Werner CEUSTERS, MD Professor, Department of Psychiatry Director, Ontology Research Group

1. Ontological Realism and theOpen Biomedical Ontologies FoundryFebruari 25, 2011 – San Francisco, CA Werner CEUSTERS, MD Professor, Department of Psychiatry Director, Ontology Research Group Center of Excellence in Bioinformatics and Life Sciences University at Buffalo, NY, USA

2. 1959 - 2011 Short personal history 1977 2006 2004 1989 1992 2002 1995 1998 1993

3. Outline • Introduction: • Health IT and the Semantic Web • Ontology and Ontologies • OBO and the OBO Foundry • Ontological Realism • Some examples

4. The ultimate goal of Healthcare IT Everything collected wherever, whenever and about whomever which is relevant to a medical problem in whomever, whenever and wherever, should be accessible without loss of relevant detail.

5. If it is possible outside healthcare … received confirmation call Note in ‘EHR’ about calories purchased (or card blocked?)

6. This raises many questions • Is this … - possible ? - desirable ? - scary ?

7. This raises many questions • Is this … I don’t care too much about these - possible ?

8. Is this possible? The answer of HIT industry. http://www.interoperabilityshowcase.com/docs/webinarArchives/2010_Webinar_Series_Review_PCD_Domain_2010-8-3f.pdf

9. I respectfully disagree … • Standards? • No shortage indeed, but: • too many, • too low quality, because, • too much ad hoc. • Availability of ‘the’ technology? • Focus on providing patches for old technology rather than developing better systems from solid foundations. • This holds for both Healthcare IT and Semantic Web Technology.

10. Ontologies and Semantic Web Technology Ontology Authoring Tools Computer Science approach to ‘ontology’ create Reasoners Domain Ontologies (OWL) Semantic Applications ‘Philosophical’ approach to ontology use

11. ‘Ontology’ • In philosophy: • Ontology(no plural) is the study of what entities exist and how they relate to each other; • In computer science and many biomedical informatics applications: • An ontology(plural: ontologies) is a shared and agreed upon conceptualization of a domain.

12. Realism Conceptualism Nominalism Universal Concept Collection of particulars yes: in particulars perhaps: in minds no Three major views on reality • Basic questions: • What does a general term such as ‘diabetes’ refer to? • Do generic things exist?

13. No serious scholar should work with ‘concepts’

14. Slow penetration of the idea …

15. what is a concept description a description of? More serious scholars become convinced …

16. but Kantians will never …

19. The visible results of Kantianism and OWL-ism

21. MedDRA: violations of all terminological rules

22. Mistakes in the NCI Thesaurus OWL version Schulz S, Schober S, Tudose I, Stenzhorn H: The Pitfalls of Thesaurus Ontologization – the Case of the NCI Thesaurus. AMIA Annu Symp Proc, 2010: 727-731 (AMIA 2010 Annual Symposium, Washington D.C. USA, November 2010): http://proceedings.amia.org/127gtf/1

23. Mistakes in the NCI Thesaurus OWL version • The NCIT ignores the relationships between representation and reality: • Functions as subclasses of processes: the bearer of a function is not necessarily participant of a process. • Domain incompatibilities: interpreting relation names as containing domain constraints (without being backed-up by any logical definition). • Individuals expressed as classes: like in • Nicaragua subClassOf Conceptual_Part_Of some North_America . Schulz S, Schober S, Tudose I, Stenzhorn H: The Pitfalls of Thesaurus Ontologization – the Case of the NCI Thesaurus. AMIA Annu Symp Proc, 2010: 727-731 (AMIA 2010 Annual Symposium, Washington D.C. USA, November 2010): http://proceedings.amia.org/127gtf/1

24. A problem of education • Consider the wine regions. Initially, we may define main wine regions, such as France, United States, Germany, and so on, as classes and specific wine regions within these large regions as instances. For example, Bourgogne region is an instance of the French region class. However, we would also like to say that the Cotes d’Or region is a Bourgogne region. Therefore, Bourgogne region must be a class (in order to have subclasses or instances). However, making Bourgogne region a class and Cotes d’Or region an instance of Bourgogne region seems arbitrary: it is very hard to clearly distinguish which regions are classes and which are instances. Therefore, we define all wine regions as classes. Ontology Development 101: A Guide to Creating Your First Ontology Natalya F. Noy and Deborah L. McGuinness

26. OBO Foundry approach to countering silo formation • a single, expanding family of ontologies designed to be interoperable and logically well-formed and to incorporate accurate representations of biological reality.

27. OBO Foundry principles • Ontologies are admitted into the Foundry only if their developers commit to an evolving set of common principles, including: • terms and s should be built up compositionally out of more basic terms from a small set of robust feeder ontologies; • for each domain there should be convergence upon exactly one Foundry ontology; • all working with same upper-level categories and relations drawn from Basic Formal Ontology (BFO) and OBO Relation Ontology (RO).

28. ‘Ontology’ • In philosophy: • Ontology(no plural) is the study of what entities exist and how they relate to each other; • In computer science and many biomedical informatics applications: • An ontology(plural: ontologies) is a shared and agreed upon conceptualization of a domain. • Ontological Realism: a specific methodology that uses ontology as the basis for building high quality ontologies, using reality as benchmark.

29. Realism-based Ontology Ontological Realism • There is an external reality which is ‘objectively’ the way it is; • That reality is accessible to us; • We build in our brains cognitive representations of reality; • We communicate with others about what is there, and what we believe there is there. Smith B, Ceusters W. Ontological Realism as a Methodology for Coordinated Evolution of Scientific Ontologies. Applied Ontology, 2010.

31. Three levels of reality in Ontological Realism Representations L3. Linguistic representations about (1), (2) or (3) L2. Clinicians’ beliefs about (1) L1. Entities (particular or generic) with objective existence which are not about anything First Order Reality

32. data organization model development further R&D (instrument and study optimization) add verify use Δ= outcome Generic beliefs application Data generation and use observation & measurement

33. data organization First- Order Reality is about model development Representation further R&D (instrument and study optimization) add verify use Δ= outcome Generic beliefs application A crucial distinction: data and what they are about observation & measurement

34. Ontological Realism makes crucial distinctions • Between data and what data are about: • Level 1 entities (L1): • everything what exists or existed • some are referents (‘are’ used informally) • some are L2, some are L3, none are L2 and L3 • Level 2 entities (L2): beliefs • all are L1 • some are about other L1-entities but none about themselves • Level 3 entities (L3): expressions • all are L1, none are L2 • some are about other L1-entities and some about themselves

35. Ontological Realism makes crucial distinctions • Between data and what data are about; • Between continuants and occurrents: • obvious differences: • a person versus his life • an elevator versus his going up and down • space versus time • more subtle differences (inexistent for flawed models e.g. HL7-RIM): • observation (data-element) versus observing • diagnosis versus making a diagnosis • message versus transmitting a message

36. OBO Foundry ontologies in BFO-dress 36

37. Ontology of General Medical Science First ontology in which the L1/L2/L3 distinction is used Scheuermann R, Ceusters W, Smith B. Toward an Ontological Treatment of Disease and Diagnosis. 2009 AMIA Summit on Translational Bioinformatics, San Francisco, California, March 15-17, 2009;: 116-120. Omnipress ISBN:0-9647743-7-2

38. Motivation • Clarity about: • disease etiology and progression • disease and the diagnostic process • phenotype and signs/symptoms

39. Big Picture

40. Approach • a disease is a disposition rooted in a physical disorder in the organism and realized in pathological processes. produces bears realized_in etiological process disorder disposition pathological process produces diagnosis interpretive process signs & symptoms abnormal bodily features produces participates_in recognized_as

41. Example: Diagnosis • Clinical Picture =def. – A representation of a clinical phenotype that is inferred from the combination of laboratory, image and clinical findings about a given patient. • Diagnosis =def. – • A conclusion of an interpretive process that has as input a clinical picture of a given patient and as output an assertion to the effect that the patient has a disease of such and such a type.

42. Obvious? • ‘Diseases and diagnoses are the principal ways in which illnesses are classified and quantified, and are vital in determining how clinicians organize health care.’ Ann Fam Med 1(1):44-51, 2003. • ‘MedDRA […] is a standardized dictionary of medical terminology [ … which …] includes terminology for symptoms, signs, diseases and diagnoses.’ Medical Dictionary for Regulatory Activities

43. A configuration of representational units; Believed to mirror the person’s disease; Believed to mirror the disease’s cause; Refers to the universal of which the disease is believed to be an instance. Disease isa A well-formed diagnosis of ‘pneumococal pneumonia’ Pneumococcal pneumonia Instance-of at t1 #78 John’s relevant portion of pneumococs #56 John’s Pneumonia caused by

44. Disease Portion of pneumococs caused by isa isa Instance-of at t1 Pneumococcal pneumonia Pneumonia Instance-of at t1 Instance-of at t1 caused by caused by #78 #56 #56 #78 Some motivations and consequences (1) • No use of debatable or ambiguous notions such as proposition, statement, assertion, fact, ... • The same diagnosis can be expressed in various forms.

45. Some motivations and consequences (2) • A diagnosis can be of level 2 or level 3, i.e. either in the mind of a cognitive agent, or in some physical form. • Allows for a clean interpretation of assertions of the sort ‘these patients have the same diagnosis’:  The configuration of representational units is such that the parts which do not refer to the particulars related to the respective patients, refer to the same portion of reality.

46. Distinct but similar diagnoses Pneumococcal pneumonia Instance-of at t1 Instance-of at t2 #78 John’s portion of pneumococs #56 John’s Pneumonia #956 Bob’s pneumonia #2087 Bob’s portion of pneumococs caused by caused by

47. Some motivations and consequences (3) • Allows evenly clean interpretations for the wealth of ‘modified’ diagnoses: • With respect to the author of the representation: • ‘nursing diagnosis’, ‘referral diagnosis’ • When created: • ‘post-operative diagnosis’, ‘admitting diagnosis’, ‘final diagnosis’ • Degree of belief: • ‘uncertain diagnosis’, ‘preliminary diagnosis’

48. The Translational Medicine Ontology C. Denney et.al. Creating a Translational Medicine Ontology. Nature Precedings August 2009.