Sticky Links: Encoding Quantitative Data of Graph Edges

Min Lu, Xiangfang Zeng, Joel Lanir, Xiaoqin Sun, Guozheng Li, Daniel Cohen-Or, Hui Huang*

*此作品的通讯作者

科研成果: 期刊稿件文章同行评审

摘要

Visually encoding quantitative information associated with graph links is an important problem in graph visualization. A conventional approach is to vary the thickness of lines to encode the strength of connections in node-link diagrams. In this paper, we present Sticky Links, a novel visual encoding method that draws graph links with stickiness. Taking the metaphor of links with glues, sticky links represent connection strength using spiky shapes, ranging from two broken spikes for weak connections to connected lines for strong connections. We conducted a controlled user study to compare the efficiency and aesthetic appeal of stickiness with conventional thickness encoding. Our results show that stickiness enables more effective and expressive quantitative encoding while maintaining the perception of node connectivity. Participants also found sticky links to be more aesthetic and less visually cluttering than conventional thickness encoding. Overall, our findings suggest that sticky links offer a promising alternative to conventional methods for encoding quantitative information in graphs.

源语言英语
页(从-至)2968-2980
页数13
期刊IEEE Transactions on Visualization and Computer Graphics
30
6
DOI
出版状态已出版 - 1 6月 2024

指纹

探究 'Sticky Links: Encoding Quantitative Data of Graph Edges' 的科研主题。它们共同构成独一无二的指纹。

引用此