1. ECO R European Centre for Ontological Research Ontology for Medical Emergency related Resource Location Werner Ceusters European Centre for Ontological Research Universität des Saarlandes Saarbrücken, Germany

2. ECO R European Centre for Ontological Research Presentation overview Professional background Ontology and terminology Concepts as the source of all evil Realist ontology Setting the scene for an ontology of emergency medicine

3. ECO R European Centre for Ontological Research Short personal history 1959 -... 1977 1989 1992 1998 2002 2004

4. ECO R European Centre for Ontological Research European Centre for Ontological Research Local members External members Partners Status April 8, 2005

5. ECO R European Centre for Ontological Research European Centre for Ontological Research DirectorsMember representatives Advisory Board Management Board Status April 8, 2005

6. ECO R European Centre for Ontological Research Institute for Formal Ontology and Medical Information Science an interdisciplinary research group –Philosophy, –Computer and Information Science, –Logic, –Medicine, –Medical Informatics. a center of theoretically grounded research in both formal and applied ontology. Main goal: to develop a formal ontology that will be applied and tested in the domain of medical and biomedical information science.

7. ECO R European Centre for Ontological Research IFOMIS competences Status April 8, 2005

8. ECO R European Centre for Ontological Research “Ontology”

9. ECO R European Centre for Ontological Research If, later, you can remember just one thing of this presentation, then make sure it is this one: If you use the word “ontology”, ALWAYS be specific about what you mean by it.

10. ECO R European Centre for Ontological Research Tom Gruber’s view In the context of knowledge sharing, I use the term ontology to mean a specification of a conceptualization. That is, an ontology is a description (like a formal specification of a program) of the concepts and relationships that can exist for an agent or a community of agents. This definition is consistent with the usage of ontology as set-of-concept-definitions, but more general. And it is certainly a different sense of the word than its use in philosophy. The word "ontology" seems to generate a lot of controversy in discussions about AI. It has a long history in philosophy, in which it refers to the subject of existence. It is also often confused with epistemology, which is about knowledge and knowing.

11. ECO R European Centre for Ontological Research The O-word in science N. Guarino, P. Giaretta, "Ontologies and Knowledge Bases: Towards a Terminological Clarification". In Towards Very Large Knowledge Bases: Knowledge Building and Knowledge Sharing, N. Mars (ed.), pp 25-32. IOS Press, Amsterdam, 1995.

12. ECO R European Centre for Ontological Research The O-word in buzz-speak “An ontology is a classification methodology for formalizing a subject's knowledge or belief system in a structured way. Dictionaries and encyclopedias are examples of ontologies.” (X1) “A terminology (or classification) is a kind of ontology by definition and it should preserve (and "understand") the relationships between the 1,000s of terms in it or else it would become a mere dictionary (or at best a thesaurus).” (X2) “Ontologies are Web pages that contain a mystical unifying force that gives differing labels common meaning.” (X3)

13. ECO R European Centre for Ontological Research Today’s biggest problem: a confusion between “terminology” and “ontology” The conditions to be agreed upon when to use a certain term to denote an entity, are often different from the conditions which make an entity what it is. – Trees would still be different from rabbits even if there were no humans to agree on what names we should use to refer to them “ontos” means “being”. The link with reality tends to be forgotten: one concentrates on the models instead of on the reality.

14. ECO R European Centre for Ontological Research Use Case: Semantic Discovery of Community of Practice COCOON Working Draft 16 Decembre 2004 2.5.1 Ontologies. First of all we need : a set of ontologies that provide the terminology used later. We introduce: an advice service terminology for specifying the action of a general practitioner asking a CoP for an advices, a set of domain terminologies for specifying the case the general practitioner is asking an advice for (in the mock-ups presented in sections sec:mock-up we decide to use a small breast cancer ontology), a date and time terminology for specifying days of the week, hours of the day and intervals required for arranging a meeting, and a terminology of the available communication channels used during the virtual meeting that will take place after the arrangement.

15. ECO R European Centre for Ontological Research Terminology A theory concerned with those aspects of the nature and the functions of language which permit the efficient representation and transmission of items of knowledge (J. Sager) Precise and appropriate terminologies provide important facilities for human communication (J. Gamper)

16. ECO R European Centre for Ontological Research Ontology What it means if we use the word A proposal put forward by the SI roadmap pannel An ontology is a representation of some pre- existing domain of reality which – (1) reflects the properties of the objects 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

17. ECO R European Centre for Ontological Research Copyright 2001, United Feature Syndicate Inc. Reality: not just a matter of view

18. ECO R European Centre for Ontological Research A division of labour Terminology: – Communication amongst humans – Communication between human and machine Ontology: – Representation inside a machine of reality as it exists outside the machine a representation is not a model or a simplification; ‘cats’ is not a simplification of cats – Communication amongst machines – Interpretation by machines

19. ECO R European Centre for Ontological Research Current “state of the art” in biomedical informatics A pervasive bias towards “concepts” – Content wise: Work based on ISO/TC37 that advocates the Ogden-Richards theory of meaning Corresponds with a linguistic reading of “concept” – Architecture wise: In Europe: work based on CEN/TC251 WG1 & WG2 that follow ISO/TC37 In the US: HL7, inspired by Speech Act Theory “Concepts” used as elements of information models, hence mixing a linguistic and engineering reading.

20. ECO R European Centre for Ontological Research “Ontology” An ontology defines the terms used to describe and represent an area of knowledge, and are used by people, databases, and applications that need to share domain information (a domain is a specific subject area, such as health or medicine). OWL Web Ontology Language; Use Cases and Requirements W3C Recommendation 10 February 2004 http://www.w3.org/TR/webont-req/ e-Health - making healthcare better for European citizens: An action plan for a European e-Health Area COM (2004) 356 final, 30.4.2004, p17

21. ECO R European Centre for Ontological Research Ontologies need to specify descriptions for the following kinds of concepts: – Classes (general things) in the many domains of interest – The relationships that can exist among things – The properties (or attributes) those things may have OWL Web Ontology Language; Use Cases and Requirements W3C Recommendation 10 February 2004 http://www.w3.org/TR/webont-req/ “Ontology”

22. ECO R European Centre for Ontological Research Semantic Interoperability Semantic interoperability is the ability for information shared by systems to be understood at the level of formally defined domain concepts so that the information is computer processable by the receiving system – Text used in the CEC documents – Taken over by Artemis

23. ECO R European Centre for Ontological Research ‘Concepts’ are the bad guys: ‘ Concept’ used in ‘ontology’ is used for different things meaning shared in common by synonymous terms idea shared in common in the minds of those who use these terms unit of knowledge describing meanings universal, feature or property shared in common by entities in the world

24. ECO R European Centre for Ontological Research What concepts allow you to do Horse ISA mammal One-horned mammal ISA mammal Rhinoceros ISA one-horned mammal Unicorn ISA one-horned mammal Small horse ISA horse Horse in the zoo of Antwerp ISA horse Horse that won the St.Gallen Steeple Chase in 2005 ISA horse  Facts and fictions run together  Statements disguised as concepts

25. ECO R European Centre for Ontological Research Origine: the semantic triangle In Information Science: – “An ontology is a description (like a formal specification of a program) of the concepts and relationships that can exist for an agent or a community of agents.” In Philosophy: – “Ontology is the science of what is, of the kinds and structures of objects, properties, events, processes and relations in every area of reality.” concept termreferent

26. ECO R European Centre for Ontological Research The price you pay if you go for concepts... (just one example) UMLS Semantic Network – What does A relation B means ? – Normally: for all a’s that are A’s, there is some b that is a B, such that the relation holds from a to b – Very relaxed: for some a’s there might be a b such that a relation b – But even that doesn’t work for the relationship prevents

27. ECO R European Centre for Ontological Research Ok, some more. It’s just too funny... UMLS-SN: – Bacterium causes Experimental model of disease – Educational activity associated with pathologic function HL7: Individual Allele is_a Act of Observation GO: Menopause part_of Death GALEN: – Female Pelvic Cavity Contains Uterus (this is ok, but compare...) – Vomitus Contains Carrot – Speech Contains Verbal Statement

28. ECO R European Centre for Ontological Research ‘Well, that’s because they don’t use description logics or OWL’ SNOMED-RT (2000) SNOMED-CT (2003) DL don’t guarantee you to get parthood right ! You really think so ?

29. ECO R European Centre for Ontological Research F-DL (Frankenstein’s DL)

30. ECO R European Centre for Ontological Research Our way: Realist Ontology Central are the “particulars” (p) – Me, you, my heart, that patient’s fracture, that car accident (which caused his fracture),… – ‘Referent tracking’ Particulars instanciate classes (c) distinguished on the basis of ontological properties: – Essence, dependency, identity, relationship with time, … – Some classes are “universals” (u) Define relationships axiomatically at four levels: – p – p, c – c, p – c, c – p

31. ECO R European Centre for Ontological Research BFO continuants

32. ECO R European Centre for Ontological Research Kinds of relations : – my heart part_of me : – me instance_of human being : – president of the US empowered_by US constitution (?) : – gene expression has_agent RNA polymerase

33. ECO R European Centre for Ontological Research Parthood as a Relation between Instances Introduced as primitive: – p part_of p1 Illustrated in assertions such as: – My heart part_of Werner Ceusters Properties: – reflexivity: for all p, p part_of p, – anti-symmetry: for all p, p1, if p part_of p1 and p1 part_of p then p and p1 are identical, – transitivity: for all p, p1, p2, if p part_of p1 and p1 part_of p2, then p part_of p2.

34. ECO R European Centre for Ontological Research Parthood as a Relation between Classes For continuants: (‘heart’, ‘person’) – C part_of C1 =def. for all c, t, if c instance_of C at t then there is some c1 such that c1 instance_of C1 at t and c part_of c1 at t. For processes: (‘menopauze’, ‘aging’) – P part_of P1 =def. for all p, if p instance_of P, then there is some p1 such that: p1 instance_of P1 and p part_of p1. These definitions tell you ONLY something about C’s and P’s, but nothing about C1’s and P1’s !!!

35. ECO R European Centre for Ontological Research Possible variants R 1 (A, B) =:  x (Inst(x, A)   y(Inst(y, B) & Rxy)) –every A stands in relation R to some B R 2 (A, B) =:  y (Inst(y, B)   x(Inst(x, A) & Rxy)) –for each B there is some A that stands in relation R to it R 12 (A, B) =: R 1 (A, B) & R 2 (A, B) –every A stands in relation R to some B and for each B there is some A that stands in relation R to it Donnelly and Bittner, 2005

36. ECO R European Centre for Ontological Research Properties of relations among individuals vs. properties of relations among classes Among Individuals Among Classes R is...R 1 must also be...? R 2 must also be...? R 12 must also be...? ReflexiveYes IrreflexiveNo SymmetricNo Yes AsymmetricNo AntisymmetricNo TransitiveYes Donnelly and Bittner, 2005

37. ECO R European Centre for Ontological Research GALEN assertions using isDivisionOF and hasDivision GALEN ’ s isDivisionOf assertion BIT+Cl relation GALEN ’ s hasDivision BIT+Cl relation Female Pelvic Cavity isDivisionOf Pelvic Part of Trunk PP 1 none Prostate Gland isDivisionOf Genito-Urinary System PP 1 none Pelvic Part of Trunk hasDivision Hair (PP -1 ) 1 LeftHeartVentricle isDivisionOf Heart PP 12 Heart hasDivision LeftHeartVentricle (PP -1 ) 12 Prostate Gland isDivisionOf Male Genito-Urinary System PP 12 Male Genito-Urinary System hasDivision Prostate Gland (PP -1 ) 12 Urinary Bladder isDivisionOf Genito-Urinary System PP 12 none Pericardium isDivisionOf Heart none Heart hasDivision Pericardium none Donnelly and Bittner, 2005

38. ECO R European Centre for Ontological Research Realist Ontology is alive The gossip: – We are holding biomedical ontology in a strangle hold The success stories (some recent examples) : – Contributing to OBO ontologies requires adherence to the relations defined in Relations in Biomedical Ontologies, forthcoming in Genome Biology – Foundational Medical Anatomy (FMA) completely reworked, and basis for forthcoming CEN standard – Previous IFOMIS collaborator hired by NLM to work on revision of Semantic Network – Barry Smith appointed by De Soto (Institute for Liberty and Democracy), funded by US Agency for International Development, to establish the philosophical underpinnings of property right.

39. ECO R European Centre for Ontological Research Towards an ontology for medical emergencies Preliminary thoughts to start discussion

40. ECO R European Centre for Ontological Research DICOEMS ontology use case Main goal: – locating the suitable resources and experts that can treat the specific medical emergency case that the paramedics face in the ambulance. Scenario: – expert in Emergency Center enters search terms in natural language based on input from paramedics on site and telemedicine equipment – NLP processing of input to retain relevant words and their synonyms (WordNet processing). – These words are used to retrieve concepts, terms and relations from an ‘ontology’ about cardiovascular diseases – Ontology entries are linked to available resources (hospitals, departments and experts) – Search output: in XML, concepts + codes that will form the input for the Resources mapping module.

41. ECO R European Centre for Ontological Research What are the particulars ? The particulars of the ‘current case’ – The victim The disorder(s) that constitute(s) the emergency case His personal history... – Time and place – The on site team It’s experience, skills,...... – On site equipment – The emergency centre specialist –... The particulars of previous cases – Same as above, plus...... outcomes Referent tracking

42. ECO R European Centre for Ontological Research Useful source for inspiration: Emergency Data Sets Framework ISO TC 215/SC N Date: 2003-05-06 ISO/PDTR 1 ISO TC 215/SC /WG 1 Secretariat: ANSI An approach and tool to describe the world of data sets within the domain of health informatics.

43. ECO R European Centre for Ontological Research Emergency Medical Service Clinical & Interventional Chief complaint Cause of injury Provider's impressions Pre-existing condition Signs and symptoms Injury description Injury intent Safety equipment / protection (seatbelt) Factors affecting EMS delivery of care Alcohol/drug use Trauma Score Procedure or treatment Medication name Treatment authorization Destination – Hospital case number – Physician/Nurse accepting patient – Time dispatched CPR – Vital signs – Time of first CPR – Provider of first CPR – Time CPR discontinued – Time of witnessed cardiac arrest – Witness to cardiac arrest – Time of first defibrillatory shock – Return of spontaneous circulation – Pulse, heart rate, rhythm – Respiratory rate – Respiratory effort – Blood pressure – Skin perfusion Mental status – Glasgow eye-opening component – Glasgow verbal component – Glasgow motor component – Glasgow Coma – Psychological score (CRAMS)

44. ECO R European Centre for Ontological Research The division of labour Ontology: – Identification of relevant particulars and classes – Identification and definition of relevant relationships at all levels – Adequate representation Terminology: – Description of particulars, classes and relationships using natural language (terms) – Links to literature, databases, resource descriptions Machine – machine interfaces Man – machine interfaces