Literature DB >> 33614073

Crowdsourcing snake identification with online communities of professional herpetologists and avocational snake enthusiasts.

A M Durso1,2, I Bolon1, A R Kleinhesselink3, M R Mondardini4, J L Fernandez-Marquez5, F Gutsche-Jones4, C Gwilliams4, M Tanner4, C E Smith6, W Wüster7, F Grey5, R Ruiz de Castañeda1.   

Abstract

Species identification can be challenging for biologists, healthcare practitioners and members of the general public. Snakes are no exception, and the potential medical consequences of venomous snake misidentification can be significant. Here, we collected data on identification of 100 snake species by building a week-long online citizen science challenge which attracted more than 1000 participants from around the world. We show that a large community including both professional herpetologists and skilled avocational snake enthusiasts with the potential to quickly (less than 2 min) and accurately (69-90%; see text) identify snakes is active online around the clock, but that only a small fraction of community members are proficient at identifying snakes to the species level, even when provided with the snake's geographical origin. Nevertheless, participants showed great enthusiasm and engagement, and our study provides evidence that innovative citizen science/crowdsourcing approaches can play significant roles in training and building capacity. Although identification by an expert familiar with the local snake fauna will always be the gold standard, we suggest that healthcare workers, clinicians, epidemiologists and other parties interested in snakebite could become more connected to these communities, and that professional herpetologists and skilled avocational snake enthusiasts could organize ways to help connect medical professionals to crowdsourcing platforms. Involving skilled avocational snake enthusiasts in decision making could build the capacity of healthcare workers to identify snakes more quickly, specifically and accurately, and ultimately improve snakebite treatment data and outcomes.
© 2021 The Authors.

Entities:  

Keywords:  biodiversity; citizen science; item response theory; misidentification; online challenge; venomous snakebite

Year:  2021        PMID: 33614073      PMCID: PMC7890515          DOI: 10.1098/rsos.201273

Source DB:  PubMed          Journal:  R Soc Open Sci        ISSN: 2054-5703            Impact factor:   2.963


  3 in total

1.  Community science draws on the power of the crowd.

Authors:  Amber Dance
Journal:  Nature       Date:  2022-09       Impact factor: 69.504

2.  An artificial intelligence model to identify snakes from across the world: Opportunities and challenges for global health and herpetology.

Authors:  Isabelle Bolon; Lukáš Picek; Andrew M Durso; Gabriel Alcoba; François Chappuis; Rafael Ruiz de Castañeda
Journal:  PLoS Negl Trop Dis       Date:  2022-08-15

3.  Citizen science and online data: Opportunities and challenges for snake ecology and action against snakebite.

Authors:  Andrew M Durso; Rafael Ruiz de Castañeda; Camille Montalcini; M Rosa Mondardini; Jose L Fernandez-Marques; François Grey; Martin M Müller; Peter Uetz; Benjamin M Marshall; Russell J Gray; Christopher E Smith; Donald Becker; Michael Pingleton; Jose Louies; Arthur D Abegg; Jeannot Akuboy; Gabriel Alcoba; Jennifer C Daltry; Omar M Entiauspe-Neto; Paul Freed; Marco Antonio de Freitas; Xavier Glaudas; Song Huang; Tianqi Huang; Yatin Kalki; Yosuke Kojima; Anne Laudisoit; Kul Prasad Limbu; José G Martínez-Fonseca; Konrad Mebert; Mark-Oliver Rödel; Sara Ruane; Manuel Ruedi; Andreas Schmitz; Sarah A Tatum; Frank Tillack; Avinash Visvanathan; Wolfgang Wüster; Isabelle Bolon
Journal:  Toxicon X       Date:  2021-06-22
  3 in total

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