The Visual Computer

, Volume 31, Issue 6–8, pp 1067–1078 | Cite as

TimeClassifier: a visual analytic system for the classification of multi-dimensional time series data

  • James S. Walker
  • Mark W. Jones
  • Robert S. Laramee
  • Owen R. Bidder
  • Hannah J. Williams
  • Rebecca Scott
  • Emily L. C. Shepard
  • Rory P. Wilson
Original Article

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.

Keywords

Visual analytics Time series analysis Movement ecology 

Supplementary material

371_2015_1112_MOESM1_ESM.pdf (334 kb)
Supplementary material 1 (pdf 333 KB)

Supplementary material 2 (mp4 19528 KB)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.Department of Computer ScienceSwansea UniversitySwanseaUK
  2. 2.Swansea Lab for Animal Movement, Biosciences, College of ScienceSwansea UniversitySwanseaUK
  3. 3.The Future Ocean Cluster of ExcellenceGEOMAR|Helmholtz Center for Ocean Research KielKielGermany

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