A survey on ontology techniques deployed in the biomedical domain

Abstract

The number of studies in big data aspects of biomedical domain are tremendously increasing because of the growing technical knowledge, need for reduced computation costs and the availability of internet facilities almost over everywhere. A considerable amount of data in the biomedical domain are stored across platforms that are semantically, structurally and semantically different. With this heterogeneity, it becomes extremely difficult to access and derive meaningful insights from data. Data Integration plays a significant role in merging the data and making access to these data faster and easier. Ontology, a form of knowledge representation, is widely used in data integration to denote the semantic relationship between the data stored in heterogeneous data sources and aid in easier retrieval. This paper surveys the ontology engineering methods used in various biomedical domains like cardiology, nephrology, diabetes, Covid-19, traditional medicine and the recent advancements in ontology development.