People are essential to linking biodiversity data

Groom, Q., Güntsch, A., Huybrechts, P., Kearney, N., Leachman, S., Nicolson, N., Page, R. D.M. , Shorthouse, D. P., Thessen, A. E. and Haston, E. (2020) People are essential to linking biodiversity data. Database, 2020, baaa072. (doi: 10.1093/database/baaa072) (PMID:33439246) (PMCID:PMC7805432)

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People are one of the best known and most stable entities in the biodiversity knowledge graph. The wealth of public information associated with people and the ability to identify them uniquely open up the possibility to make more use of these data in biodiversity science. Person data are almost always associated with entities such as specimens, molecular sequences, taxonomic names, observations, images, traits and publications. For example, the digitization and the aggregation of specimen data from museums and herbaria allow us to view a scientist’s specimen collecting in conjunction with the whole corpus of their works. However, the metadata of these entities are also useful in validating data, integrating data across collections and institutional databases and can be the basis of future research into biodiversity and science. In addition, the ability to reliably credit collectors for their work has the potential to change the incentive structure to promote improved curation and maintenance of natural history collections.

Item Type:Articles
Additional Information:This work was supported by European Cooperation in Science and Technology (COST) as part of the Mobilise Action CA17106 on Mobilising Data, Experts and Policies in Scientific Collections and SYNTHESYS+ a Research and Innovation action funded under H2020-EU. (Grant agreement ID: 823827).
Glasgow Author(s) Enlighten ID:Page, Professor Roderic
Authors: Groom, Q., Güntsch, A., Huybrechts, P., Kearney, N., Leachman, S., Nicolson, N., Page, R. D.M., Shorthouse, D. P., Thessen, A. E., and Haston, E.
College/School:College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine
Journal Name:Database
Publisher:Oxford University Press
ISSN (Online):1758-0463
Published Online:27 November 2020
Copyright Holders:Copyright © 2020 The Authors
First Published:First published in Database 2020: baaa072
Publisher Policy:Reproduced under a Creative Commons License

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