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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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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 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.
College: Faculty of Science and Engineering
Issue: 6-8
Start Page: 1067
End Page: 1078