An Information-Theoretic Framework for Evaluating Edge Bundling Visualization
Edge bundling is a promising graph visualization approach to simplifying the visual result of a graph drawing. Plenty of edge bundling methods have been developed to generate diverse graph layouts. However, it is difficult to defend an edge bundling method with its resulting layout against other edg...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2018-08-01
|
| Series: | Entropy |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1099-4300/20/9/625 |
| _version_ | 1797999130039025664 |
|---|---|
| author | Jieting Wu Feiyu Zhu Xin Liu Hongfeng Yu |
| author_facet | Jieting Wu Feiyu Zhu Xin Liu Hongfeng Yu |
| author_sort | Jieting Wu |
| collection | DOAJ |
| description | Edge bundling is a promising graph visualization approach to simplifying the visual result of a graph drawing. Plenty of edge bundling methods have been developed to generate diverse graph layouts. However, it is difficult to defend an edge bundling method with its resulting layout against other edge bundling methods as a clear theoretic evaluation framework is absent in the literature. In this paper, we propose an information-theoretic framework to evaluate the visual results of edge bundling techniques. We first illustrate the advantage of edge bundling visualizations for large graphs, and pinpoint the ambiguity resulting from drawing results. Second, we define and quantify the amount of information delivered by edge bundling visualization from the underlying network using information theory. Third, we propose a new algorithm to evaluate the resulting layouts of edge bundling using the amount of the mutual information between a raw network dataset and its edge bundling visualization. Comparison examples based on the proposed framework between different edge bundling techniques are presented. |
| first_indexed | 2024-04-11T10:59:37Z |
| format | Article |
| id | doaj.art-7083256a134e450f91867486bd16cf1a |
| institution | Directory Open Access Journal |
| issn | 1099-4300 |
| language | English |
| last_indexed | 2024-04-11T10:59:37Z |
| publishDate | 2018-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Entropy |
| spelling | doaj.art-7083256a134e450f91867486bd16cf1a2022-12-22T04:28:40ZengMDPI AGEntropy1099-43002018-08-0120962510.3390/e20090625e20090625An Information-Theoretic Framework for Evaluating Edge Bundling VisualizationJieting Wu0Feiyu Zhu1Xin Liu2Hongfeng Yu3Department of Computer Science & Engineering, University of Nebraska-Lincoln, 1400 R St, Lincoln, NE 68588, USADepartment of Computer Science & Engineering, University of Nebraska-Lincoln, 1400 R St, Lincoln, NE 68588, USADepartment of Computer Science & Engineering, University of Nebraska-Lincoln, 1400 R St, Lincoln, NE 68588, USADepartment of Computer Science & Engineering, University of Nebraska-Lincoln, 1400 R St, Lincoln, NE 68588, USAEdge bundling is a promising graph visualization approach to simplifying the visual result of a graph drawing. Plenty of edge bundling methods have been developed to generate diverse graph layouts. However, it is difficult to defend an edge bundling method with its resulting layout against other edge bundling methods as a clear theoretic evaluation framework is absent in the literature. In this paper, we propose an information-theoretic framework to evaluate the visual results of edge bundling techniques. We first illustrate the advantage of edge bundling visualizations for large graphs, and pinpoint the ambiguity resulting from drawing results. Second, we define and quantify the amount of information delivered by edge bundling visualization from the underlying network using information theory. Third, we propose a new algorithm to evaluate the resulting layouts of edge bundling using the amount of the mutual information between a raw network dataset and its edge bundling visualization. Comparison examples based on the proposed framework between different edge bundling techniques are presented.http://www.mdpi.com/1099-4300/20/9/625information visualizationgraph visualizationedge bundlinginformation theoryminimum description length |
| spellingShingle | Jieting Wu Feiyu Zhu Xin Liu Hongfeng Yu An Information-Theoretic Framework for Evaluating Edge Bundling Visualization Entropy information visualization graph visualization edge bundling information theory minimum description length |
| title | An Information-Theoretic Framework for Evaluating Edge Bundling Visualization |
| title_full | An Information-Theoretic Framework for Evaluating Edge Bundling Visualization |
| title_fullStr | An Information-Theoretic Framework for Evaluating Edge Bundling Visualization |
| title_full_unstemmed | An Information-Theoretic Framework for Evaluating Edge Bundling Visualization |
| title_short | An Information-Theoretic Framework for Evaluating Edge Bundling Visualization |
| title_sort | information theoretic framework for evaluating edge bundling visualization |
| topic | information visualization graph visualization edge bundling information theory minimum description length |
| url | http://www.mdpi.com/1099-4300/20/9/625 |
| work_keys_str_mv | AT jietingwu aninformationtheoreticframeworkforevaluatingedgebundlingvisualization AT feiyuzhu aninformationtheoreticframeworkforevaluatingedgebundlingvisualization AT xinliu aninformationtheoreticframeworkforevaluatingedgebundlingvisualization AT hongfengyu aninformationtheoreticframeworkforevaluatingedgebundlingvisualization AT jietingwu informationtheoreticframeworkforevaluatingedgebundlingvisualization AT feiyuzhu informationtheoreticframeworkforevaluatingedgebundlingvisualization AT xinliu informationtheoreticframeworkforevaluatingedgebundlingvisualization AT hongfengyu informationtheoreticframeworkforevaluatingedgebundlingvisualization |