Nivedita Dutta, Michael DeBellis, Nripen Chanda, Alexander D Diehl, Finn Wilson, Mateus Rocha, Mattew Diller, Gopikrishnan M Chandrasekharan, William D Duncan
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引用次数: 0
Abstract
BACKGROUND: Semantic clarity and standardization in representing dental restoration materials are essential for ensuring interoperability across research and clinical settings. However, existing ontologies, including those in the Open Biological and Biomedical Ontology (OBO) Foundry, provide minimal coverage of this clinically relevant domain. METHODS: Guided by OBO Foundry principles, developed an ontological extension of the Oral Health and Disease (OHD) ontology to formally represent dental restoration materials. The modeling process included iterative expert input to ensure clinical accuracy and precise terminology. Logical definitions and subclass hierarchies were created to classify materials by composition and microstructure. RESULTS: The extended ontology introduces a logically structured taxonomy of dental restoration materials using genus-differentia definitions. Its class hierarchy aligns with domain-specific classification systems and captures current and emerging material types. Reuse of class from the Chemical Entities of Biological Interest (ChEBI) and the Environment Ontology (ENVO) as well as relations from the Relation Ontology (RO) supports semantic integration with related biomedical ontologies. CONCLUSION: This work highlights how domain-informed ontology design can effectively capture complex material knowledge. The extensive collaboration integrates expertise from ontology engineers, academic researchers, and practicing clinicians. This approach enables the capture of intricate, often-disregarded real clinical factors, resulting in a model that reflects both the structural properties of materials and their practical use. The extended OHD ontology improves the semantic representation of dental restoration materials and provides a scalable foundation for advancing oral health informatics.
期刊介绍:
Journal of Biomedical Semantics addresses issues of semantic enrichment and semantic processing in the biomedical domain. The scope of the journal covers two main areas:
Infrastructure for biomedical semantics: focusing on semantic resources and repositories, meta-data management and resource description, knowledge representation and semantic frameworks, the Biomedical Semantic Web, and semantic interoperability.
Semantic mining, annotation, and analysis: focusing on approaches and applications of semantic resources; and tools for investigation, reasoning, prediction, and discoveries in biomedicine.