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Developing a web-based SKOS editor

BACKGROUND: The Simple Knowledge Organization System (SKOS) was introduced to the wider research community by a 2005 World Wide Web Consortium (W3C) working draft, and further developed and refined in a 2009 W3C recommendation. Since then, SKOS has become the de facto standard for representing and s...

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Autores principales: Conway, Mike, Khojoyan, Artem, Fana, Fariba, Scuba, William, Castine, Melissa, Mowery, Danielle, Chapman, Wendy, Jupp, Simon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4819276/
https://www.ncbi.nlm.nih.gov/pubmed/27047653
http://dx.doi.org/10.1186/s13326-015-0043-z
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author Conway, Mike
Khojoyan, Artem
Fana, Fariba
Scuba, William
Castine, Melissa
Mowery, Danielle
Chapman, Wendy
Jupp, Simon
author_facet Conway, Mike
Khojoyan, Artem
Fana, Fariba
Scuba, William
Castine, Melissa
Mowery, Danielle
Chapman, Wendy
Jupp, Simon
author_sort Conway, Mike
collection PubMed
description BACKGROUND: The Simple Knowledge Organization System (SKOS) was introduced to the wider research community by a 2005 World Wide Web Consortium (W3C) working draft, and further developed and refined in a 2009 W3C recommendation. Since then, SKOS has become the de facto standard for representing and sharing thesauri, lexicons, vocabularies, taxonomies, and classification schemes. In this paper, we describe the development of a web-based, free, open-source SKOS editor built for the development, curation, and management of small to medium-sized lexicons for health-related Natural Language Processing (NLP). RESULTS: The web-based SKOS editor allows users to create, curate, version, manage, and visualise SKOS resources. We tested the system against five widely-used, publicly-available SKOS vocabularies of various sizes and found that the editor is suitable for the development and management of small to medium-size lexicons. Qualitative testing has focussed on using the editor to develop lexical resources to drive NLP applications in two domains. First, developing a lexicon to support an Electronic Health Record-based NLP system for the automatic identification of pneumonia symptoms. Second, creating a taxonomy of lexical cues associated with Diagnostic and Statistical Manual of Mental Disorders (DSM-5) diagnoses with the goal of facilitating the automatic identification of symptoms associated with depression from short, informal texts. CONCLUSIONS: The SKOS editor we have developed is — to the best of our knowledge — the first free, open-source, web-based, SKOS editor capable of creating, curating, versioning, managing, and visualising SKOS lexicons. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13326-015-0043-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-48192762016-04-05 Developing a web-based SKOS editor Conway, Mike Khojoyan, Artem Fana, Fariba Scuba, William Castine, Melissa Mowery, Danielle Chapman, Wendy Jupp, Simon J Biomed Semantics Software BACKGROUND: The Simple Knowledge Organization System (SKOS) was introduced to the wider research community by a 2005 World Wide Web Consortium (W3C) working draft, and further developed and refined in a 2009 W3C recommendation. Since then, SKOS has become the de facto standard for representing and sharing thesauri, lexicons, vocabularies, taxonomies, and classification schemes. In this paper, we describe the development of a web-based, free, open-source SKOS editor built for the development, curation, and management of small to medium-sized lexicons for health-related Natural Language Processing (NLP). RESULTS: The web-based SKOS editor allows users to create, curate, version, manage, and visualise SKOS resources. We tested the system against five widely-used, publicly-available SKOS vocabularies of various sizes and found that the editor is suitable for the development and management of small to medium-size lexicons. Qualitative testing has focussed on using the editor to develop lexical resources to drive NLP applications in two domains. First, developing a lexicon to support an Electronic Health Record-based NLP system for the automatic identification of pneumonia symptoms. Second, creating a taxonomy of lexical cues associated with Diagnostic and Statistical Manual of Mental Disorders (DSM-5) diagnoses with the goal of facilitating the automatic identification of symptoms associated with depression from short, informal texts. CONCLUSIONS: The SKOS editor we have developed is — to the best of our knowledge — the first free, open-source, web-based, SKOS editor capable of creating, curating, versioning, managing, and visualising SKOS lexicons. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13326-015-0043-z) contains supplementary material, which is available to authorized users. BioMed Central 2016-04-04 /pmc/articles/PMC4819276/ /pubmed/27047653 http://dx.doi.org/10.1186/s13326-015-0043-z Text en © Conway et al. 2015 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Conway, Mike
Khojoyan, Artem
Fana, Fariba
Scuba, William
Castine, Melissa
Mowery, Danielle
Chapman, Wendy
Jupp, Simon
Developing a web-based SKOS editor
title Developing a web-based SKOS editor
title_full Developing a web-based SKOS editor
title_fullStr Developing a web-based SKOS editor
title_full_unstemmed Developing a web-based SKOS editor
title_short Developing a web-based SKOS editor
title_sort developing a web-based skos editor
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4819276/
https://www.ncbi.nlm.nih.gov/pubmed/27047653
http://dx.doi.org/10.1186/s13326-015-0043-z
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