (1997), 11--20.Google Scholar
- Tim Dwyer. 2016. Constraint-Based Layout in the Browser: WebCoLa. http://marvl.infotech.monash.edu/webcola/. (2016). Accessed: 2016-08-08.Google Scholar
- Mohammad Ghoniem, J-D Fekete, and Philippe Castagliola. 2004. A comparison of the readability of graphs using node-link and matrix-based representations. In Proceedings of IEEE Symposium on Information Visualization, 2004 (InfoVis). IEEE, 17--24.Google ScholarDigital Library
- Nathalie Henry and Jean-Daniel Fekete. 2006. MatrixExplorer: a dual-representation system to explore social networks. IEEE Transactions on Visualization and Computer Graphics 12, 5 (2006), 677--684. Google ScholarDigital Library
- Nathalie Henry and Jean-Daniel Fekete. 2007. Matlink: Enhanced matrix visualization for analyzing social networks. In IFIP Conference on Human-Computer Interaction. Springer, 288--302. Google ScholarCross Ref
- Nathalie Henry, Jean-Daniel Fekete, and Michael J McGuffin. 2007. NodeTrix: a hybrid visualization of social networks. IEEE transactions on visualization and computer graphics 13, 6 (2007), 1302--1309. Google ScholarDigital Library
- René Keller, Claudia M Eckert, and P John Clarkson. 2006. Matrices or node-link diagrams: which visual representation is better for visualising connectivity models' Information Visualization 5, 1 (2006), 62--76. Google ScholarDigital Library
- Miguel Nacenta, Uta Hinrichs, and Sheelagh Carpendale. 2012. FatFonts: combining the symbolic and visual aspects of numbers. In Proceedings of the International Working Conference on Advanced Visual Interfaces. ACM, 407--414. Google ScholarDigital Library
- Chris North and Ben Shneiderman. 1997. A taxonomy of multiple window coordination. (1997).Google Scholar
- Lucy Nowell, Robert Schulman, and Deborah Hix. 2002. Graphical encoding for information visualization: an empirical study. In Information Visualization, 2002. INFOVIS 2002. IEEE Symposium on. IEEE, 43--50. Google ScholarCross Ref
- Charles Perin, Pierre Dragicevic, and Jean-Daniel Fekete. 2014. Revisiting bertin matrices: New interactions for crafting tabular visualizations. IEEE transactions on visualization and computer graphics 20, 12 (2014), 2082--2091. Google ScholarCross Ref
- Patrick Riehmann, Manfred Hanfler, and Bernd Froehlich. 2005. Interactive sankey diagrams. In Proceedings of IEEE Symposium on Information Visualization, 2005. (InfoVis). IEEE, 233--240. Google ScholarCross Ref
- Jonathan C Roberts. 2007. State of the art: Coordinated & multiple views in exploratory visualization. In Proceedings of International Conference on Coordinated and Multiple Views in Exploratory Visualization, 2007. IEEE, 61--71.Google ScholarDigital Library
- Stanley S Stevens. 1971. Issues in psychophysical measurement. Psychological review 78, 5 (1971), 426.Google Scholar
- Matthew Tobiasz, Petra Isenberg, and Sheelagh Carpendale. 2009. Lark: Coordinating co-located collaboration with information visualization. IEEE transactions on visualization and computer graphics 15, 6 (2009), 1065--1072. Google ScholarDigital Library
- Michelle Q. Wang Baldonado, Allison Woodruff, and Allan Kuchinsky. 2000. Guidelines for Using Multiple Views in Information Visualization. In Proceedings of the Working Conference on Advanced Visual Interfaces (AVI '00). ACM, NY, NY, USA, 110--119. DOI: http://dx.doi.org/10.1145/345513.345271 Google ScholarDigital Library
- Krist Wongsuphasawat and David Gotz. 2012. Exploring flow, factors, and outcomes of temporal event sequences with the outflow visualization. IEEE Transactions on Visualization and Computer Graphics 18, 12 (2012), 2659--2668. Google ScholarDigital Library
- Jiaje Zhang and Donald A Norman. 1994. Representations in distributed cognitive tasks. Cognitive science 18, 1 (1994), 87--122. Google ScholarCross Ref
- Jian Zhao, Zhicheng Liu, Mira Dontcheva, Aaron Hertzmann, and Alan Wilson. 2015. MatrixWave: Visual comparison of event sequence data. In Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems. ACM, 259--268. Google ScholarDigital Library
Index Terms
- Evaluating Perceptually Complementary Views for Network Exploration Tasks
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