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A generic workflow for effective sampling of environmental vouchers with UUID assignment and image processing

Sampling of biological and environmental vouchers in the field is rather challenging, particularly under adverse habitat conditions and when various activities need to be handled simultaneously. The workflow described here includes five procedural steps, which result in professional sampling and the...

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Autores principales: Triebel, Dagmar, Reichert, Wolfgang, Bosert, Simone, Feulner, Martin, Okach, Daniel Osieko, Slimani, Abderachid, Rambold, Gerhard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206647/
https://www.ncbi.nlm.nih.gov/pubmed/29688348
http://dx.doi.org/10.1093/database/bax096
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author Triebel, Dagmar
Reichert, Wolfgang
Bosert, Simone
Feulner, Martin
Okach, Daniel Osieko
Slimani, Abderachid
Rambold, Gerhard
author_facet Triebel, Dagmar
Reichert, Wolfgang
Bosert, Simone
Feulner, Martin
Okach, Daniel Osieko
Slimani, Abderachid
Rambold, Gerhard
author_sort Triebel, Dagmar
collection PubMed
description Sampling of biological and environmental vouchers in the field is rather challenging, particularly under adverse habitat conditions and when various activities need to be handled simultaneously. The workflow described here includes five procedural steps, which result in professional sampling and the generation of universally identifiable data. In preparation for the field campaign, sample containers need to be labelled with universally unique identifier (UUID)-QR-codes. At the collection site, labelled containers, sampled material and attached supplementary information are imaged using a GNSS- respectively GPS-enabled smartphone or camera. Image processing, tagging and data storage as CSV text file is subsequently achieved in a field station or laboratory. For this purposes, the newly implemented tool DiversityImageInspector (URL: http://diversityworkbench.net/Portal/DiversityImageInspector) is used. It addresses combined image and data processing in such a context including the extraction of the QR-coded UUID from the image content and the extraction of geodata and time information from the Exif image header. The import of the resulting data files into a relational database or other kind of data management systems is optional but recommended. If applied, the import might be guided by a data transformation tool with compliant schema as described here. The new approach is discussed also with regard to implications for virtual research environments and data publication networks. Database URL: http://diversityworkbench.net/Portal/DiversityImageInspector
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spelling pubmed-72066472020-05-13 A generic workflow for effective sampling of environmental vouchers with UUID assignment and image processing Triebel, Dagmar Reichert, Wolfgang Bosert, Simone Feulner, Martin Okach, Daniel Osieko Slimani, Abderachid Rambold, Gerhard Database (Oxford) Original Article Sampling of biological and environmental vouchers in the field is rather challenging, particularly under adverse habitat conditions and when various activities need to be handled simultaneously. The workflow described here includes five procedural steps, which result in professional sampling and the generation of universally identifiable data. In preparation for the field campaign, sample containers need to be labelled with universally unique identifier (UUID)-QR-codes. At the collection site, labelled containers, sampled material and attached supplementary information are imaged using a GNSS- respectively GPS-enabled smartphone or camera. Image processing, tagging and data storage as CSV text file is subsequently achieved in a field station or laboratory. For this purposes, the newly implemented tool DiversityImageInspector (URL: http://diversityworkbench.net/Portal/DiversityImageInspector) is used. It addresses combined image and data processing in such a context including the extraction of the QR-coded UUID from the image content and the extraction of geodata and time information from the Exif image header. The import of the resulting data files into a relational database or other kind of data management systems is optional but recommended. If applied, the import might be guided by a data transformation tool with compliant schema as described here. The new approach is discussed also with regard to implications for virtual research environments and data publication networks. Database URL: http://diversityworkbench.net/Portal/DiversityImageInspector Oxford University Press 2018-01-09 /pmc/articles/PMC7206647/ /pubmed/29688348 http://dx.doi.org/10.1093/database/bax096 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Triebel, Dagmar
Reichert, Wolfgang
Bosert, Simone
Feulner, Martin
Okach, Daniel Osieko
Slimani, Abderachid
Rambold, Gerhard
A generic workflow for effective sampling of environmental vouchers with UUID assignment and image processing
title A generic workflow for effective sampling of environmental vouchers with UUID assignment and image processing
title_full A generic workflow for effective sampling of environmental vouchers with UUID assignment and image processing
title_fullStr A generic workflow for effective sampling of environmental vouchers with UUID assignment and image processing
title_full_unstemmed A generic workflow for effective sampling of environmental vouchers with UUID assignment and image processing
title_short A generic workflow for effective sampling of environmental vouchers with UUID assignment and image processing
title_sort generic workflow for effective sampling of environmental vouchers with uuid assignment and image processing
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7206647/
https://www.ncbi.nlm.nih.gov/pubmed/29688348
http://dx.doi.org/10.1093/database/bax096
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