OpenClinical logo


 bullet  Definitions  bullet  Introductory web resources  bullet  Benefits  bullet  Issues  bullet  Current work  bullet  References  bullet  Links

An ontology can be viewed as a declarative model of a domain that defines and represents the concepts existing in that domain, their attributes and the relationships between them. It is typically represented as a knowledge base which then becomes available to applications that need to use and/or share the knowledge of a domain. Within health informatics, an ontology is a formal description of a health-related domain.


Ontology - the "science of being" - typically has different meanings in different contexts. Webster's Dictionary defines ontology as:

  1. a branch of metaphysics relating to the nature and relations of being
  2. a particular theory about the nature of being and the kinds of existence

Several philosophers - from Aristoteles (4th Century BC) to Leibniz (1646-1716), and more recently the 19th Century major ontologists like Bolzano, Brentano, Husserl and Frege - have provided criteria for distinguishing between different kind of objects (a.g. concrete vs. abstract) and the relations between them.

In the late 20th Century, Artificial Intelligence (AI) adopted the term and began using it in the sense of a "specification of a conceptualization" in the context of knowledge and data sharing (Gruber).

Guarino provides the following definition for an ontology: "A set of logical axioms designed to account for the intended meaning of a vocabulary", whereas Sowa proposes the following: "The subject of ontology is the study of the categories of things that exist or may exist in some domain. The product of such a study, called an ontology, is a catalog of the types of things that are assumed to exist in a domain of interest D from the perspective of a person who uses a language L for the purpose of talking about D."

From an AI perspective therefore, ontology is not only a discipline, but also the outcome of the activity of ontological analysis and modeling. In this sense we can speak of "an ontology of cardiac valves" or "an ontology of inflammation". Such ontologies are examples of the so-called "domain ontologies", whereas "foundational ontologies" represent domain-independent concepts like objects, events, processes.

Ontologies: introductory web resources
 bullet  A Guide to Creating Your First Ontology, Stanford University  bullet  What-is-an-ontology - by Tom Gruber, Stanford University  bullet  Ontology tutorial materials, including use of the OWL language, Medical Informatics Group, Manchester University  bullet  Bio-ontology pages maintained by Robert Stevens at the University of Manchester  bullet  Guided Tour of Ontology by John Sowa  bullet  The IEEE "Standard Upper Ontology" working group which is developing a standard that will specify an domain-independent ontology to support computer applications  bullet  Tutorial by Nicola Guarino covering background material on conceptual modeling, knowledge structuring, and ontology in general

Ontologies in medicine

The use of ontologies in medicine is mainly focussed on the representation and (re-)organization of medical terminologies. Physicians developed their own specialized languages and lexicons to help them store and communicate general medical knowledge and patient-related information efficiently. Such terminologies, optimized for human processing, are characterized by a significant amount of implicit knowledge. Medical information systems, on the other hand, need to be able to communicate complex and detailed medical concepts (possibly expressed in different languages) unambiguously. This is obviously a difficult task and requires a profound analysis of the structure and the concepts of medical terminologies. But it can be achieved by constructing medical domain ontologies for representing medical terminology systems.

Ontology-based applications have also been built in the field of Medical Natural Language Processing.


  • Ontologies can help build more powerful and more interoperable information systems in healthcare.
  • Ontologies can support the need of the healthcare process to transmit, re-use and share patient data.
  • Ontologies can also provide semantic-based criteria to support different statistical aggregations for different purposes.
  • Possibly the most significant benefit that ontologies may bring to healthcare systems is their ability to support the indispensible integration of knowledge and data.

On the negative side:

  • Some remain sceptical about the impact that ontologies may have on the design and maintenance of real-world healthcare information systems.

The debate on ontology is still very active in the philosophical community. An interesting account of historical issues and their implications with current investigations can be found at

A discussion on ontology and information systems is provided by Simon Milton at the University of Melbourne

Foundational ontology issues are discussed by the Laboratory for Applied Ontology (LOA) in Rome.

Many relevant papers dealing both with philosophical aspects and medical applications in ontology may be found on
Current work on medical ontologies
 bullet  CO-ODE: Collaborative Open Ontology Development Environment project, Medical Informatics Group at the University of Manchester  bullet  LinKBase: knowledge base of over 1 million language-independent medical concepts featuring an ontology with a formal conceptual description of the medical domain (Language and Computing NV, Belgium)  bullet  The Medical Ontology Research program, Lister Hill National Center for Biomedical Communications (a division of the US National Library of Medicine). The aim of this program is to develop a sound medical ontology to enable various knowledge processing applications to communicate with one another.  bullet  The Language and Information Engineering Lab (JULIE) at Jena University, Germany focuses on automatic text analysis in order to service various applications such as information extraction, text mining, cross-language document retrieval, and text summarization. Most of these applications are embedded in the biomedical domain. The JULIE Lab is developing morphological, syntactic and semantic processors, as well as domain-specific knowledge resources (ontologies) for deep text understanding.  bullet  GALEN and the "Galen-Core" high-level ontology for medicine.  bullet  The ONIONS methodology - designed to build the ON9 medical ontology.  bullet  MedO - a bio-medical ontology developed at the Institute of Formal Ontology and Medical Information Systems, Germany.  bullet  The ontology for the HL7 Reference Information Model (RIM)  bullet  The Foundational Model of Anatomy - a domain ontology that represents a coherent body of explicit declarative knowledge about human anatomy.  bullet  the Gene Ontology Consortium which aims to produce a controlled vocabulary that can be applied to all organisms even as knowledge of gene and protein roles in cells is accumulating and changing.
references: general

Barry Smith. Ontology. In Luciano Floridi (ed.), Blackwell Guide to the Philosophy of Computing and Information, Oxford: Blackwell, 2003, 155-166.

[Draft version - U Buffalo]   [Blackwell]

" Ontology as a branch of philosophy is the science of what is, of the kinds and structures of objects, properties, events, processes and relations in every area of reality. ... "

Natalya F. Noy and Deborah L. McGuinness. Guide to Creating Your First Ontology. Stanford University.

[Stanford University]   []

" In recent years the development of ontologies—explicit formal specifications of the terms in the domain and relations among them (Gruber 1993)—has been moving from the realm of Artificial-Intelligence laboratories to the desktops of domain experts. Ontologies have become common on the World-Wide Web. The ontologies on the Web range from large taxonomies categorizing Web sites (such as on Yahoo!) to categorizations of products for sale and their features (such as on The WWW Consortium (W3C) is developing the Resource Description Framework (Brickley and Guha 1999), a language for encoding knowledge on Web pages to make it understandable to electronic agents searching for information. The Defense Advanced Research Projects Agency (DARPA), in conjunction with the W3C, is developing DARPA Agent Markup Language (DAML) by extending RDF with more expressive constructs aimed at facilitating agent interaction on the Web (Hendler and McGuinness 2000). Many disciplines now develop standardized ontologies that domain experts can use to share and annotate information in their fields. Medicine, for example, has produced large, standardized, structured vocabularies such as snomed (Price and Spackman 2000) and the semantic network of the Unified Medical Language System (Humphreys and Lindberg 1993). Broad general-purpose ontologies are emerging as well. For example, the United Nations Development Program and Dun & Bradstreet combined their efforts to develop the UNSPSC ontology which provides terminology for products and services ... "

Guarino N. Formal ontology and information systems. Amended version of a paper that appeared in N. Guarino (ed.), Formal Ontology in Information Systems. Proceedings of FOIS’98, Trento, Italy, 6-8 June 1998. Amsterdam, IOS Press, pp. 3-15.


" Research on ontology is becoming increasingly widespread in the computer science community, and its importance is being recognized in a multiplicity of research fields and application areas, including knowledge engineering, database design and integration, information retrieval and extraction. We shall use the generic term “information systems”, in its broadest sense, to collectively refer to these application perspectives. We argue in this paper that so-called ontologies present their own methodological and architectural peculiarities: on the methodological side, their main peculiarity is the adoption of a highly interdisciplinary approach, while on the architectural side the most interesting aspect is the centrality of the role they can play in an information system, leading to the perspective of ontology-driven information systems. "

Guarino N. (editor). Formal ontology and information systems. Amended version of a paper appeared in N. Guarino (ed.), Volume 46 Frontiers in Artificial Intelligence and Applications. IOS Press, 1998.

[IOS Press]

" Research on ontology is becoming increasingly widespread in the computer science community. While this term has been rather confined to the philosophical sphere in the past, it is now gaining a specific role in areas such as Artificial Intelligence, Computational Linguistics, and Databases. Its importance has been recognized in fields as diverse as knowledge engineering, knowledge representation, qualitative modeling, language engineering, database design, information integration, object-oriented analysis, information retrieval and extraction, knowledge management and organization, agent-based systems design. Current applications areas are disparate, including enterprise integration, natural language translation, medicine, mechanical engineering, electronic commerce, geographic information systems, legal information systems, and biological information systems. Various workshops addressing the engineering aspects of ontology have been held in the recent years. However, ontology by 'its very nature' ought to be a unifying discipline. Insights in this field have potential impact on the whole area of information systems (taking this term in its broadest sense), as testified by the interest recently shown by international standards organizations. In order to provide a solid general foundation for this work, it is therefore important to focus on the common scientific principles and open problems arising from current tools, methodologies, and applications of ontology. "

Staab S, Studer R (Eds.). Handbook on Ontologies. Series : International Handbooks on Information Systems Springer 2004. ISBN: 3-540-40834-7

[Springer]   [TOC - Springer]

" An ontology is a description (like a formal specification of a program) of concepts and relationships that can exist for an agent or a community of agents. The concept is important for the purpose of enabling knowledge sharing and reuse. The Handbook on Ontologies provides a comprehensive overview of the current status and future prospectives of the field of ontologies. The handbook demonstrates standards that have been created recently, it surveys methods that have been developed and it shows how to bring both into practice of ontology infrastructures and applications that are the best of their kind. "
References: Ontologies in Medicine

Ontology as the Core Discipline of Biomedical Informatics: Legacies of the Past and Recommendations for the Future Direction of Research. In: Dodig Crnkovic Gordana, Stuart Susan (eds.): Computing, Philosophy, and Cognitive Science, Cambridge Scholars Press, Cambridge, 2006.

[U Buffalo]   []

" Conclusion:

We have argued that what is needed if we are to support the kind of information integration to which we all aspire is not more or better information models but rather a theory of the reality to which both coding systems and electronic health records are directed. Applying a sound realist ontology to coding systems and to EHR architectures means in the first place ensuring that the latter are calibrated not to the denizens of Wüster’s ‘realm of concepts’ but rather to those entities in reality – such as particular patients, diseases, therapies, surgical acts, and the universals which they instantiate – which form the subject matter of healthcare. In this way we can make coding systems more coherent, both internally and in their relation to the EHRs which they are designed to support, and externally in relation to the patients, physicians, nurses, etc. toward whom they are directed. "

D.M. Pisanelli (Ed.). Ontologies in Medicine. Volume 102 Studies in Health Technology and Informatics. IOS Press, 2004.

[IOS Press]   []

Titles of papers:

If Ontology is the Solution, What is the Problem?
Biodynamic Ontology: Applying BFO in the Biomedical Domain.
Bodily Systems and the Spatial-Functional Structure of the Human Body.
Inflammation Ontology Design Pattern: an Exercise in Building a Core Biomedical Ontology with Descriptions and Situations.
Context-Based Task Ontologies for Clinical Guidelines.
An Ontological Framework for the Implementation of Clinical Guidelines in Health Care Organizations.
Gene Ontology Application to Genomic Functional Annotation, Statistical Analysis and Knowledge Mining.
Evolving from Standard Vocabularies to Formal Ontology for an Information System Dedicated to Organ Transplantation.
Mistakes in Medical Ontologies: Where Do They Come From and How Can They Be Detected?

" It is now widely acknowledged that ontologies can make a significant contribution to the design and implementation of information systems in the medical field. The aim of this book is both to review fundamental theoretical issues in ontology and to demonstrate the practical effectiveness of the ontological approach by means of a series of case studies in specific problem areas. It begins with a discussion of the usefulness of ontology in solving problems in the field of medical terminology, including disambiguation of polysemous terms and organization of very large corpora. It goes on to consider the role played by ontologies in the integration and alignment of heterogeneous knowledge sources, in particular in the field of clinical guidelines and evidence-based medicine. Also included are discussions of basic issues of formal ontology, such as how to represent space, time and granularity in biomedical information systems, and discussions of specific high-level medical categories, such as organ systems and their functions. Other papers describe applications of ontology in the field of genomics and in the domain of organ transplantation, and also methods by which mistakes, cycles and inconsistencies in medical ontologies can be detected. The whole presents a unique survey of the most important contributions to the topic of formal ontology in medicine. "
Pisanelli DM, Zaccagnini D, Capurso L, Koch M. An ontological approach to evidence-based medicine and meta-analysis. Stud Health Technol Inform. 2003;95:543-8.


See also paper at: [LOA-CNR]
" The "evidence-based medicine" (EBM) paradigm is centered on the concept of "best evidence" and clinical studies based on this approach are more likely to be considered by physicians in their practice. In this paper we describe an ontology representing the concepts involved in evidence-based medicine and meta-analysis and show how an ontological approach can be applied both for revisiting EBM conceptual foundations and for allowing a more effective knowledge-based information retrieval in literature. "

Mejino JLV and Rosse C. (2004) Symbolic modeling of structural relationships in the Foundational Model of Anatomy

[]   [UW-SIG Publications]

" The need for a sharable resource that can provide deep anatomical knowledge and support inference for biomedical applications has recently been the driving force in the creation of biomedical ontologies. Previous attempts at the symbolic representation of anatomical relationships necessary for such ontologies have been largely limited to general partonomy and class subsumption. We propose an ontology of anatomical relationships beyond class assignments and generic part-whole relations and illustrate the inheritance of structural attributes in the Digital Anatomist Foundational Model of Anatomy. Our purpose is to generate a symbolic model that accommodates all structural relationships and physical properties required to comprehensively and explicitly describe the physical organization of the human body. "

Rosse C, Mejino JL Jr. A reference ontology for biomedical informatics: the Foundational Model of Anatomy. J Biomed Inform. 2003 Dec;36(6):478-500.

[PubMed]   []

" The Foundational Model of Anatomy (FMA), initially developed as an enhancement of the anatomical content of UMLS, is a domain ontology of the concepts and relationships that pertain to the structural organization of the human body. It encompasses the material objects from the molecular to the macroscopic levels that constitute the body and associates with them non-material entities (spaces, surfaces, lines, and points) required for describing structural relationships. The disciplined modeling approach employed for the development of the FMA relies on a set of declared principles, high level schemes, Aristotelian definitions and a frame-based authoring environment. We propose the FMA as a reference ontology in biomedical informatics for correlating different views of anatomy, aligning existing and emerging ontologies in bioinformatics ontologies and providing a structure-based template for representing biological functions. "

Ontologies with potential for use in medicine
KIF: Genesereth MR, Fikes RE. Knowledge Interchange Format, Version 3.0 Stanford, Calif.: Stanford University, 1992.

[U Stanford]   []

" Knowledge Interchange Format (KIF) is a computer-oriented language for the interchange of knowledge among disparate programs. It has declarative semantics (i.e. the meaning of expressions in the representation can be understood without appeal to an interpreter for manipulating those expressions); it is logically comprehensive (i.e. it provides for the expression of arbitrary sentences in the first-order predicate calculus); it provides for the representation of knowledge about the representation of knowledge; it provides for the representation of nonmonotonic reasoning rules; and it provides for the definition of objects, functions, and relations. "
Ontolingua: Farquhar A, Fikes R, Rice J. The Ontolingua server: a tool for collaborative ontology construction. Proceedings of the 10th Knowledge Acquisition Workshop; Nov 9–14, 1996; Banff, Alberta, Canada; pp 1–19.


" Reusable ontologies are becoming increasingly important for tasks such as information integration, knowledge-level interoperation, and knowledge-base development. We have developed a set of tools and services to support the process of achieving consensus on common shared ontologies by geographically distributed groups. These tools make use of the world-wide web to enable wide access and provide users with the ability to publish, browse, create, and edit ontologies stored on an ontology server. Users can quickly assemble a new ontology from a library of modules. We discuss how our system was constructed, how it exploits existing protocols and browsing tools, and our experience supporting hundreds of users. We describe applications using our tools to achieve consensus on ontologies and to integrate information. "
GOL - General Ontological Language: Guizzardi G., Herre H., Wagner, G. On the General Ontological Foundations of Conceptual Modeling, In Proceedings of 21th International Conference on Conceptual Modeling (ER 2002). Springer-Verlag, Berlin, Lecture Notes in Computer Science

[]   [see GOL pages - U. Leipzig]

" ... [A]n upper level ontology allows to evaluate the ontological correctness of a conceptual model and to develop guidelines how the constructs of a conceptual modeling language should be used. In this paper we adopt the General Ontological Language (GOL) ... for this purpose. We discuss a number of issues that arise when applying the concepts of GOL to UML class diagrams as a conceptual modeling language. We also compare our ontological analysis of some parts of the UML with one [previously] proposed. "
 bullet  Ontologies resources (AAAI)  bullet  US National Center for Biomedical Ontology: consortium of leading biologists, clinicians, informaticians, and ontologists who develop innovative technology and methods that allow scientists to create, disseminate, and manage biomedical information and knowledge in machine-processable form  bullet  Open Biomedical Ontologies (OBO) - a useful web site reporting on ontologies across different biological and medical domains  bullet  Journal of Applied Ontology: an interdisciplinary Journal of Ontological Analysis and Conceptual Modeling  bullet  The "Ontology Web Language" (OWL) Guide with many examples  bullet  Protégé: An Open Source ontology-development and Knowledge acquisition Environment [OC]  bullet  Onto-Builder - web based software tool for the development of data dictionaries CNR-ISTC Laboratory of Applied Ontology, Rome
Written and maintained by Domenico M. Pisanelli, CNR-ISTC Laboratory of Applied Ontology, Rome
page history
Entry on OpenClinical: 03 July 2004
Last main update: 04 January 207

Search this site

Privacy policy User agreement Copyright Feedback

Last modified:
© Copyright OpenClinical 2002-2011