Scalability considerations for multivariate graph visualization
Jankun-Kelly, T. J., Dwyer, Tim, Holten, Danny, Hurter, Christophe, Nollenburg, Martin, Weaver, Chris and Xu, Kai 
ORCID: https://orcid.org/0000-0003-2242-5440
(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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Abstract
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 https://doi.org/10.1007/978-3-319-06793-3_10 |
| Useful Links: | |
| Depositing User: | Kai Xu |
| Date Deposited: | 07 May 2015 14:55 |
| Last Modified: | 09 Jun 2022 10:01 |
| URI: | https://eprints.mdx.ac.uk/id/eprint/15818 |
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