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TimeNotes: A Study on Effective Chart Visualization and Interaction Techniques for Time-Series Data

James Walker, Rita Borgo Orcid Logo, Mark Jones Orcid Logo

IEEE Transactions on Visualization and Computer Graphics, Volume: 22, Issue: 1, Pages: 549 - 558

Swansea University Authors: Rita Borgo Orcid Logo, Mark Jones Orcid Logo

DOI (Published version): 10.1109/TVCG.2015.2467751

Abstract

Collecting sensor data results in large temporal data sets which need to be visualized, analysed, and presented. One dimensional time-series charts are used, but these present problems when screen resolution is small in comparison to the data. This can result in severe over-plotting, giving rise for...

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Published in: IEEE Transactions on Visualization and Computer Graphics
Published: 2015
Online Access: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7192735&tag=1
URI: https://cronfa.swan.ac.uk/Record/cronfa23067
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spelling 2023-01-30T15:42:32.4884591 v2 23067 2015-09-11 TimeNotes: A Study on Effective Chart Visualization and Interaction Techniques for Time-Series Data c4675d4072e4b2b3921ae57666f1d9ff 0000-0003-2875-6793 Rita Borgo Rita Borgo true false 2e1030b6e14fc9debd5d5ae7cc335562 0000-0001-8991-1190 Mark Jones Mark Jones true false 2015-09-11 SCS Collecting sensor data results in large temporal data sets which need to be visualized, analysed, and presented. One dimensional time-series charts are used, but these present problems when screen resolution is small in comparison to the data. This can result in severe over-plotting, giving rise for the requirement to provide effective rendering and methods to allow interaction with the detailed data. Common solutions can be categorized as multi-scale representations, frequency based, and lens based interaction techniques. In this paper, we comparatively evaluate existing methods, such as Stack Zoom [15] and ChronoLenses [39], giving a graphical overview of each and classifying their ability to explore and interact with data. We propose new visualizations and other extensions to the existing approaches. We undertake and report an empirical study and a field study using these techniques. Journal Article IEEE Transactions on Visualization and Computer Graphics 22 1 549 558 12 8 2015 2015-08-12 10.1109/TVCG.2015.2467751 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7192735&amp;tag=1 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2023-01-30T15:42:32.4884591 2015-09-11T19:49:52.6472496 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science James Walker 1 Rita Borgo 0000-0003-2875-6793 2 Mark Jones 0000-0001-8991-1190 3 0023067-11092015195255.pdf 2015_TimeNotes.pdf 2015-09-11T19:52:55.3400000 Output 5996319 application/pdf Accepted Manuscript true 2016-09-01T00:00:00.0000000 false
title TimeNotes: A Study on Effective Chart Visualization and Interaction Techniques for Time-Series Data
spellingShingle TimeNotes: A Study on Effective Chart Visualization and Interaction Techniques for Time-Series Data
Rita Borgo
Mark Jones
title_short TimeNotes: A Study on Effective Chart Visualization and Interaction Techniques for Time-Series Data
title_full TimeNotes: A Study on Effective Chart Visualization and Interaction Techniques for Time-Series Data
title_fullStr TimeNotes: A Study on Effective Chart Visualization and Interaction Techniques for Time-Series Data
title_full_unstemmed TimeNotes: A Study on Effective Chart Visualization and Interaction Techniques for Time-Series Data
title_sort TimeNotes: A Study on Effective Chart Visualization and Interaction Techniques for Time-Series Data
author_id_str_mv c4675d4072e4b2b3921ae57666f1d9ff
2e1030b6e14fc9debd5d5ae7cc335562
author_id_fullname_str_mv c4675d4072e4b2b3921ae57666f1d9ff_***_Rita Borgo
2e1030b6e14fc9debd5d5ae7cc335562_***_Mark Jones
author Rita Borgo
Mark Jones
author2 James Walker
Rita Borgo
Mark Jones
format Journal article
container_title IEEE Transactions on Visualization and Computer Graphics
container_volume 22
container_issue 1
container_start_page 549
publishDate 2015
institution Swansea University
doi_str_mv 10.1109/TVCG.2015.2467751
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
url http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7192735&amp;tag=1
document_store_str 1
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description Collecting sensor data results in large temporal data sets which need to be visualized, analysed, and presented. One dimensional time-series charts are used, but these present problems when screen resolution is small in comparison to the data. This can result in severe over-plotting, giving rise for the requirement to provide effective rendering and methods to allow interaction with the detailed data. Common solutions can be categorized as multi-scale representations, frequency based, and lens based interaction techniques. In this paper, we comparatively evaluate existing methods, such as Stack Zoom [15] and ChronoLenses [39], giving a graphical overview of each and classifying their ability to explore and interact with data. We propose new visualizations and other extensions to the existing approaches. We undertake and report an empirical study and a field study using these techniques.
published_date 2015-08-12T03:27:22Z
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score 11.016235

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