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TimeClassifier - A Visual Analytic System for the Classification of Multi-Dimensional Time-Series Data

James S. Walker, Mark Jones Orcid Logo, Robert S. Laramee, Owen R. Bidder, Hannah J. Williams, Rebecca Scott, Emily Shepard Orcid Logo, Rory Wilson Orcid Logo, Bob Laramee Orcid Logo

The Visual Computer, Volume: 31, Issue: 6-8, Pages: 1067 - 1078

Swansea University Authors: Mark Jones Orcid Logo, Emily Shepard Orcid Logo, Rory Wilson Orcid Logo, Bob Laramee Orcid Logo

DOI (Published version): 10.1007/s00371-015-1112-0

Abstract

Biologists studying animals in their natural environment are increasingly using sensors such as accelerometers in animal-attached ‘smart’ tags because it is widely acknowledged that this approach can enhance the understanding of ecological and behavioural processes. The potential of such tags is tem...

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Published in: The Visual Computer
Published: 2015
URI: https://cronfa.swan.ac.uk/Record/cronfa20645
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spelling 2019-07-17T15:23:25.8558671 v2 20645 2015-04-14 TimeClassifier - A Visual Analytic System for the Classification of Multi-Dimensional Time-Series Data 2e1030b6e14fc9debd5d5ae7cc335562 0000-0001-8991-1190 Mark Jones Mark Jones true false 54729295145aa1ea56d176818d51ed6a 0000-0001-7325-6398 Emily Shepard Emily Shepard true false 017bc6dd155098860945dc6249c4e9bc 0000-0003-3177-0177 Rory Wilson Rory Wilson true false 7737f06e2186278a925f6119c48db8b1 0000-0002-3874-6145 Bob Laramee Bob Laramee true false 2015-04-14 SCS Biologists studying animals in their natural environment are increasingly using sensors such as accelerometers in animal-attached ‘smart’ tags because it is widely acknowledged that this approach can enhance the understanding of ecological and behavioural processes. The potential of such tags is tempered by the difficulty of extracting animal behaviour from the sensors which is currently primarily dependent on the manual inspection of multiple time-series graphs. This is time-consuming and error-prone for the domain expert and is now the limiting factor for realising the value of tags in this area. We introduce TimeClassifier, a visual analytic system for the classification of time-series data for movement ecologists. We deploy our system with biologists and report two real-world case studies of its use. Journal Article The Visual Computer 31 6-8 1067 1078 14 5 2015 2015-05-14 10.1007/s00371-015-1112-0 COLLEGE NANME Computer Science COLLEGE CODE SCS Swansea University 2019-07-17T15:23:25.8558671 2015-04-14T09:25:34.0373827 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science James S. Walker 1 Mark Jones 0000-0001-8991-1190 2 Robert S. Laramee 3 Owen R. Bidder 4 Hannah J. Williams 5 Rebecca Scott 6 Emily Shepard 0000-0001-7325-6398 7 Rory Wilson 0000-0003-3177-0177 8 Bob Laramee 0000-0002-3874-6145 9 0020645-15042015115814.pdf TimeClassifier.pdf 2015-04-15T11:58:14.9330000 Output 396578 application/pdf Accepted Manuscript true 2016-04-14T00:00:00.0000000 false
title TimeClassifier - A Visual Analytic System for the Classification of Multi-Dimensional Time-Series Data
spellingShingle TimeClassifier - A Visual Analytic System for the Classification of Multi-Dimensional Time-Series Data
Mark Jones
Emily Shepard
Rory Wilson
Bob Laramee
title_short TimeClassifier - A Visual Analytic System for the Classification of Multi-Dimensional Time-Series Data
title_full TimeClassifier - A Visual Analytic System for the Classification of Multi-Dimensional Time-Series Data
title_fullStr TimeClassifier - A Visual Analytic System for the Classification of Multi-Dimensional Time-Series Data
title_full_unstemmed TimeClassifier - A Visual Analytic System for the Classification of Multi-Dimensional Time-Series Data
title_sort TimeClassifier - A Visual Analytic System for the Classification of Multi-Dimensional Time-Series Data
author_id_str_mv 2e1030b6e14fc9debd5d5ae7cc335562
54729295145aa1ea56d176818d51ed6a
017bc6dd155098860945dc6249c4e9bc
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author_id_fullname_str_mv 2e1030b6e14fc9debd5d5ae7cc335562_***_Mark Jones
54729295145aa1ea56d176818d51ed6a_***_Emily Shepard
017bc6dd155098860945dc6249c4e9bc_***_Rory Wilson
7737f06e2186278a925f6119c48db8b1_***_Bob Laramee
author Mark Jones
Emily Shepard
Rory Wilson
Bob Laramee
author2 James S. Walker
Mark Jones
Robert S. Laramee
Owen R. Bidder
Hannah J. Williams
Rebecca Scott
Emily Shepard
Rory Wilson
Bob Laramee
format Journal article
container_title The Visual Computer
container_volume 31
container_issue 6-8
container_start_page 1067
publishDate 2015
institution Swansea University
doi_str_mv 10.1007/s00371-015-1112-0
college_str Faculty of Science and Engineering
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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
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description Biologists studying animals in their natural environment are increasingly using sensors such as accelerometers in animal-attached ‘smart’ tags because it is widely acknowledged that this approach can enhance the understanding of ecological and behavioural processes. The potential of such tags is tempered by the difficulty of extracting animal behaviour from the sensors which is currently primarily dependent on the manual inspection of multiple time-series graphs. This is time-consuming and error-prone for the domain expert and is now the limiting factor for realising the value of tags in this area. We introduce TimeClassifier, a visual analytic system for the classification of time-series data for movement ecologists. We deploy our system with biologists and report two real-world case studies of its use.
published_date 2015-05-14T03:24:27Z
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