Taxonomy-Based Approaches to Quality Assurance of Ontologies

Michael Halper, Yehoshua Perl, Christopher Ochs, Ling Zheng

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

Ontologies are important components of health information management systems. As such, the quality of their content is of paramount importance. It has been proven to be practical to develop quality assurance (QA) methodologies based on automated identification of sets of concepts expected to have higher likelihood of errors. Four kinds of such sets (called QA-sets) organized around the themes of complex and uncommonly modeled concepts are introduced. A survey of different methodologies based on these QA-sets and the results of applying them to various ontologies are presented. Overall, following these approaches leads to higher QA yields and better utilization of QA personnel. The formulation of additional QA-set methodologies will further enhance the suite of available ontology QA tools.

Original languageEnglish (US)
Article number3495723
JournalJournal of Healthcare Engineering
Volume2017
DOIs
StatePublished - 2017

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Surgery
  • Biomedical Engineering
  • Health Informatics

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