Data from: Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project
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...
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Online Access: | http://hdl.handle.net/10255/dryad.168552 https://doi.org/10.5061/dryad.vv36g.1 |
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ftdryad:oai:v1.datadryad.org:10255/dryad.168552 2023-05-15T13:44:27+02:00 Data from: Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project Jones, Fiona M. Allen, Campbell Arteta, Carlos Arthur, Joan Black, Caitlin Emmerson, Louise M. Freeman, Robin Hines, Greg Lintott, Chris J. Macháĉková, Zuzana Miller, Grant Simpson, Rob Southwell, Colin Torsey, Holly R. Zisserman, Andrew Hart, Tom Antarctica Antarctic Peninsula Southern Ocean South Georgia Island South Shetland Islands 2018-06-21T05:18:42Z http://hdl.handle.net/10255/dryad.168552 https://doi.org/10.5061/dryad.vv36g.1 unknown doi:10.5061/dryad.vv36g.1/4.1 doi:10.5061/dryad.vv36g.1/5.1 doi:10.5061/dryad.vv36g.1/6.1 doi:10.5061/dryad.vv36g.1/7.1 doi:10.5061/dryad.vv36g.1/8.1 doi:10.5061/dryad.vv36g.1/9.1 doi:10.5061/dryad.vv36g.1/10.1 doi:10.1038/sdata.2018.124 doi:10.5061/dryad.vv36g.1 Jones FM, Allen C, Arteta C, Arthur J, Black C, Emmerson LM, Freeman R, Hines G, Lintott CJ, Macháĉková Z, Miller G, Simpson R, Southwell C, Torsey HR, Zisserman A, Hart T (2018) Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project. Scientific Data 5: 180124. http://hdl.handle.net/10255/dryad.168552 Ecological monitoring Time-lapse Citizen science Computer vision Article 2018 ftdryad https://doi.org/10.5061/dryad.vv36g.1 https://doi.org/10.5061/dryad.vv36g.1/4.1 https://doi.org/10.5061/dryad.vv36g.1/5.1 https://doi.org/10.5061/dryad.vv36g.1/6.1 https://doi.org/10.5061/dryad.vv36g.1/7.1 https://doi.org/10.5061/dryad.vv36g.1/8 2020-01-01T16:03:16Z 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. Article in Journal/Newspaper Antarc* Antarctic Antarctic Peninsula Antarctica South Georgia Island South Shetland Islands Southern Ocean Dryad Digital Repository (Duke University) Antarctic Southern Ocean The Antarctic Antarctic Peninsula South Shetland Islands South Georgia Island ENVELOPE(-36.750,-36.750,-54.250,-54.250) |
institution |
Open Polar |
collection |
Dryad Digital Repository (Duke University) |
op_collection_id |
ftdryad |
language |
unknown |
topic |
Ecological monitoring Time-lapse Citizen science Computer vision |
spellingShingle |
Ecological monitoring Time-lapse Citizen science Computer vision Jones, Fiona M. Allen, Campbell Arteta, Carlos Arthur, Joan Black, Caitlin Emmerson, Louise M. Freeman, Robin Hines, Greg Lintott, Chris J. Macháĉková, Zuzana Miller, Grant Simpson, Rob Southwell, Colin Torsey, Holly R. Zisserman, Andrew Hart, Tom Data from: Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project |
topic_facet |
Ecological monitoring Time-lapse Citizen science Computer vision |
description |
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. |
format |
Article in Journal/Newspaper |
author |
Jones, Fiona M. Allen, Campbell Arteta, Carlos Arthur, Joan Black, Caitlin Emmerson, Louise M. Freeman, Robin Hines, Greg Lintott, Chris J. Macháĉková, Zuzana Miller, Grant Simpson, Rob Southwell, Colin Torsey, Holly R. Zisserman, Andrew Hart, Tom |
author_facet |
Jones, Fiona M. Allen, Campbell Arteta, Carlos Arthur, Joan Black, Caitlin Emmerson, Louise M. Freeman, Robin Hines, Greg Lintott, Chris J. Macháĉková, Zuzana Miller, Grant Simpson, Rob Southwell, Colin Torsey, Holly R. Zisserman, Andrew Hart, Tom |
author_sort |
Jones, Fiona M. |
title |
Data from: Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project |
title_short |
Data from: Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project |
title_full |
Data from: Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project |
title_fullStr |
Data from: Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project |
title_full_unstemmed |
Data from: Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project |
title_sort |
data from: time-lapse imagery and volunteer classifications from the zooniverse penguin watch project |
publishDate |
2018 |
url |
http://hdl.handle.net/10255/dryad.168552 https://doi.org/10.5061/dryad.vv36g.1 |
op_coverage |
Antarctica Antarctic Peninsula Southern Ocean South Georgia Island South Shetland Islands |
long_lat |
ENVELOPE(-36.750,-36.750,-54.250,-54.250) |
geographic |
Antarctic Southern Ocean The Antarctic Antarctic Peninsula South Shetland Islands South Georgia Island |
geographic_facet |
Antarctic Southern Ocean The Antarctic Antarctic Peninsula South Shetland Islands South Georgia Island |
genre |
Antarc* Antarctic Antarctic Peninsula Antarctica South Georgia Island South Shetland Islands Southern Ocean |
genre_facet |
Antarc* Antarctic Antarctic Peninsula Antarctica South Georgia Island South Shetland Islands Southern Ocean |
op_relation |
doi:10.5061/dryad.vv36g.1/4.1 doi:10.5061/dryad.vv36g.1/5.1 doi:10.5061/dryad.vv36g.1/6.1 doi:10.5061/dryad.vv36g.1/7.1 doi:10.5061/dryad.vv36g.1/8.1 doi:10.5061/dryad.vv36g.1/9.1 doi:10.5061/dryad.vv36g.1/10.1 doi:10.1038/sdata.2018.124 doi:10.5061/dryad.vv36g.1 Jones FM, Allen C, Arteta C, Arthur J, Black C, Emmerson LM, Freeman R, Hines G, Lintott CJ, Macháĉková Z, Miller G, Simpson R, Southwell C, Torsey HR, Zisserman A, Hart T (2018) Time-lapse imagery and volunteer classifications from the Zooniverse Penguin Watch project. Scientific Data 5: 180124. http://hdl.handle.net/10255/dryad.168552 |
op_doi |
https://doi.org/10.5061/dryad.vv36g.1 https://doi.org/10.5061/dryad.vv36g.1/4.1 https://doi.org/10.5061/dryad.vv36g.1/5.1 https://doi.org/10.5061/dryad.vv36g.1/6.1 https://doi.org/10.5061/dryad.vv36g.1/7.1 https://doi.org/10.5061/dryad.vv36g.1/8 |
_version_ |
1766201953938833408 |