Architecture and usability of OntoKeeper, an ontology evaluation tool.

Biomedical ontologies Knowledge engineering Knowledge management Ontology auditing Quality evaluation Semantic web Semiotics Usability analysis

Journal

BMC medical informatics and decision making
ISSN: 1472-6947
Titre abrégé: BMC Med Inform Decis Mak
Pays: England
ID NLM: 101088682

Informations de publication

Date de publication:
08 08 2019
Historique:
entrez: 9 8 2019
pubmed: 9 8 2019
medline: 25 6 2020
Statut: epublish

Résumé

The existing community-wide bodies of biomedical ontologies are known to contain quality and content problems. Past research has revealed various errors related to their semantics and logical structure. Automated tools may help to ease the ontology construction, maintenance, assessment and quality assurance processes. However, there are relatively few tools that exist that can provide this support to knowledge engineers. We introduce OntoKeeper as a web-based tool that can automate quality scoring for ontology developers. We enlisted 5 experienced ontologists to test the tool and then administered the System Usability Scale to measure their assessment. In this paper, we present usability results from 5 ontologists revealing high system usability of OntoKeeper, and use-cases that demonstrate its capabilities in previous published biomedical ontology research. To the best of our knowledge, OntoKeeper is the first of a few ontology evaluation tools that can help provide ontology evaluation functionality for knowledge engineers with good usability.

Sections du résumé

BACKGROUND
The existing community-wide bodies of biomedical ontologies are known to contain quality and content problems. Past research has revealed various errors related to their semantics and logical structure. Automated tools may help to ease the ontology construction, maintenance, assessment and quality assurance processes. However, there are relatively few tools that exist that can provide this support to knowledge engineers.
METHOD
We introduce OntoKeeper as a web-based tool that can automate quality scoring for ontology developers. We enlisted 5 experienced ontologists to test the tool and then administered the System Usability Scale to measure their assessment.
RESULTS
In this paper, we present usability results from 5 ontologists revealing high system usability of OntoKeeper, and use-cases that demonstrate its capabilities in previous published biomedical ontology research.
CONCLUSION
To the best of our knowledge, OntoKeeper is the first of a few ontology evaluation tools that can help provide ontology evaluation functionality for knowledge engineers with good usability.

Identifiants

pubmed: 31391056
doi: 10.1186/s12911-019-0859-z
pii: 10.1186/s12911-019-0859-z
pmc: PMC6686219
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

152

Subventions

Organisme : NLM NIH HHS
ID : R01 LM011829
Pays : United States
Organisme : NHGRI NIH HHS
ID : U01 HG009454
Pays : United States

Références

J Biomed Semantics. 2017 Apr 24;8(1):17
pubmed: 28438189
Stud Health Technol Inform. 2017;245:838-842
pubmed: 29295217
J Biomed Inform. 2018 Apr;80:1-13
pubmed: 29462669

Auteurs

Muhammad Amith (M)

School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin Street, Suite 600, Houston, 77030, TX, USA.

Frank Manion (F)

Department of Systems, Populations and Leadership, University of Michigan School of Nursing, 426 N. Ingalls St, Ann Arbor, 48109, MI, USA.

Chen Liang (C)

Arnold School of Public Health, University of South Carolina, Columbia, 29208, SC, USA.

Marcelline Harris (M)

Department of Systems, Populations and Leadership, University of Michigan School of Nursing, 426 N. Ingalls St, Ann Arbor, 48109, MI, USA.

Dennis Wang (D)

University of Texas, Austin, 78712, TX, USA.

Yongqun He (Y)

Center for Computational Medicine & Bioinformatics, University of Michigan Medical School, Room 2017, Palmer Commons 100 Washtenaw Avenue, Ann Arbor, 48109, MI, USA.

Cui Tao (C)

School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin Street, Suite 600, Houston, 77030, TX, USA. cui.tao@uth.tmc.edu.

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