Semantic assessment of smart healthcare ontology

被引:12
|
作者
Tiwari, Sanju [1 ]
Abraham, Ajith [2 ]
机构
[1] Machine Intelligence Res Labs MIR Labs, Auburn, AL USA
[2] Machine Intelligence Res Labs MIR Labs, Sci Network Innovat & Res Excellence, Auburn, WA, Australia
关键词
Health care; IoT; Ontology assessment; Knowledge modeling; Linked data; Test cases;
D O I
10.1108/IJWIS-05-2020-0027
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Purpose Health-care ontologies and their terminologies play a vital role in knowledge representation and data integration for health information. In health-care systems, Internet of Technology (IoT) technologies provide data exchange among various entities and ontologies offer a formal description to present the knowledge of health-care domains. These ontologies are advised to assure the quality of their adoption and applicability in the real world. Design/methodology/approach Ontology assessment is an integral part of ontology construction and maintenance. It is always performed to identify inconsistencies and modeling errors by the experts during the ontology development. A smart health-care ontology (SHCO) has been designed to deal with health-care information and IoT devices. In this paper, an integrated approach has been proposed to assess the SHCO on different assessment tools such as Themis, Test-Driven Development (TDD)onto, Protege and OOPs! Several test cases are framed to assess the ontology on these tools, in this research, Themis and TDDonto tools provide the verification for the test cases while Protege and OOPs! provides validation of modeled knowledge in the ontology. Findings As of the best knowledge, no other study has been presented earlier to conduct the integrated assessment on different tools. All test cases are successfully analyzed on these tools and results are drawn and compared with other ontologies. Originality/value The developed ontology is analyzed on different verification and validation tools to assure the quality of ontologies.
引用
收藏
页码:475 / 491
页数:17
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