Dataset of seized wildlife and their intended uses

The illegal wildlife trade (IWT) threatens conservation and biosecurity efforts. The Internet has greatly facilitated the trade of wildlife, and researchers have increasingly examined the Internet to uncover illegal trade. However, most efforts to locate illegal trade on the Internet are targeted to...

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Autores principales:	Oliver C. Stringham, Stephanie Moncayo, Eilish Thomas, Sarah Heinrich, Adam Toomes, Jacob Maher, Katherine G.W. Hill, Lewis Mitchell, Joshua V. Ross, Chris R. Shepherd, Phillip Cassey
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	CITES Dark web Illegal wildlife trade Internet LEMIS Social media Computer applications to medicine. Medical informatics R858-859.7 Science (General) Q1-390
Acceso en línea:	https://doaj.org/article/6f2801a24e7c4412bc73d0b4bf1ed7c6
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spelling	oai:doaj.org-article:6f2801a24e7c4412bc73d0b4bf1ed7c62021-11-04T04:32:36ZDataset of seized wildlife and their intended uses2352-340910.1016/j.dib.2021.107531https://doaj.org/article/6f2801a24e7c4412bc73d0b4bf1ed7c62021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2352340921008076https://doaj.org/toc/2352-3409The illegal wildlife trade (IWT) threatens conservation and biosecurity efforts. The Internet has greatly facilitated the trade of wildlife, and researchers have increasingly examined the Internet to uncover illegal trade. However, most efforts to locate illegal trade on the Internet are targeted to one or few taxa or products. Large-scale efforts to find illegal wildlife on the Internet (e-commerce, social media, dark web) may be facilitated by a systematic compilation of illegally traded wildlife taxa and their uses. Here, we provide such a dataset. We used seizure records from three global wildlife trade databases to compile the identity of seized taxa along with their intended usage (i.e., use-type). Our dataset includes c. 4.9k distinct taxa representing c. 3.3k species and contains c. 11k taxa-use combinations from 110 unique use-types. Further, we acquired over 45k common names for seized taxa from over 100 languages. Our dataset can be used to conduct large-scale broad searches of the Internet to find illegally traded wildlife. Further, our dataset can be filtered for more targeted searches of specific taxa or derived products.Oliver C. StringhamStephanie MoncayoEilish ThomasSarah HeinrichAdam ToomesJacob MaherKatherine G.W. HillLewis MitchellJoshua V. RossChris R. ShepherdPhillip CasseyElsevierarticleCITESDark webIllegal wildlife tradeInternetLEMISSocial mediaComputer applications to medicine. Medical informaticsR858-859.7Science (General)Q1-390ENData in Brief, Vol 39, Iss , Pp 107531- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	CITES Dark web Illegal wildlife trade Internet LEMIS Social media Computer applications to medicine. Medical informatics R858-859.7 Science (General) Q1-390
spellingShingle	CITES Dark web Illegal wildlife trade Internet LEMIS Social media Computer applications to medicine. Medical informatics R858-859.7 Science (General) Q1-390 Oliver C. Stringham Stephanie Moncayo Eilish Thomas Sarah Heinrich Adam Toomes Jacob Maher Katherine G.W. Hill Lewis Mitchell Joshua V. Ross Chris R. Shepherd Phillip Cassey Dataset of seized wildlife and their intended uses
description	The illegal wildlife trade (IWT) threatens conservation and biosecurity efforts. The Internet has greatly facilitated the trade of wildlife, and researchers have increasingly examined the Internet to uncover illegal trade. However, most efforts to locate illegal trade on the Internet are targeted to one or few taxa or products. Large-scale efforts to find illegal wildlife on the Internet (e-commerce, social media, dark web) may be facilitated by a systematic compilation of illegally traded wildlife taxa and their uses. Here, we provide such a dataset. We used seizure records from three global wildlife trade databases to compile the identity of seized taxa along with their intended usage (i.e., use-type). Our dataset includes c. 4.9k distinct taxa representing c. 3.3k species and contains c. 11k taxa-use combinations from 110 unique use-types. Further, we acquired over 45k common names for seized taxa from over 100 languages. Our dataset can be used to conduct large-scale broad searches of the Internet to find illegally traded wildlife. Further, our dataset can be filtered for more targeted searches of specific taxa or derived products.
format	article
author	Oliver C. Stringham Stephanie Moncayo Eilish Thomas Sarah Heinrich Adam Toomes Jacob Maher Katherine G.W. Hill Lewis Mitchell Joshua V. Ross Chris R. Shepherd Phillip Cassey
author_facet	Oliver C. Stringham Stephanie Moncayo Eilish Thomas Sarah Heinrich Adam Toomes Jacob Maher Katherine G.W. Hill Lewis Mitchell Joshua V. Ross Chris R. Shepherd Phillip Cassey
author_sort	Oliver C. Stringham
title	Dataset of seized wildlife and their intended uses
title_short	Dataset of seized wildlife and their intended uses
title_full	Dataset of seized wildlife and their intended uses
title_fullStr	Dataset of seized wildlife and their intended uses
title_full_unstemmed	Dataset of seized wildlife and their intended uses
title_sort	dataset of seized wildlife and their intended uses
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/6f2801a24e7c4412bc73d0b4bf1ed7c6
work_keys_str_mv	AT olivercstringham datasetofseizedwildlifeandtheirintendeduses AT stephaniemoncayo datasetofseizedwildlifeandtheirintendeduses AT eilishthomas datasetofseizedwildlifeandtheirintendeduses AT sarahheinrich datasetofseizedwildlifeandtheirintendeduses AT adamtoomes datasetofseizedwildlifeandtheirintendeduses AT jacobmaher datasetofseizedwildlifeandtheirintendeduses AT katherinegwhill datasetofseizedwildlifeandtheirintendeduses AT lewismitchell datasetofseizedwildlifeandtheirintendeduses AT joshuavross datasetofseizedwildlifeandtheirintendeduses AT chrisrshepherd datasetofseizedwildlifeandtheirintendeduses AT phillipcassey datasetofseizedwildlifeandtheirintendeduses
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Dataset of seized wildlife and their intended uses

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