Biomedical Ontologies in Action: Role in Knowledge Management, Data Integration and Decision Support

TLDR

Biomedical ontologies are primarily used as standardized vocabularies for integration, but also serve as sources of computable knowledge, though barriers to their application remain. The study surveys practical examples of biomedical ontologies to illustrate their roles in knowledge management, data integration, and decision support. The authors examine recent operational systems and literature, focusing on ontologies such as SNOMED CT, LOINC, FMA, Gene Ontology, RxNorm, NCI Thesaurus, ICD, MeSH, and UMLS. Ontologies are classified into three categories—knowledge management, data integration and semantic interoperability, and decision support and reasoning—highlighting their diverse applications in biomedical research.

Abstract

To provide typical examples of biomedical ontologies in action, emphasizing the role played by biomedical ontologies in knowledge management, data integration and decision support.Biomedical ontologies selected for their practical impact are examined from a functional perspective. Examples of applications are taken from operational systems and the biomedical literature, with a bias towards recent journal articles.The ontologies under investigation in this survey include SNOMED CT, the Logical Observation Identifiers, Names, and Codes (LOINC), the Foundational Model of Anatomy, the Gene Ontology, RxNorm, the National Cancer Institute Thesaurus, the International Classification of Diseases, the Medical Subject Headings (MeSH) and the Unified Medical Language System (UMLS). The roles played by biomedical ontologies are classified into three major categories: knowledge management (indexing and retrieval of data and information, access to information, mapping among ontologies); data integration, exchange and semantic interoperability; and decision support and reasoning (data selection and aggregation, decision support, natural language processing applications, knowledge discovery).Ontologies play an important role in biomedical research through a variety of applications. While ontologies are used primarily as a source of vocabulary for standardization and integration purposes, many applications also use them as a source of computable knowledge. Barriers to the use of ontologies in biomedical applications are discussed.