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Processing biological literature with customizable Web services supporting interoperable formats

Web services have become a popular means of interconnecting solutions for processing a body of scientific literature. This has fuelled research on high-level data exchange formats suitable for a given domain and ensuring the interoperability of Web services. In this article, we focus on the biologic...

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Autores principales: Rak, Rafal, Batista-Navarro, Riza Theresa, Carter, Jacob, Rowley, Andrew, Ananiadou, Sophia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086403/
https://www.ncbi.nlm.nih.gov/pubmed/25006225
http://dx.doi.org/10.1093/database/bau064
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author Rak, Rafal
Batista-Navarro, Riza Theresa
Carter, Jacob
Rowley, Andrew
Ananiadou, Sophia
author_facet Rak, Rafal
Batista-Navarro, Riza Theresa
Carter, Jacob
Rowley, Andrew
Ananiadou, Sophia
author_sort Rak, Rafal
collection PubMed
description Web services have become a popular means of interconnecting solutions for processing a body of scientific literature. This has fuelled research on high-level data exchange formats suitable for a given domain and ensuring the interoperability of Web services. In this article, we focus on the biological domain and consider four interoperability formats, BioC, BioNLP, XMI and RDF, that represent domain-specific and generic representations and include well-established as well as emerging specifications. We use the formats in the context of customizable Web services created in our Web-based, text-mining workbench Argo that features an ever-growing library of elementary analytics and capabilities to build and deploy Web services straight from a convenient graphical user interface. We demonstrate a 2-fold customization of Web services: by building task-specific processing pipelines from a repository of available analytics, and by configuring services to accept and produce a combination of input and output data interchange formats. We provide qualitative evaluation of the formats as well as quantitative evaluation of automatic analytics. The latter was carried out as part of our participation in the fourth edition of the BioCreative challenge. Our analytics built into Web services for recognizing biochemical concepts in BioC collections achieved the highest combined scores out of 10 participating teams. Database URL: http://argo.nactem.ac.uk.
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spelling pubmed-40864032014-07-09 Processing biological literature with customizable Web services supporting interoperable formats Rak, Rafal Batista-Navarro, Riza Theresa Carter, Jacob Rowley, Andrew Ananiadou, Sophia Database (Oxford) Original Article Web services have become a popular means of interconnecting solutions for processing a body of scientific literature. This has fuelled research on high-level data exchange formats suitable for a given domain and ensuring the interoperability of Web services. In this article, we focus on the biological domain and consider four interoperability formats, BioC, BioNLP, XMI and RDF, that represent domain-specific and generic representations and include well-established as well as emerging specifications. We use the formats in the context of customizable Web services created in our Web-based, text-mining workbench Argo that features an ever-growing library of elementary analytics and capabilities to build and deploy Web services straight from a convenient graphical user interface. We demonstrate a 2-fold customization of Web services: by building task-specific processing pipelines from a repository of available analytics, and by configuring services to accept and produce a combination of input and output data interchange formats. We provide qualitative evaluation of the formats as well as quantitative evaluation of automatic analytics. The latter was carried out as part of our participation in the fourth edition of the BioCreative challenge. Our analytics built into Web services for recognizing biochemical concepts in BioC collections achieved the highest combined scores out of 10 participating teams. Database URL: http://argo.nactem.ac.uk. Oxford University Press 2014-07-08 /pmc/articles/PMC4086403/ /pubmed/25006225 http://dx.doi.org/10.1093/database/bau064 Text en © The Author(s) 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by/3.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Rak, Rafal
Batista-Navarro, Riza Theresa
Carter, Jacob
Rowley, Andrew
Ananiadou, Sophia
Processing biological literature with customizable Web services supporting interoperable formats
title Processing biological literature with customizable Web services supporting interoperable formats
title_full Processing biological literature with customizable Web services supporting interoperable formats
title_fullStr Processing biological literature with customizable Web services supporting interoperable formats
title_full_unstemmed Processing biological literature with customizable Web services supporting interoperable formats
title_short Processing biological literature with customizable Web services supporting interoperable formats
title_sort processing biological literature with customizable web services supporting interoperable formats
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4086403/
https://www.ncbi.nlm.nih.gov/pubmed/25006225
http://dx.doi.org/10.1093/database/bau064
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