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Crowdsourcing the identification of organisms: A case-study of iSpot

Abstract. Accurate species identification is fundamental to biodiversity science, but the natural history skills required for this are neglected in formal education at all levels. In this paper we describe how the web application ispotnature.org and its sister site ispot.org.za (collectively, “iSpot...

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Autores principales: Silvertown, Jonathan, Harvey, Martin, Greenwood, Richard, Dodd, Mike, Rosewell, Jon, Rebelo, Tony, Ansine, Janice, McConway, Kevin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Pensoft Publishers 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4319112/
https://www.ncbi.nlm.nih.gov/pubmed/25685027
http://dx.doi.org/10.3897/zookeys.480.8803
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author Silvertown, Jonathan
Harvey, Martin
Greenwood, Richard
Dodd, Mike
Rosewell, Jon
Rebelo, Tony
Ansine, Janice
McConway, Kevin
author_facet Silvertown, Jonathan
Harvey, Martin
Greenwood, Richard
Dodd, Mike
Rosewell, Jon
Rebelo, Tony
Ansine, Janice
McConway, Kevin
author_sort Silvertown, Jonathan
collection PubMed
description Abstract. Accurate species identification is fundamental to biodiversity science, but the natural history skills required for this are neglected in formal education at all levels. In this paper we describe how the web application ispotnature.org and its sister site ispot.org.za (collectively, “iSpot”) are helping to solve this problem by combining learning technology with crowdsourcing to connect beginners with experts. Over 94% of observations submitted to iSpot receive a determination. External checking of a sample of 3,287 iSpot records verified > 92% of them. To mid 2014, iSpot crowdsourced the identification of 30,000 taxa (>80% at species level) in > 390,000 observations with a global community numbering > 42,000 registered participants. More than half the observations on ispotnature.org were named within an hour of submission. iSpot uses a unique, 9-dimensional reputation system to motivate and reward participants and to verify determinations. Taxon-specific reputation points are earned when a participant proposes an identification that achieves agreement from other participants, weighted by the agreers’ own reputation scores for the taxon. This system is able to discriminate effectively between competing determinations when two or more are proposed for the same observation. In 57% of such cases the reputation system improved the accuracy of the determination, while in the remainder it either improved precision (e.g. by adding a species name to a genus) or revealed false precision, for example where a determination to species level was not supported by the available evidence. We propose that the success of iSpot arises from the structure of its social network that efficiently connects beginners and experts, overcoming the social as well as geographic barriers that normally separate the two.
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spelling pubmed-43191122015-02-15 Crowdsourcing the identification of organisms: A case-study of iSpot Silvertown, Jonathan Harvey, Martin Greenwood, Richard Dodd, Mike Rosewell, Jon Rebelo, Tony Ansine, Janice McConway, Kevin Zookeys Research Article Abstract. Accurate species identification is fundamental to biodiversity science, but the natural history skills required for this are neglected in formal education at all levels. In this paper we describe how the web application ispotnature.org and its sister site ispot.org.za (collectively, “iSpot”) are helping to solve this problem by combining learning technology with crowdsourcing to connect beginners with experts. Over 94% of observations submitted to iSpot receive a determination. External checking of a sample of 3,287 iSpot records verified > 92% of them. To mid 2014, iSpot crowdsourced the identification of 30,000 taxa (>80% at species level) in > 390,000 observations with a global community numbering > 42,000 registered participants. More than half the observations on ispotnature.org were named within an hour of submission. iSpot uses a unique, 9-dimensional reputation system to motivate and reward participants and to verify determinations. Taxon-specific reputation points are earned when a participant proposes an identification that achieves agreement from other participants, weighted by the agreers’ own reputation scores for the taxon. This system is able to discriminate effectively between competing determinations when two or more are proposed for the same observation. In 57% of such cases the reputation system improved the accuracy of the determination, while in the remainder it either improved precision (e.g. by adding a species name to a genus) or revealed false precision, for example where a determination to species level was not supported by the available evidence. We propose that the success of iSpot arises from the structure of its social network that efficiently connects beginners and experts, overcoming the social as well as geographic barriers that normally separate the two. Pensoft Publishers 2015-02-02 /pmc/articles/PMC4319112/ /pubmed/25685027 http://dx.doi.org/10.3897/zookeys.480.8803 Text en Jonathan Silvertown, Martin Harvey, Richard Greenwood, Mike Dodd, Jon Rosewell, Tony Rebelo, Janice Ansine, Kevin McConway http://creativecommons.org/licenses/by/4.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Silvertown, Jonathan
Harvey, Martin
Greenwood, Richard
Dodd, Mike
Rosewell, Jon
Rebelo, Tony
Ansine, Janice
McConway, Kevin
Crowdsourcing the identification of organisms: A case-study of iSpot
title Crowdsourcing the identification of organisms: A case-study of iSpot
title_full Crowdsourcing the identification of organisms: A case-study of iSpot
title_fullStr Crowdsourcing the identification of organisms: A case-study of iSpot
title_full_unstemmed Crowdsourcing the identification of organisms: A case-study of iSpot
title_short Crowdsourcing the identification of organisms: A case-study of iSpot
title_sort crowdsourcing the identification of organisms: a case-study of ispot
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4319112/
https://www.ncbi.nlm.nih.gov/pubmed/25685027
http://dx.doi.org/10.3897/zookeys.480.8803
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