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...
Saved in:
Main Authors: | , , , , , |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2016
|
Subjects: | |
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 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
id |
sg-smu-ink.sis_research-6348 |
---|---|
record_format |
dspace |
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 |
_version_ |
1770575410409504768 |