AmbiguityVis: Visualization of ambiguity in graph layouts

Node-link diagrams provide an intuitive way to explore networks and have inspired a large number of automated graph layout strategies that optimize aesthetic criteria. However, any particular drawing approach cannot fully satisfy all these criteria simultaneously, producing drawings with visual ambi...

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Main Authors: WANG, Yong, SHEN, Qiaomu, ZHOU, Zhiguang, ZHU, Min, YANG, Sixiao, QU Huamin
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Language:English
Published: Institutional Knowledge at Singapore Management University 2016
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Online Access:https://ink.library.smu.edu.sg/sis_research/5344
https://ink.library.smu.edu.sg/context/sis_research/article/6348/viewcontent/AmbiguityVis_infovis15.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-63482020-11-06T02:37:12Z AmbiguityVis: Visualization of ambiguity in graph layouts WANG, Yong SHEN, Qiaomu ZHOU, Zhiguang ZHU, Min YANG, Sixiao QU Huamin, Node-link diagrams provide an intuitive way to explore networks and have inspired a large number of automated graph layout strategies that optimize aesthetic criteria. However, any particular drawing approach cannot fully satisfy all these criteria simultaneously, producing drawings with visual ambiguities that can impede the understanding of network structure. To bring attention to these potentially problematic areas present in the drawing. this paper presents a technique that highlights common types of visual ambiguities: ambiguous spatial relationships between nodes and edges, visual overlap between community structures, and ambiguity in edge bundling and metanodes. Metrics, including newly proposed metrics for abnormal edge lengths, visual overlap in community structures and node/edge aggregation, are proposed to quantify areas of ambiguity in the drawing. These metrics and others are then displayed using a heatmap-based visualization that provides visual feedback to developers of graph drawing and visualization approaches, allowing them to quickly identify misleading areas. The novel metrics and the heatmap-based visualization allow a user to explore ambiguities in graph layouts from multiple perspectives in order to make reasonable graph layout choices. The effectiveness of the technique is demonstrated through case studies and expert reviews. 2016-01-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/5344 info:doi/10.1109/TVCG.2015.2467691 https://ink.library.smu.edu.sg/context/sis_research/article/6348/viewcontent/AmbiguityVis_infovis15.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Visual Ambiguity Visualization Node-link diagram Graph layout Graph visualization Graphics and Human Computer Interfaces Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Visual Ambiguity
Visualization
Node-link diagram
Graph layout
Graph visualization
Graphics and Human Computer Interfaces
Software Engineering
spellingShingle Visual Ambiguity
Visualization
Node-link diagram
Graph layout
Graph visualization
Graphics and Human Computer Interfaces
Software Engineering
WANG, Yong
SHEN, Qiaomu
ZHOU, Zhiguang
ZHU, Min
YANG, Sixiao
QU Huamin,
AmbiguityVis: Visualization of ambiguity in graph layouts
description Node-link diagrams provide an intuitive way to explore networks and have inspired a large number of automated graph layout strategies that optimize aesthetic criteria. However, any particular drawing approach cannot fully satisfy all these criteria simultaneously, producing drawings with visual ambiguities that can impede the understanding of network structure. To bring attention to these potentially problematic areas present in the drawing. this paper presents a technique that highlights common types of visual ambiguities: ambiguous spatial relationships between nodes and edges, visual overlap between community structures, and ambiguity in edge bundling and metanodes. Metrics, including newly proposed metrics for abnormal edge lengths, visual overlap in community structures and node/edge aggregation, are proposed to quantify areas of ambiguity in the drawing. These metrics and others are then displayed using a heatmap-based visualization that provides visual feedback to developers of graph drawing and visualization approaches, allowing them to quickly identify misleading areas. The novel metrics and the heatmap-based visualization allow a user to explore ambiguities in graph layouts from multiple perspectives in order to make reasonable graph layout choices. The effectiveness of the technique is demonstrated through case studies and expert reviews.
format text
author WANG, Yong
SHEN, Qiaomu
ZHOU, Zhiguang
ZHU, Min
YANG, Sixiao
QU Huamin,
author_facet WANG, Yong
SHEN, Qiaomu
ZHOU, Zhiguang
ZHU, Min
YANG, Sixiao
QU Huamin,
author_sort WANG, Yong
title AmbiguityVis: Visualization of ambiguity in graph layouts
title_short AmbiguityVis: Visualization of ambiguity in graph layouts
title_full AmbiguityVis: Visualization of ambiguity in graph layouts
title_fullStr AmbiguityVis: Visualization of ambiguity in graph layouts
title_full_unstemmed AmbiguityVis: Visualization of ambiguity in graph layouts
title_sort ambiguityvis: visualization of ambiguity in graph layouts
publisher Institutional Knowledge at Singapore Management University
publishDate 2016
url https://ink.library.smu.edu.sg/sis_research/5344
https://ink.library.smu.edu.sg/context/sis_research/article/6348/viewcontent/AmbiguityVis_infovis15.pdf
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