BOOK-CHAPTER

Dental Restorative Material Ontology (DrMO)

Abstract

The DrMO ontology is a domain ontology that represents knowledge underlying the composition, characterization and standardization of different materials involved in the dental restoration procedure. It will assist dentists in selecting appropriate materials based on up-to-date scientific knowledge to satisfy a patient’s specific requirements, without jeopardizing their clinical time. It reuses several ontologies from the OBO foundry, especially the Oral Health and Disease (OHD) Ontology. However, the dental restoration domain is complex and also requires concepts from materials science and engineering. Thus, DrMO also incorporates knowledge from the Devices, Experimental scaffolds, and Biomaterials (DEB) and Functionally Graded Materials (FGM) ontologies to provide more comprehensive knowledge of this area of dental material than previous ontologies. However, much of the terminology from FGM is different than that used in clinical dentistry. Thus, DrMO has changed the appropriate classes to make them consistent with terminology common in dentistry. DrMO also follows ontology design best practices by reusing meta-data properties from the Dublin Core vocabulary. It captures knowledge from a set of the most recent and influential papers in Dental Materials and related fields. Links to these papers are included in the ontology as meta-data defined with Dublin Core. It is implemented in OWL2 and was developed with the Protégé 5.6 ontology editor. The ontology was created using the Ontology Development 101 methodology by Noy et. al. Several domain experts in addition to Dr. Dutta also provided their expertise. The ontology is available on GitHub and licensed via an open source license. The GitHub project includes a corresponding file of SPARQL queries that answer the competency questions defined as part of the ontology development methodology.

Keywords:
Ontology Terminology Computer science Open Biomedical Ontologies Upper ontology Process ontology Ontology-based data integration Standardization Vocabulary Data science Suggested Upper Merged Ontology Domain knowledge Software engineering

Metrics

1
Cited By
0.65
FWCI (Field Weighted Citation Impact)
18
Refs
0.73
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Semantic Web and Ontologies
Physical Sciences →  Computer Science →  Artificial Intelligence
Biomedical Text Mining and Ontologies
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Molecular Biology
linguistics and terminology studies
Social Sciences →  Arts and Humanities →  Language and Linguistics

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