Jones, FM;
Allen, C;
Arteta, C;
Arthur, J;
Black, C;
Emmerson, LM;
Freeman, R;
... Hart, T; + view all
(2018)
Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project.
Scientific Data
, 5
, Article 180124. 10.1038/sdata.2018.124.
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Abstract
Automated time-lapse cameras can facilitate reliable and consistent monitoring of wild animal populations. In this report, data from 73,802 images taken by 15 different Penguin Watch cameras are presented, capturing the dynamics of penguin (Spheniscidae; Pygoscelis spp.) breeding colonies across the Antarctic Peninsula, South Shetland Islands and South Georgia (03/2012 to 01/2014). Citizen science provides a means by which large and otherwise intractable photographic data sets can be processed, and here we describe the methodology associated with the Zooniverse project Penguin Watch, and provide validation of the method. We present anonymised volunteer classifications for the 73,802 images, alongside the associated metadata (including date/time and temperature information). In addition to the benefits for ecological monitoring, such as easy detection of animal attendance patterns, this type of annotated time-lapse imagery can be employed as a training tool for machine learning algorithms to automate data extraction, and we encourage the use of this data set for computer vision development.
| Type: | Article |
|---|---|
| Title: | Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1038/sdata.2018.124 |
| Publisher version: | http://doi.org/10.1038/sdata.2018.124 |
| Language: | English |
| Additional information: | Copyright © The Author(s) 2018, Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons. org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/ zero/1.0/ applies to the metadata files made available in this article. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > Div of Biosciences > Genetics, Evolution and Environment |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10075147 |
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