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AmbiguityVis: Visualization of Ambiguity in Graph Layouts

Yong Wang, Qiaomu Shen, Daniel Archambault Orcid Logo, Zhiguang Zhou, Min Zhu, Sixiao Yang, Huamin Qu

IEEE Transactions on Visualization and Computer Graphics (InfoVis 2015), Volume: 22, Issue: 1, Pages: 359 - 368

Swansea University Author: Daniel Archambault Orcid Logo

DOI (Published version): 10.1109/TVCG.2015.2467691

Abstract

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

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Published in: IEEE Transactions on Visualization and Computer Graphics (InfoVis 2015)
Published: 2016
URI: https://cronfa.swan.ac.uk/Record/cronfa23061
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spelling 2018-10-02T10:45:32.4703486 v2 23061 2015-09-11 AmbiguityVis: Visualization of Ambiguity in Graph Layouts 8fa6987716a22304ef04d3c3d50ef266 0000-0003-4978-8479 Daniel Archambault Daniel Archambault true false 2015-09-11 SCS Node-link diagrams provide an intuitive way to explore networks and have inspired a large number of automated graphlayout strategies that optimize aesthetic criteria. However, any particular drawing approach cannot fully satisfy all these criteriasimultaneously, producing drawings with visual ambiguities that can impede the understanding of network structure. To bring attentionto these potentially problematic areas present in the drawing, this paper presents a technique that highlights common types of visualambiguities: ambiguous spatial relationships between nodes and edges, visual overlap between community structures, and ambiguityin edge bundling and metanodes. Metrics, including newly proposed metrics for abnormal edge lengths, visual overlap in communitystructures and node/edge aggregation, are proposed to quantify areas of ambiguity in the drawing. These metrics and others arethen displayed using a heatmap-based visualization that provides visual feedback to developers of graph drawing and visualizationapproaches, allowing them to quickly identify misleading areas. The novel metrics and the heatmap-based visualization allow a userto explore ambiguities in graph layouts from multiple perspectives in order to make reasonable graph layout choices. The effectivenessof the technique is demonstrated through case studies and expert reviews. Journal Article IEEE Transactions on Visualization and Computer Graphics (InfoVis 2015) 22 1 359 368 31 1 2016 2016-01-31 10.1109/TVCG.2015.2467691 (c) 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2018-10-02T10:45:32.4703486 2015-09-11T10:37:01.4348806 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Yong Wang 1 Qiaomu Shen 2 Daniel Archambault 0000-0003-4978-8479 3 Zhiguang Zhou 4 Min Zhu 5 Sixiao Yang 6 Huamin Qu 7 0023061-11092015104541.pdf ambiguityVisFinal.pdf 2015-09-11T10:45:41.5430000 Output 7181241 application/pdf Accepted Manuscript true 2015-09-11T00:00:00.0000000 This is a test note - please ignore. true
title AmbiguityVis: Visualization of Ambiguity in Graph Layouts
spellingShingle AmbiguityVis: Visualization of Ambiguity in Graph Layouts
Daniel Archambault
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
author_id_str_mv 8fa6987716a22304ef04d3c3d50ef266
author_id_fullname_str_mv 8fa6987716a22304ef04d3c3d50ef266_***_Daniel Archambault
author Daniel Archambault
author2 Yong Wang
Qiaomu Shen
Daniel Archambault
Zhiguang Zhou
Min Zhu
Sixiao Yang
Huamin Qu
format Journal article
container_title IEEE Transactions on Visualization and Computer Graphics (InfoVis 2015)
container_volume 22
container_issue 1
container_start_page 359
publishDate 2016
institution Swansea University
doi_str_mv 10.1109/TVCG.2015.2467691
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 1
active_str 0
description Node-link diagrams provide an intuitive way to explore networks and have inspired a large number of automated graphlayout strategies that optimize aesthetic criteria. However, any particular drawing approach cannot fully satisfy all these criteriasimultaneously, producing drawings with visual ambiguities that can impede the understanding of network structure. To bring attentionto these potentially problematic areas present in the drawing, this paper presents a technique that highlights common types of visualambiguities: ambiguous spatial relationships between nodes and edges, visual overlap between community structures, and ambiguityin edge bundling and metanodes. Metrics, including newly proposed metrics for abnormal edge lengths, visual overlap in communitystructures and node/edge aggregation, are proposed to quantify areas of ambiguity in the drawing. These metrics and others arethen displayed using a heatmap-based visualization that provides visual feedback to developers of graph drawing and visualizationapproaches, allowing them to quickly identify misleading areas. The novel metrics and the heatmap-based visualization allow a userto explore ambiguities in graph layouts from multiple perspectives in order to make reasonable graph layout choices. The effectivenessof the technique is demonstrated through case studies and expert reviews.
published_date 2016-01-31T03:27:22Z
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score 11.035874

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