New York State Center of Excellence in Bioinformatics & Life Sciences R T U 1 MIE 2006 Workshop Semantic Challenge for Interoperable EHR Architectures provided by EFMI WGs EHR - Security, Safety and Ethics - Natural Language Understanding Part 4: The role of terminology and ontology for semantic interoperability Tuesday August 29th, 2006 Werner Ceusters, MD Ontology Research Group Center of Excellence in Bioinformatics & Life Sciences SUNY at Buffalo, NY

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 2/28 The word ‘Terminology’ has two meanings 1)The discipline of terminology management –synonymous with terminology work (used in ISO 704) 2)The set of designations used in the special language of a subject field, such as the terminology of medicine –Used in both the singular and plural –Used with an article in the singular: a terminology

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 3/28 Terminology is VERY standardised ISO 704: 2000Terminology work – Principles and methods ISO 860: 1996Terminology work – Harmonization of concepts and terms ISO : 2000Terminology work – Vocabulary – Part 1: Theory and application ISO 15188: 2001Project management guidelines for terminology standardization ISO :2000Terminology work – Vocabulary – Part 2: Computer applications ISO 12620: 1999Computer applications in terminology – Data categories ISO 16642: 2003Computer applications in terminology – Terminological markup framework ISO 2788: 1986Documentation – Guidelines for the establishment and development of monolingual thesauri

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 4/28 ISO Standards in Terminology: building blocks Objects perceived or conceived, concrete or abstract abstracted or conceptualized into concepts Concepts depict or correspond to a set of objects based on a defined set of characteristics represented or expressed in language by designations or by definitions organized into concept systems Designations represented as terms, names (appellations) or symbols designate or represent a concept attributed to a concept by consensus within a special language community

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 5/28 Origin: Peirce, Ogden & Richards, Wüster Unit of Thinking (Concept) Designation (Symbol, Sign, Term, Formula etc.) Referent (Concrete Object, Real Thing, Conceived Object) (Unit of Thought, Unit of Knowledge)

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 6/28 Fundamental Activities of Terminology Work Identifying ‘concepts’ and ‘concept relations’; –Analyzing and modeling concept systems on the basis of identified concepts and concept relations; –Establishing representations of concept systems through concept diagrams; –Crafting concept-oriented definitions; –Attributing designations (predominantly terms) to each concept in one or more languages; and, –Recording and presenting terminological data, principally in terminological entries stored in print and electronic media (terminography).

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 7/28 Why terminologies ? As such ? –Fixing/stabilizing the language within a domain and a linguistic community; –Unambiguous communication. In Healthcare Information Technology ? –Semantic Indexing; –Information exchange and linking between heterogeneous systems; –Terminologies as basis for documentation through coding and classification

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 8/28 From terminology to ontology Concept/terminology-based systems make implicit knowledge explicit Ontologies aim to push explicitness further: –reasoning by machines Classification Prediction Triggering of alerts

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 9/28 The word ‘Ontology’ has two meanings Ontology: the science of what entities exist and how they relate to each other An ontology: a representation of some domain which –(1) is intelligible to a domain expert –(2) is formalized in a way that allows it to support automatic information processing

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 10/28 Within the context of ‘an ontology’, the word ‘domain’ has two meanings For most computer scientists: –An agreed upon conceptualization about which man and machine can communicate using an agreed upon vocabulary For philosophical ontologists: –A portion of reality Still allowing for a variety of entities to be recognised by one school and refuted by another one

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 11/28 Ontology based on Unqualified Realism Accepts the existence of –a real world outside mind and language –a structure in that world prior to mind and language (universals / particulars) Rejects ontology as a matter of agreement on ‘conceptualizations’ Uses reality as a benchmark for testing the quality of ontologies as artifacts by building appropriate logics with referential semantics (rather than model-theoretic)

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 12/28 Important to distinguish 3 fundamentally different levels (e.g. in healthcare) 1.the reality on the side of the patient; 2.the cognitive representations of this reality embodied in observations and interpretations on the part of patients, clinicians and others; 3.the publicly accessible concretizations of such cognitive representations in representational artifacts of various sorts, of which ontologies, terminologies and EHRs are examples.

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 13/28 Relevance for EHR & Semantic Interoperability REALITYREALITY BELIEFBELIEF Ontology EHR The conceptualist approach

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 14/28 Relevance for EHR & Semantic Interoperability REALITYREALITY Ontology EHR The realist approach L O G O L K A I S N S G

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 15/28 For the latter, thus … An ontology is a representation of some pre-existing domain of reality which –(1) reflects the properties of the entities within its domain in such a way that there obtains a systematic correlation between reality and the representation itself, –(2) is intelligible to a domain expert –(3) is formalized in a way that allows it to support automatic information processing

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 16/28 For the latter, thus … An ontology should be a representation of some pre-existing domain of reality which –(1) reflects the properties of the entities within its domain in such a way that there obtains a systematic correlation between reality and the representation itself, –(2) is intelligible to a domain expert –(3) is formalized in a way that allows it to support automatic information processing

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 17/28 And accept that everything may change: 1.changes in the underlying reality: Latex allergy did not exist 200 years ago. 2.changes in our (scientific) understanding: Psychoses with hallucinations did exist 600 years ago but some of them were thought to be diabolic possessions. 3.reassessments of what is considered to be relevant for inclusion (notion of purpose). 4.encoding mistakes introduced during data entry or ontology development.

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 18/28 Today’s biggest problem: a confusion between “terminology” and “ontology”

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 19/28 For example: some SNOMED definitions “Disorders are concepts in which there is an explicit or implicit pathological process causing a state of disease which tends to exist for a significant length of time under ordinary circumstances.” But also: “Concepts are unique units of thought”. Thus: Disorders are unique units of thoughts in which there is a pathological process …??? And thus: to threat all diseases in the world at once we simply should stop thinking ?????????

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 20/28

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 21/28 Important to differentiate between Lexical, semantic and ontological relations gall gallbladder urinary bladder gall gall bladder bladder inflammation urine urinary bladder inflammation cystitis gallbladder inflammation biliary cystitis inflammation gallbladder inflammation urinary bladder

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 22/28 Algorithms exploiting this distinction were used to detect mistakes in several terminologies and ontologies Ceusters W, Smith B, Kumar A, Dhaen C. Mistakes in Medical Ontologies: Where Do They Come From and How Can They Be Detected? in: Pisanelli DM (ed) IOS Press, Studies in Health Technology and Informatics, vol 102, 2004.

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 23/28 One conclusion: Concept-based terminology (and standardisation thereof) is there as a mechanism to improve understanding of messages by humans. It is NOT the right device –to explain why reality is what it is, how it is organised, etc., (although it is needed to allow communication), –to reason about reality, –to make machines understand what is real, –to integrate across different views, languages, conceptualisations,...

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 24 Why not ? Because there is no valid benchmark !

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 25/28 Why not ? Concepts not necessarily correspond to something that (will) exist(ed) –Sorcerer, unicorn, leprechaun,... Definitions set the conditions under which terms may be used, and may not be abused as conditions an entity must satisfy to be what it is. –Pluto is still the same thing as before although we don’t call it a ‘planet’ anymore Language can make strings of words look as if it were terms –“Middle lobe of left lung” –“prevented abortion” –“cancelled X-Ray”

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 26/28 What to do about it ? (1) Research: –Revision of the appropriatness of concept-based terminology for specific purposes –Relationship between models and that part of reality that the models want to represent –Adequacy of current tools and languages for representation –Boundaries between terminology and ontology and the place of each in semantic interoperability in healthcare

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 27/28 What to do about it ? (2) Training and awareness –Make people more critical wrt terminology and ontology promisses What is needed must be based on needs, not on the popularity of a new paradigm But in a system, it’s not just your own needs, it is each component’s needs ! –Towards “an ontology of ontologies” First description Then quality criteria

New York State Center of Excellence in Bioinformatics & Life Sciences R T U 28/28 Conclusion: the right division of labour Terminology (such as SNOMED-CT): –Communication amongst humans –Communication between human and machine Ontology (such as BFO, FMA): –Representation of “reality” inside a machine –Communication amongst machines –Interpretation by machines