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Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach

Markus Wallinger, Daniel Archambault Orcid Logo, David Auber, Martin Nollenburg, Jaakko Peltonen

IEEE Transactions on Visualization and Computer Graphics, Volume: 28, Issue: 1, Pages: 1 - 1

Swansea University Author: Daniel Archambault Orcid Logo

Abstract

Edge bundling techniques cluster edges with similar attributes (i.e. similarity in direction and proximity) together to reduce the visual clutter. All edge bundling techniques to date implicitly or explicitly cluster groups of individual edges, or parts of them, together based on these attributes. T...

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Published in: IEEE Transactions on Visualization and Computer Graphics
ISSN: 1077-2626 1941-0506
Published: Institute of Electrical and Electronics Engineers (IEEE) 2021
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URI: https://cronfa.swan.ac.uk/Record/cronfa57597
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spelling 2022-01-05T14:01:18.8549698 v2 57597 2021-08-11 Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach 8fa6987716a22304ef04d3c3d50ef266 0000-0003-4978-8479 Daniel Archambault Daniel Archambault true false 2021-08-11 SCS Edge bundling techniques cluster edges with similar attributes (i.e. similarity in direction and proximity) together to reduce the visual clutter. All edge bundling techniques to date implicitly or explicitly cluster groups of individual edges, or parts of them, together based on these attributes. These clusters can result in ambiguous connections that do not exist in the data. Confluent drawings of networks do not have these ambiguities, but require the layout to be computed as part of the bundling process. We devise a new bundling method, Edge-Path bundling, to simplify edge clutter while greatly reducing ambiguities compared to previous bundling techniques. Edge-Path bundling takes a layout as input and clusters each edge along a weighted, shortest path to limit its deviation from a straight line. Edge-Path bundling does not incur independent edge ambiguities typically seen in all edge bundling methods, and the level of bundling can be tuned through shortest path distances, Euclidean distances, and combinations of the two. Also, directed edge bundling naturally emerges from the model. Through metric evaluations, we demonstrate the advantages of Edge-Path bundling over other techniques. Journal Article IEEE Transactions on Visualization and Computer Graphics 28 1 1 1 Institute of Electrical and Electronics Engineers (IEEE) 1077-2626 1941-0506 29 9 2021 2021-09-29 10.1109/tvcg.2021.3114795 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University UKRI EPSRC EP/V033670/1 2022-01-05T14:01:18.8549698 2021-08-11T10:07:06.7499720 College of Science Computer Science Markus Wallinger 1 Daniel Archambault 0000-0003-4978-8479 2 David Auber 3 Martin Nollenburg 4 Jaakko Peltonen 5 57597__20608__c01ed60846f344309ec68c28807d42f4.pdf EdgePathBundle.pdf 2021-08-11T10:20:21.5029249 Output 26451334 application/pdf Accepted Manuscript true 2021-10-24T00:00:00.0000000 true eng
title Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach
spellingShingle Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach
Daniel Archambault
title_short Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach
title_full Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach
title_fullStr Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach
title_full_unstemmed Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach
title_sort Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach
author_id_str_mv 8fa6987716a22304ef04d3c3d50ef266
author_id_fullname_str_mv 8fa6987716a22304ef04d3c3d50ef266_***_Daniel Archambault
author Daniel Archambault
author2 Markus Wallinger
Daniel Archambault
David Auber
Martin Nollenburg
Jaakko Peltonen
format Journal article
container_title IEEE Transactions on Visualization and Computer Graphics
container_volume 28
container_issue 1
container_start_page 1
publishDate 2021
institution Swansea University
issn 1077-2626
1941-0506
doi_str_mv 10.1109/tvcg.2021.3114795
publisher Institute of Electrical and Electronics Engineers (IEEE)
college_str College of Science
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hierarchy_top_title College of Science
hierarchy_parent_id collegeofscience
hierarchy_parent_title College of Science
department_str Computer Science{{{_:::_}}}College of Science{{{_:::_}}}Computer Science
document_store_str 1
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description Edge bundling techniques cluster edges with similar attributes (i.e. similarity in direction and proximity) together to reduce the visual clutter. All edge bundling techniques to date implicitly or explicitly cluster groups of individual edges, or parts of them, together based on these attributes. These clusters can result in ambiguous connections that do not exist in the data. Confluent drawings of networks do not have these ambiguities, but require the layout to be computed as part of the bundling process. We devise a new bundling method, Edge-Path bundling, to simplify edge clutter while greatly reducing ambiguities compared to previous bundling techniques. Edge-Path bundling takes a layout as input and clusters each edge along a weighted, shortest path to limit its deviation from a straight line. Edge-Path bundling does not incur independent edge ambiguities typically seen in all edge bundling methods, and the level of bundling can be tuned through shortest path distances, Euclidean distances, and combinations of the two. Also, directed edge bundling naturally emerges from the model. Through metric evaluations, we demonstrate the advantages of Edge-Path bundling over other techniques.
published_date 2021-09-29T04:13:49Z
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score 10.878606