Scalability considerations for multivariate graph visualization

Jankun-Kelly, T. J., Dwyer, Tim, Holten, Danny, Hurter, Christophe, Nollenburg, Martin, Weaver, Chris and Xu, Kai ORCID: (2014) Scalability considerations for multivariate graph visualization. In: Multivariate Network Visualization: Dagstuhl Seminar # 13201, Dagstuhl Castle, Germany, May 12-17, 2013, Revised Discussions. Kerren, Andreas, Purchase, Helen and Ward, Matthew O., eds. Lecture Notes in Computer Science, 8380 . Springer International Publishing, pp. 207-235. . [Book Section] (doi:10.1007/978-3-319-06793-3_10)

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Real-world, multivariate datasets are frequently too large to show in their entirety on a visual display. Still, there are many techniques we can employ to show useful partial views-sufficient to support incremental exploration of large graph datasets. In this chapter, we first explore the cognitive and architectural limitations which restrict the amount of visual bandwidth available to multivariate graph visualization approaches. These limitations afford several design approaches, which we systematically explore. Finally, we survey systems and studies that exhibit these design strategies to mitigate these perceptual and architectural limitations.

Item Type: Book Section
Keywords (uncontrolled): Algorithm Analysis and Problem Complexity, Computer Applications, Data Mining and Knowledge Discovery, Discrete Mathematics in Computer Science, Information Systems and Communication Service
Research Areas: A. > School of Science and Technology > Computer Science
Item ID: 15818
Notes on copyright: The final authenticated version is available online at
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Depositing User: Kai Xu
Date Deposited: 07 May 2015 14:55
Last Modified: 13 Feb 2021 02:23

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