A framework for the development of a global standardised marine taxon reference image database (SMarTaR-ID) to support image-based analyses
Video and image data are regularly used in the field of benthic ecology to document biodiversity. However, their use is subject to a number of challenges, principally the identification of taxa within the images without associated physical specimens. The challenge of applying traditional taxonomic k...
Published in: | PLOS ONE |
---|---|
Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
Format: | Article in Journal/Newspaper |
Language: | unknown |
Published: |
Zenodo
2019
|
Subjects: | |
Online Access: | https://doi.org/10.1371/journal.pone.0218904 |
id |
ftzenodo:oai:zenodo.org:4265133 |
---|---|
record_format |
openpolar |
spelling |
ftzenodo:oai:zenodo.org:4265133 2024-09-15T18:23:49+00:00 A framework for the development of a global standardised marine taxon reference image database (SMarTaR-ID) to support image-based analyses Howell KL Davies JS Allcock AL Braga-Henriques A Buhl-Mortensen P Carreiro-Silva M Dominguez-Carrio C Durden JM Foster NL Game CA Hitchin B Horton T Hosking B Jones DOB Mah C Laguionie Marchais C Menot L Morato T Pearman TRR Piechaud N Ross RE Ruhl HA Saeedi H Stefanoudis PV Taranto GH Thompson MB Taylor JR Tyler P Vad J Victorero L Vieira RP Woodall LC Xavier JR Wagner D 2019-12-31 https://doi.org/10.1371/journal.pone.0218904 unknown Zenodo https://zenodo.org/communities/atlas https://zenodo.org/communities/eu https://doi.org/10.1371/journal.pone.0218904 oai:zenodo.org:4265133 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode info:eu-repo/semantics/article 2019 ftzenodo https://doi.org/10.1371/journal.pone.0218904 2024-07-26T18:19:36Z Video and image data are regularly used in the field of benthic ecology to document biodiversity. However, their use is subject to a number of challenges, principally the identification of taxa within the images without associated physical specimens. The challenge of applying traditional taxonomic keys to the identification of fauna from images has led to the development of personal, group, or institution level reference image catalogues of operational taxonomic units (OTUs) or morphospecies. Lack of standardisation among these reference catalogues has led to problems with observer bias and the inability to combine datasets across studies. In addition, lack of a common reference standard is stifling efforts in the application of artificial intelligence to taxon identification. Using the North Atlantic deep sea as a case study, we propose a database structure to facilitate standardisation of morphospecies image catalogues between research groups and support future use in multiple frontend applications. We also propose a framework for coordination of international efforts to develop reference guides for the identification of marine species from images. The proposed structure maps to the Darwin Core standard to allow integration with existing databases. We suggest a management framework where high-level taxonomic groups are curated by a regional team, consisting of both end users and taxonomic experts. We identify a mechanism by which overall quality of data within a common reference guide could be raised over the next decade. Finally, we discuss the role of a common reference standard in advancing marine ecology and supporting sustainable use of this ecosystem. Article in Journal/Newspaper North Atlantic Zenodo PLOS ONE 14 12 e0218904 |
institution |
Open Polar |
collection |
Zenodo |
op_collection_id |
ftzenodo |
language |
unknown |
description |
Video and image data are regularly used in the field of benthic ecology to document biodiversity. However, their use is subject to a number of challenges, principally the identification of taxa within the images without associated physical specimens. The challenge of applying traditional taxonomic keys to the identification of fauna from images has led to the development of personal, group, or institution level reference image catalogues of operational taxonomic units (OTUs) or morphospecies. Lack of standardisation among these reference catalogues has led to problems with observer bias and the inability to combine datasets across studies. In addition, lack of a common reference standard is stifling efforts in the application of artificial intelligence to taxon identification. Using the North Atlantic deep sea as a case study, we propose a database structure to facilitate standardisation of morphospecies image catalogues between research groups and support future use in multiple frontend applications. We also propose a framework for coordination of international efforts to develop reference guides for the identification of marine species from images. The proposed structure maps to the Darwin Core standard to allow integration with existing databases. We suggest a management framework where high-level taxonomic groups are curated by a regional team, consisting of both end users and taxonomic experts. We identify a mechanism by which overall quality of data within a common reference guide could be raised over the next decade. Finally, we discuss the role of a common reference standard in advancing marine ecology and supporting sustainable use of this ecosystem. |
format |
Article in Journal/Newspaper |
author |
Howell KL Davies JS Allcock AL Braga-Henriques A Buhl-Mortensen P Carreiro-Silva M Dominguez-Carrio C Durden JM Foster NL Game CA Hitchin B Horton T Hosking B Jones DOB Mah C Laguionie Marchais C Menot L Morato T Pearman TRR Piechaud N Ross RE Ruhl HA Saeedi H Stefanoudis PV Taranto GH Thompson MB Taylor JR Tyler P Vad J Victorero L Vieira RP Woodall LC Xavier JR Wagner D |
spellingShingle |
Howell KL Davies JS Allcock AL Braga-Henriques A Buhl-Mortensen P Carreiro-Silva M Dominguez-Carrio C Durden JM Foster NL Game CA Hitchin B Horton T Hosking B Jones DOB Mah C Laguionie Marchais C Menot L Morato T Pearman TRR Piechaud N Ross RE Ruhl HA Saeedi H Stefanoudis PV Taranto GH Thompson MB Taylor JR Tyler P Vad J Victorero L Vieira RP Woodall LC Xavier JR Wagner D A framework for the development of a global standardised marine taxon reference image database (SMarTaR-ID) to support image-based analyses |
author_facet |
Howell KL Davies JS Allcock AL Braga-Henriques A Buhl-Mortensen P Carreiro-Silva M Dominguez-Carrio C Durden JM Foster NL Game CA Hitchin B Horton T Hosking B Jones DOB Mah C Laguionie Marchais C Menot L Morato T Pearman TRR Piechaud N Ross RE Ruhl HA Saeedi H Stefanoudis PV Taranto GH Thompson MB Taylor JR Tyler P Vad J Victorero L Vieira RP Woodall LC Xavier JR Wagner D |
author_sort |
Howell KL |
title |
A framework for the development of a global standardised marine taxon reference image database (SMarTaR-ID) to support image-based analyses |
title_short |
A framework for the development of a global standardised marine taxon reference image database (SMarTaR-ID) to support image-based analyses |
title_full |
A framework for the development of a global standardised marine taxon reference image database (SMarTaR-ID) to support image-based analyses |
title_fullStr |
A framework for the development of a global standardised marine taxon reference image database (SMarTaR-ID) to support image-based analyses |
title_full_unstemmed |
A framework for the development of a global standardised marine taxon reference image database (SMarTaR-ID) to support image-based analyses |
title_sort |
framework for the development of a global standardised marine taxon reference image database (smartar-id) to support image-based analyses |
publisher |
Zenodo |
publishDate |
2019 |
url |
https://doi.org/10.1371/journal.pone.0218904 |
genre |
North Atlantic |
genre_facet |
North Atlantic |
op_relation |
https://zenodo.org/communities/atlas https://zenodo.org/communities/eu https://doi.org/10.1371/journal.pone.0218904 oai:zenodo.org:4265133 |
op_rights |
info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode |
op_doi |
https://doi.org/10.1371/journal.pone.0218904 |
container_title |
PLOS ONE |
container_volume |
14 |
container_issue |
12 |
container_start_page |
e0218904 |
_version_ |
1810464077165625344 |