Data

Platypus accelerometry: behavioural classification data and R code for ex situ individuals

Western Sydney University
Webb, Breony ; Ryan, Michelle ; Hunt, John ; Thomas, Jessica L.
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.26183/4qyk-rd78&rft.title=Platypus accelerometry: behavioural classification data and R code for ex situ individuals&rft.identifier=10.26183/4qyk-rd78&rft.publisher=Western Sydney University&rft.description=This dataset comprises multi-modal behavioural and accelerometry data collected from four captive platypuses (Ornithorhynchus anatinus). It includes raw tri-axial acceleration time-series data (±8 g, 50 Hz), annotated behavioural segments derived from synchronised video observations, and derived predictor variables used for behavioural classification modelling. Behavioural annotations are provided as time-aligned windows corresponding to five classes (burrow rest, surface rest, grooming, foraging, and diving), with window lengths tailored to behavioural duration. Processed datasets include raw axis accelerometer data, dynamic and statics acceleration signals for each axis at the window level, alongside model-ready datasets with summarised accelerometer variables used for machine learning analyses. Accompanying R scripts provide full reproducibility of data processing, feature extraction, and Random Forest model implementation. Video recordings used for behavioural validation are not publicly available due to sensitivity and ethical restrictions but may be accessed upon reasonable request subject to institutional approval. Metadata describing sampling protocols, sensor specifications, data structure, and variable definitions are included to facilitate reuse and interpretation.&rft.creator=Webb, Breony &rft.creator=Ryan, Michelle &rft.creator=Hunt, John &rft.creator=Thomas, Jessica L. &rft.date=2026&rft.coverage=&rft_rights=Copyright Western Sydney University&rft_rights=CC BY 4.0: Attribution 4.0 International http://creativecommons.org/licenses/by/4.0&rft_subject=accelerometry&rft_subject=platypus&rft_subject=Ornithorhynchus anatinus&rft_subject=Random Forest&rft_subject=Behavioural ecology&rft_subject=Ecology&rft_subject=BIOLOGICAL SCIENCES&rft_subject=Freshwater ecology&rft_subject=Animal behaviour&rft_subject=Zoology&rft_subject=Animal diet and nutrition&rft_subject=Animal structure and function&rft_subject=Genetics not elsewhere classified&rft_subject=Genetics&rft_subject=Genomics&rft_subject=Population ecology&rft_subject=Ecosystem function&rft_subject=Ecological applications&rft_subject=ENVIRONMENTAL SCIENCES&rft_subject=Landscape ecology&rft_subject=Environmental assessment and monitoring&rft_subject=Environmental management&rft_subject=Environmental management&rft_subject=Wildlife and habitat management&rft_subject=Expanding knowledge in the biological sciences&rft_subject=Expanding knowledge&rft_subject=EXPANDING KNOWLEDGE&rft_subject=Expanding knowledge in the environmental sciences&rft.type=dataset&rft.language=English Access the data

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CC BY 4.0: Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0

Copyright Western Sydney University

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This dataset comprises multi-modal behavioural and accelerometry data collected from four captive platypuses (Ornithorhynchus anatinus). It includes raw tri-axial acceleration time-series data (±8 g, 50 Hz), annotated behavioural segments derived from synchronised video observations, and derived predictor variables used for behavioural classification modelling. Behavioural annotations are provided as time-aligned windows corresponding to five classes (burrow rest, surface rest, grooming, foraging, and diving), with window lengths tailored to behavioural duration.

Processed datasets include raw axis accelerometer data, dynamic and statics acceleration signals for each axis at the window level, alongside model-ready datasets with summarised accelerometer variables used for machine learning analyses. Accompanying R scripts provide full reproducibility of data processing, feature extraction, and Random Forest model implementation.

Video recordings used for behavioural validation are not publicly available due to sensitivity and ethical restrictions but may be accessed upon reasonable request subject to institutional approval. Metadata describing sampling protocols, sensor specifications, data structure, and variable definitions are included to facilitate reuse and interpretation.

Created: 2026-10-26

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Identifiers
  • DOI : 10.26183/4QYK-RD78
  • Local : research-data.westernsydney.edu.au/published/6c41c1a0d0db11f1b41ff13a2eb620be
ACN 633 798 857