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No specimen left behind: industrial scale digitization of natural history collections

Abstract. Traditional approaches for digitizing natural history collections, which include both imaging and metadata capture, are both labour- and time-intensive. Mass-digitization can only be completed if the resource-intensive steps, such as specimen selection and databasing of associated informat...

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Detalles Bibliográficos
Autores principales: Blagoderov, Vladimir, Kitching, Ian J., Livermore, Laurence, Simonsen, Thomas J., Smith, Vincent S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Pensoft Publishers 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3406472/
https://www.ncbi.nlm.nih.gov/pubmed/22859884
http://dx.doi.org/10.3897/zookeys.209.3178
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author Blagoderov, Vladimir
Kitching, Ian J.
Livermore, Laurence
Simonsen, Thomas J.
Smith, Vincent S.
author_facet Blagoderov, Vladimir
Kitching, Ian J.
Livermore, Laurence
Simonsen, Thomas J.
Smith, Vincent S.
author_sort Blagoderov, Vladimir
collection PubMed
description Abstract. Traditional approaches for digitizing natural history collections, which include both imaging and metadata capture, are both labour- and time-intensive. Mass-digitization can only be completed if the resource-intensive steps, such as specimen selection and databasing of associated information, are minimized. Digitization of larger collections should employ an “industrial” approach, using the principles of automation and crowd sourcing, with minimal initial metadata collection including a mandatory persistent identifier. A new workflow for the mass-digitization of natural history museum collections based on these principles, and using SatScan® tray scanning system, is described.
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spelling pubmed-34064722012-08-02 No specimen left behind: industrial scale digitization of natural history collections Blagoderov, Vladimir Kitching, Ian J. Livermore, Laurence Simonsen, Thomas J. Smith, Vincent S. Zookeys Article Abstract. Traditional approaches for digitizing natural history collections, which include both imaging and metadata capture, are both labour- and time-intensive. Mass-digitization can only be completed if the resource-intensive steps, such as specimen selection and databasing of associated information, are minimized. Digitization of larger collections should employ an “industrial” approach, using the principles of automation and crowd sourcing, with minimal initial metadata collection including a mandatory persistent identifier. A new workflow for the mass-digitization of natural history museum collections based on these principles, and using SatScan® tray scanning system, is described. Pensoft Publishers 2012-07-20 /pmc/articles/PMC3406472/ /pubmed/22859884 http://dx.doi.org/10.3897/zookeys.209.3178 Text en Vladimir Blagoderov, Ian J. Kitching, Laurence Livermore, Thomas J. Simonsen, Vincent S. Smith http://creativecommons.org/licenses/by/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC-BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Article
Blagoderov, Vladimir
Kitching, Ian J.
Livermore, Laurence
Simonsen, Thomas J.
Smith, Vincent S.
No specimen left behind: industrial scale digitization of natural history collections
title No specimen left behind: industrial scale digitization of natural history collections
title_full No specimen left behind: industrial scale digitization of natural history collections
title_fullStr No specimen left behind: industrial scale digitization of natural history collections
title_full_unstemmed No specimen left behind: industrial scale digitization of natural history collections
title_short No specimen left behind: industrial scale digitization of natural history collections
title_sort no specimen left behind: industrial scale digitization of natural history collections
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3406472/
https://www.ncbi.nlm.nih.gov/pubmed/22859884
http://dx.doi.org/10.3897/zookeys.209.3178
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