Journal article 641 views 410 downloads
Edge-Path Bundling: A Less Ambiguous Edge Bundling Approach
IEEE Transactions on Visualization and Computer Graphics, Volume: 28, Issue: 1, Pages: 1 - 1
Swansea University Author:
Daniel Archambault
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DOI (Published version): 10.1109/tvcg.2021.3114795
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...
Published in: | IEEE Transactions on Visualization and Computer Graphics |
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ISSN: | 1077-2626 1941-0506 |
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Institute of Electrical and Electronics Engineers (IEEE)
2021
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URI: | https://cronfa.swan.ac.uk/Record/cronfa57597 |
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2022-07-25T11:50:23.6780073 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 EP/V033670/1 2022-07-25T11:50:23.6780073 2021-08-11T10:07:06.7499720 Faculty of Science and Engineering School of Mathematics and Computer 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 |
Faculty of Science and Engineering |
hierarchytype |
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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 |
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 |
2021-09-29T04:13:27Z |
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1763753913375260672 |
score |
11.021648 |