Accelerating taxonomic discovery through automated character extraction

La Salle, J., Wheeler, Q., Jackway, P., Winterton, S., Hobern, D., & Lovell, D. R. (2009) Accelerating taxonomic discovery through automated character extraction. Zootaxa, pp. 43-55.

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This paper discusses the following key messages. Taxonomy is (and taxonomists are) more important than ever in times of global change. Taxonomic endeavour is not occurring fast enough: in 250 years since the creation of the Linnean Systema Naturae, only about 20% of Earth's species have been named. We need fundamental changes to the taxonomic process and paradigm to increase taxonomic productivity by orders of magnitude. Currently, taxonomic productivity is limited principally by the rate at which we capture and manage morphological information to enable species discovery. Many recent (and welcomed) initiatives in managing and delivering biodiversity information and accelerating the taxonomic process do not address this bottleneck. Development of computational image analysis and feature extraction methods is a crucial missing capacity needed to enable taxonomists to overcome the taxonomic impediment in a meaningful time frame. Copyright © 2009 Magnolia Press.

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31 citations in Web of Science®

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ID Code: 79892
Item Type: Journal Article
Refereed: Yes
Additional Information: Cited By :35 Export Date: 6 January 2015
Keywords: Automated character extraction, Feature extraction, Image analysis, Pattern recognition, Taxonomic impediment, Taxonomy
ISSN: 1175-5326
Divisions: Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2009 Magnolia Press
Deposited On: 07 Jan 2015 05:10
Last Modified: 21 Jan 2015 05:25

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