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Expressing Biomedical Ontologies in Natural Language for Expert Evaluation

We report on a study of our custom Hootation software for the purposes of assessing its ability to produce clear and accurate natural language phrases from axioms embedded in three biomedical ontologies. Using multiple domain experts and three discrete rating scales, we evaluated the tool on clarity...

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Detalles Bibliográficos
Autores principales: Amith, Muhammad, Manion, Frank J., Harris, Marcelline R., Zhang, Yaoyun, Xu, Hua, Tao, Cui
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6644701/
https://www.ncbi.nlm.nih.gov/pubmed/29295217
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author Amith, Muhammad
Manion, Frank J.
Harris, Marcelline R.
Zhang, Yaoyun
Xu, Hua
Tao, Cui
author_facet Amith, Muhammad
Manion, Frank J.
Harris, Marcelline R.
Zhang, Yaoyun
Xu, Hua
Tao, Cui
author_sort Amith, Muhammad
collection PubMed
description We report on a study of our custom Hootation software for the purposes of assessing its ability to produce clear and accurate natural language phrases from axioms embedded in three biomedical ontologies. Using multiple domain experts and three discrete rating scales, we evaluated the tool on clarity of the natural language produced, fidelity of the natural language produced from the ontology to the axiom, and the fidelity of the domain knowledge represented by the axioms. Results show that Hootation provided relatively clear natural language equivalents for a select set of OWL axioms, although the clarity of statements hinges on the accuracy and representation of axioms in the ontology.
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spelling pubmed-66447012019-07-22 Expressing Biomedical Ontologies in Natural Language for Expert Evaluation Amith, Muhammad Manion, Frank J. Harris, Marcelline R. Zhang, Yaoyun Xu, Hua Tao, Cui Stud Health Technol Inform Article We report on a study of our custom Hootation software for the purposes of assessing its ability to produce clear and accurate natural language phrases from axioms embedded in three biomedical ontologies. Using multiple domain experts and three discrete rating scales, we evaluated the tool on clarity of the natural language produced, fidelity of the natural language produced from the ontology to the axiom, and the fidelity of the domain knowledge represented by the axioms. Results show that Hootation provided relatively clear natural language equivalents for a select set of OWL axioms, although the clarity of statements hinges on the accuracy and representation of axioms in the ontology. 2017 /pmc/articles/PMC6644701/ /pubmed/29295217 Text en http://creativecommons.org/licenses/by/4.0/ This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
spellingShingle Article
Amith, Muhammad
Manion, Frank J.
Harris, Marcelline R.
Zhang, Yaoyun
Xu, Hua
Tao, Cui
Expressing Biomedical Ontologies in Natural Language for Expert Evaluation
title Expressing Biomedical Ontologies in Natural Language for Expert Evaluation
title_full Expressing Biomedical Ontologies in Natural Language for Expert Evaluation
title_fullStr Expressing Biomedical Ontologies in Natural Language for Expert Evaluation
title_full_unstemmed Expressing Biomedical Ontologies in Natural Language for Expert Evaluation
title_short Expressing Biomedical Ontologies in Natural Language for Expert Evaluation
title_sort expressing biomedical ontologies in natural language for expert evaluation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6644701/
https://www.ncbi.nlm.nih.gov/pubmed/29295217
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