Knowledge Representation and Ontologies

Abstract

Ontologies have become important tools in biomedicine, supporting critical aspects of both health care and biomedical research, including clinical research [1]. Some even see ontologies as integral to science [2]. Unlike terminologies (focusing on naming) and classification systems (developed for partitioning a domain), ontologies define the types of entities that exist, as well as their interrelations. And while knowledge bases generally integrate both definitional and assertional knowledge, ontologies focus on what is always true of entities, i.e., definitional knowledge [3]. In practice, however, there is no sharp distinction between these kinds of artifacts and 'ontology' has become a generic name for a variety of knowledge sources with important differences in their degree of formality, coverage, richness and computability [4]. In this chapter, we focus on those ontologies of particular relevance to clinical research. After a brief introduction to ontology development and knowledge representation, we present the characteristics of some of these ontologies. We then show how ontologies are integrated in and made accessible through knowledge repositories, and illustrate their role in clinical research. Ontology developmentOntology development has not yet been formalized to the same extent as, say, database development has, and there is still no equivalent for ontologies to the entity-relationship model. However, ontology development is guided by fundamental ontological distinctions and supported by the formalisms and tools for knowledge representation that have emerged over the past decades. Several top-level ontologies provide useful constraints for the development of domain ontologies and one the most recent trends is increased collaboration among the creators of ontologies for coordinated development.In: Richesson RL, Andrews JE, editors. Clinical research informatics. London: Springer-Verlag; 2012. p. 255-275. 2 Important ontological distinctionsA small number of ontological distinctions inherited from philosophical ontology provide a useful framework for creating ontologies. The first distinction is between types and instances. Instances correspond to individual entities (e.g., my left kidney, the patient identified by 1234), while types represent the common characteristics of sets of instances (e.g., a kidney is a bean-shaped, intraabdominal organ -properties common to all kidneys) [5]. Instances are related to the corresponding types by the relation instance of. For example, my left kidney is an instance of kidney. (It must be noted that most biomedical ontologies only represent types in reference to which the instances recorded in patient records and laboratory notebooks can be annotated). Another fundamental distinction is between continuants and occurrents [6]. While continuants exist (endure) through time, occurrents go through time in phases. Roughly speaking, objects (e.g., a liver, an endoscope) are continuants and processes (e.g., the flow of blood through the mitral valve) are continuants. O...

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