Taxonomy-Based Approaches to Quality Assurance of Ontologies

Document Type

Article

Publication Date

1-1-2017

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.

Identifier

85042512863 (Scopus)

Publication Title

Journal of Healthcare Engineering

External Full Text Location

https://doi.org/10.1155/2017/3495723

e-ISSN

20402309

ISSN

20402295

PubMed ID

29158885

Volume

2017

Grant

R01CA190779

Fund Ref

National Institutes of Health

This document is currently not available here.

Share

COinS