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Smart Brushing for Parallel Coordinates

Richard C. Roberts, Bob Laramee Orcid Logo, Gary A. Smith, Paul Brookes, Tony D'Cruze

IEEE Transactions on Visualization and Computer Graphics, Volume: 25, Issue: 3, Pages: 1575 - 1590

Swansea University Author: Bob Laramee Orcid Logo

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DOI (Published version): 10.1109/tvcg.2018.2808969

Abstract

The Parallel Coordinates plot is a popular tool for the visualization of high-dimensional data. One of the main challenges whenusing parallel coordinates is occlusion and overplotting resulting from large data sets. Brushing is a popular approach to address thesechallenges. Since its conception, lim...

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Published in: IEEE Transactions on Visualization and Computer Graphics
ISSN: 1077-2626 2160-9306
Published: Institute of Electrical and Electronics Engineers (IEEE) 2019
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URI: https://cronfa.swan.ac.uk/Record/cronfa38785
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first_indexed 2018-02-20T13:25:56Z
last_indexed 2020-07-27T18:58:54Z
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spelling 2020-07-27T16:26:49.3487739 v2 38785 2018-02-20 Smart Brushing for Parallel Coordinates 7737f06e2186278a925f6119c48db8b1 0000-0002-3874-6145 Bob Laramee Bob Laramee true false 2018-02-20 SCS The Parallel Coordinates plot is a popular tool for the visualization of high-dimensional data. One of the main challenges whenusing parallel coordinates is occlusion and overplotting resulting from large data sets. Brushing is a popular approach to address thesechallenges. Since its conception, limited improvements have been made to brushing both in the form of visual design and functionalinteraction. We present a set of novel, smart brushing techniques that enhance the standard interactive brushing of a parallel coordinatesplot. We introduce two new interaction concepts: Higher-order, sketch-based brushing, and smart, data-driven brushing. Higher-orderbrushes support interactive, flexible, n-dimensional pattern searches involving an arbitrary number of dimensions. Smart, data-drivenbrushing provides interactive, real-time guidance to the user during the brushing process based on derived meta-data. In addition, weimplement a selection of novel enhancements and user options that complement the two techniques as well as enhance the explorationand analytical ability of the user. We demonstrate the utility and evaluate the results using a case study with a large, high-dimensional,real-world telecommunication data set and we report domain expert feedback from the data suppliers. Journal Article IEEE Transactions on Visualization and Computer Graphics 25 3 1575 1590 Institute of Electrical and Electronics Engineers (IEEE) 1077-2626 2160-9306 information visualization, visual analytics, parallel coordinates 1 3 2019 2019-03-01 10.1109/tvcg.2018.2808969 This research paper features co-authors from industry. COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2020-07-27T16:26:49.3487739 2018-02-20T10:28:32.8941959 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Richard C. Roberts 1 Bob Laramee 0000-0002-3874-6145 2 Gary A. Smith 3 Paul Brookes 4 Tony D'Cruze 5 0038785-21032018143802.pdf 38785.pdf 2018-03-21T14:38:02.5600000 Output 26008353 application/pdf Accepted Manuscript true 2019-02-27T00:00:00.0000000 true eng
title Smart Brushing for Parallel Coordinates
spellingShingle Smart Brushing for Parallel Coordinates
Bob Laramee
title_short Smart Brushing for Parallel Coordinates
title_full Smart Brushing for Parallel Coordinates
title_fullStr Smart Brushing for Parallel Coordinates
title_full_unstemmed Smart Brushing for Parallel Coordinates
title_sort Smart Brushing for Parallel Coordinates
author_id_str_mv 7737f06e2186278a925f6119c48db8b1
author_id_fullname_str_mv 7737f06e2186278a925f6119c48db8b1_***_Bob Laramee
author Bob Laramee
author2 Richard C. Roberts
Bob Laramee
Gary A. Smith
Paul Brookes
Tony D'Cruze
format Journal article
container_title IEEE Transactions on Visualization and Computer Graphics
container_volume 25
container_issue 3
container_start_page 1575
publishDate 2019
institution Swansea University
issn 1077-2626
2160-9306
doi_str_mv 10.1109/tvcg.2018.2808969
publisher Institute of Electrical and Electronics Engineers (IEEE)
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 The Parallel Coordinates plot is a popular tool for the visualization of high-dimensional data. One of the main challenges whenusing parallel coordinates is occlusion and overplotting resulting from large data sets. Brushing is a popular approach to address thesechallenges. Since its conception, limited improvements have been made to brushing both in the form of visual design and functionalinteraction. We present a set of novel, smart brushing techniques that enhance the standard interactive brushing of a parallel coordinatesplot. We introduce two new interaction concepts: Higher-order, sketch-based brushing, and smart, data-driven brushing. Higher-orderbrushes support interactive, flexible, n-dimensional pattern searches involving an arbitrary number of dimensions. Smart, data-drivenbrushing provides interactive, real-time guidance to the user during the brushing process based on derived meta-data. In addition, weimplement a selection of novel enhancements and user options that complement the two techniques as well as enhance the explorationand analytical ability of the user. We demonstrate the utility and evaluate the results using a case study with a large, high-dimensional,real-world telecommunication data set and we report domain expert feedback from the data suppliers.
published_date 2019-03-01T03:49:10Z
_version_ 1763752385653506048
score 11.013148

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