On open access, data mining and plant conservation in the Circumpolar North with an online data example of the Herbarium, University of Alaska Museum of the North
With the advent of global online data sharing initiatives, few limits remain to using the treasure troves of museum data for biodiversity and conservation. The University of Alaska Museum Herbarium is fully online with metadata. Over 260 000 specimens representing the largest collection of Alaska pl...
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Canadian Science Publishing
2018
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Online Access: | http://dx.doi.org/10.1139/as-2016-0046 https://cdnsciencepub.com/doi/full-xml/10.1139/as-2016-0046 https://cdnsciencepub.com/doi/pdf/10.1139/as-2016-0046 |
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crcansciencepubl:10.1139/as-2016-0046 2024-09-15T17:49:57+00:00 On open access, data mining and plant conservation in the Circumpolar North with an online data example of the Herbarium, University of Alaska Museum of the North Huettmann, Falk Ickert-Bond, Stefanie M. 2018 http://dx.doi.org/10.1139/as-2016-0046 https://cdnsciencepub.com/doi/full-xml/10.1139/as-2016-0046 https://cdnsciencepub.com/doi/pdf/10.1139/as-2016-0046 en eng Canadian Science Publishing http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining Arctic Science volume 4, issue 4, page 433-470 ISSN 2368-7460 2368-7460 journal-article 2018 crcansciencepubl https://doi.org/10.1139/as-2016-0046 2024-07-18T04:13:38Z With the advent of global online data sharing initiatives, few limits remain to using the treasure troves of museum data for biodiversity and conservation. The University of Alaska Museum Herbarium is fully online with metadata. Over 260 000 specimens representing the largest collection of Alaska plants anywhere can be data mined. We found that most specimens were collected through the National Park Service’s Inventory and Monitoring program at Denali National Park and Preserve. The majority of specimens were collected along roads, trails, coastline, or waterways, while high-altitude, remote, and pristine sampling locations are underrepresented still. Actual field efforts varied over the years, peaking in the late 1980s. From 1 to 400 specimens were collected per sampling location, and on average 40 species were obtained per collection event at a unique location. Our analysis presents a first data mining inventory of such open access data allowing for a rapid assessment, quality control, and predictive modeling involving automated high-performing machine learning algorithms and mapping analysis using open geographic information systems concepts. Our research sets a first template for more investigations in the Arctic and we briefly compare with selected specimen details from adjacent landscapes such as the Russian Far East, Canada, and the Circumpolar North. Article in Journal/Newspaper Arctic Alaska Canadian Science Publishing Arctic Science 4 4 433 470 |
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Open Polar |
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Canadian Science Publishing |
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crcansciencepubl |
language |
English |
description |
With the advent of global online data sharing initiatives, few limits remain to using the treasure troves of museum data for biodiversity and conservation. The University of Alaska Museum Herbarium is fully online with metadata. Over 260 000 specimens representing the largest collection of Alaska plants anywhere can be data mined. We found that most specimens were collected through the National Park Service’s Inventory and Monitoring program at Denali National Park and Preserve. The majority of specimens were collected along roads, trails, coastline, or waterways, while high-altitude, remote, and pristine sampling locations are underrepresented still. Actual field efforts varied over the years, peaking in the late 1980s. From 1 to 400 specimens were collected per sampling location, and on average 40 species were obtained per collection event at a unique location. Our analysis presents a first data mining inventory of such open access data allowing for a rapid assessment, quality control, and predictive modeling involving automated high-performing machine learning algorithms and mapping analysis using open geographic information systems concepts. Our research sets a first template for more investigations in the Arctic and we briefly compare with selected specimen details from adjacent landscapes such as the Russian Far East, Canada, and the Circumpolar North. |
format |
Article in Journal/Newspaper |
author |
Huettmann, Falk Ickert-Bond, Stefanie M. |
spellingShingle |
Huettmann, Falk Ickert-Bond, Stefanie M. On open access, data mining and plant conservation in the Circumpolar North with an online data example of the Herbarium, University of Alaska Museum of the North |
author_facet |
Huettmann, Falk Ickert-Bond, Stefanie M. |
author_sort |
Huettmann, Falk |
title |
On open access, data mining and plant conservation in the Circumpolar North with an online data example of the Herbarium, University of Alaska Museum of the North |
title_short |
On open access, data mining and plant conservation in the Circumpolar North with an online data example of the Herbarium, University of Alaska Museum of the North |
title_full |
On open access, data mining and plant conservation in the Circumpolar North with an online data example of the Herbarium, University of Alaska Museum of the North |
title_fullStr |
On open access, data mining and plant conservation in the Circumpolar North with an online data example of the Herbarium, University of Alaska Museum of the North |
title_full_unstemmed |
On open access, data mining and plant conservation in the Circumpolar North with an online data example of the Herbarium, University of Alaska Museum of the North |
title_sort |
on open access, data mining and plant conservation in the circumpolar north with an online data example of the herbarium, university of alaska museum of the north |
publisher |
Canadian Science Publishing |
publishDate |
2018 |
url |
http://dx.doi.org/10.1139/as-2016-0046 https://cdnsciencepub.com/doi/full-xml/10.1139/as-2016-0046 https://cdnsciencepub.com/doi/pdf/10.1139/as-2016-0046 |
genre |
Arctic Alaska |
genre_facet |
Arctic Alaska |
op_source |
Arctic Science volume 4, issue 4, page 433-470 ISSN 2368-7460 2368-7460 |
op_rights |
http://www.nrcresearchpress.com/page/about/CorporateTextAndDataMining |
op_doi |
https://doi.org/10.1139/as-2016-0046 |
container_title |
Arctic Science |
container_volume |
4 |
container_issue |
4 |
container_start_page |
433 |
op_container_end_page |
470 |
_version_ |
1810291800550670336 |