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BMC Med Inform Decis Mak. 2019 Aug 8;19(Suppl 4):152. doi: 10.1186/s12911-019-0859-z.

Architecture and usability of OntoKeeper, an ontology evaluation tool.

Author information

1
School of Biomedical Informatics, The University of Texas Health Science Center at Houston, 7000 Fannin Street, Suite 600, Houston, 77030, TX, USA.
2
Department of Systems, Populations and Leadership, University of Michigan School of Nursing, 426 N. Ingalls St, Ann Arbor, 48109, MI, USA.
3
Arnold School of Public Health, University of South Carolina, Columbia, 29208, SC, USA.
4
University of Texas, Austin, 78712, TX, USA.
5
Center for Computational Medicine & Bioinformatics, University of Michigan Medical School, Room 2017, Palmer Commons 100 Washtenaw Avenue, Ann Arbor, 48109, MI, USA.
6
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.

Abstract

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.

KEYWORDS:

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

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