1. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 3D Anatomical Human – EU Marie Curie Research Network Realism-based Ontology for Building Three-dimensional Functional Models of Human Motion 3rd General Meeting – London, UK – October 5th, 2007 Werner CEUSTERS, MD Center of Excellence in Bioinformatics and Life Sciences Department of Psychiatry, University at Buffalo, NY, USA http://www.org.buffalo.edu/RTU

2. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 2 Short personal history 1959 -... 1977 1989 1992 1998 2002 2004 2006

3. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 3 Research areas Realism- based Ontology Referent Tracking What is generic What is specific Instance-of

4. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 4 Context of this presentation Goal of the 3D Anatomical Human project: –modelling and simulation of human body for medical purposes –change our understanding of musculoskeletal motion –associate functional models of human physiology, biomechanics and motion to the patient-specific shape of the corresponding anatomical structures. My goal: –Set the scene for high quality ontology development in the context of modelling and simulation of the human body

5. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 5 Presentation overview ‘Traditional’ ontology approaches and associated problems Realism-based ontology: –Fundamental principles –Basic entities: particulars and universals –Relationships –Ontology evolution

6. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Concept-based ontologies

7. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 7 An unfortunate perception of ‘ontology’ The most widespread view of what an ontology is, is that of ‘an explicit specification of the conceptualization of a domain’ (Gruber), often complemented with the notion of ‘agreement’.

8. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 8 Central in this view are ‘concepts’ But what the word ‘concept’ denotes, is never clarified and users of it often refer to different entities in a haphazard way: meaning shared in common by synonymous terms idea shared in common in the minds of those who use these terms unit of describing meanings knowledge universal that what is shared by all and only all entities in reality of a similar sort Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, Biomedical Ontology in Action, November 8, 2006, Baltimore MD, USA

9. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 9 Central in this view are ‘concepts’ But what the word ‘concept’ denotes, is never clarified and users of it often refer to different entities in a haphazard way: meaning shared in common by synonymous terms idea shared in common in the minds of those who use these terms unit of describing meanings knowledge universal that what is shared by all and only all entities in reality of a similar sort These views require the involvement of a cognitive entity:

10. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 10 Central in this view are ‘concepts’ But what the word ‘concept’ denotes, is never clarified and users of it often refer to different entities in a haphazard way: meaning shared in common by synonymous terms idea shared in common in the minds of those who use these terms unit of describing meanings knowledge universal that what is shared by all and only all entities in reality of a similar sort These views require the involvement of a cognitive entity: This view does not presuppose cognition at all

11. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 11 Concept-orientation in ontology has sad consequences Too much effort goes into the specification business –OWL, DL-reasoners, translators and convertors, syntax checkers,... Too little effort into the faithfulness of the conceptualizations towards what they represent. –Pseudo-separation of language and entities “absent nipple” Many ‘ontologies’ and ontology-like systems exhibit mistakes of various sorts.

12. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Realism-based ontology: reality comes first, representation is second.

13. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 13 Ontologies as representations of reality A taxonomy: is a tree-form graph-theoretic representational artifact with nodes representing universals or classes and edges representing isa or subset relations. An ontology: is a representational artifact, comprising a taxonomy as proper part, whose representational units are intended to designate some combination of universals, defined classes, and certain relations between them. A realism-based ontology: is built out of representational units which are intended to refer exclusively to universals, and corresponds to that part of the content of a scientific theory that is captured by its constituent general terms and their interrelations. Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, Biomedical Ontology in Action, November 8, 2006, Baltimore MD, USA

14. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 14 Three levels of reality 1.The world exists ‘as it is’ prior to a cognitive agent’s perception thereof; Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, November 8, 2006, Baltimore MD, USA

15. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 15 Reality exist before any observation R

16. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 16 Reality exist before any observation Humans had a brain well before they knew they had one. Trees were green before humans started to use the word “green”. R And also most structures in reality are there in advance.

17. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 17 Three levels of reality 1.The world exists ‘as it is’ prior to a cognitive agent’s perception thereof; 2.Cognitive agents build up ‘in their minds’ cognitive representations of the world; Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, November 8, 2006, Baltimore MD, USA

18. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 18 The ontology author acknowledges the existence of some Portion Of Reality (POR) R B

19. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 19 R B Some portions of reality escape his attention.

20. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 20 Three levels of reality 1.The world exists ‘as it is’ prior to a cognitive agent’s perception thereof; 2.Cognitive agents build up ‘in their minds’ cognitive representations of the world; 3.To make these representations publicly accessible in some enduring fashion, they create representational artifacts that are fixed in some medium. Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, November 8, 2006, Baltimore MD, USA

21. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 21 R He represents only what he considers relevant O B #1 RU 1 B1 RU 1 O1 Both RU 1 B1 and RU 1 O1 are representational units referring to #1; RU 1 O1 is NOT a representation of RU 1 B1 ; RU 1 O1 is created through concretization of RU 1 B1 in some medium.

22. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 22 Thus... These concretizations are NOT supposed to be the representations of these cognitive representations; “concept representation” We should not be in the business of

23. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 23 Some characteristics of an optimal ontology Each representational unit in such an ontology would designate –(1) a single portion of reality (POR), which is –(2) relevant to the purposes of the ontology and such that –(3) the authors of the ontology intended to use this unit to designate this POR, and –(4) there would be no PORs objectively relevant to these purposes that are not referred to in the ontology.

24. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 24 Basic components of a realist view of the world The world consists of –entities that are Either particulars or universals; Either occurrents or continuants; Either dependent or independent; and, –relationships between these entities of the form e.g. is-instance-of, lacks e.g. is-member-of, is-part-of e.g. isa (is-subtype-of) Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, November 8, 2006, Baltimore MD, USA

25. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 25 The example to work (partially) out: ‘walking’ methis walking Has-participant at t 2 human being Instance-of at t living creature Is_a walking Instance-of my left leg part-of at t this leg moving leg moving part-of leg to make me walk function process Instance-of at t Instance-of at t Is_a Instance-of Has- Participant at t Is-realized- In at t Has-function at t

26. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Basic entities in realism-based ontology: three main distinctions 123

27. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 27 Particulars methis walking my left leg this leg moving to make me walk Individual entities that carry identity and preserve their identity over time 1

28. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 28 Universals human being living creature walkingleg moving leg function process Entities which exist “in” the particulars amongst which there is a relation of similarity not found with other particulars 1

29. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 29 Particulars and Universals methis walking my left leg this leg moving to make me walk human being living creature walkingleg moving leg function process Instance-of at t Instance-of at t Instance-of at t Instance-of 1

30. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 30 Continuants and Occurrents methis walking my left leg this leg moving to make me walk human being living creature walkingleg moving leg function process Instance-of at t Instance-of at t Instance-of at t Instance-of 2

31. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 31 Continuants me human being Instance-of at t my left leg leg to make me walk function Instance-of at t Instance-of at t Continuants are entities which endure (=continue to exist) while undergoing different sorts of changes, including changes of place. While they exist, they exist “in total”. 2

32. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 32 Preserving identity through change childadult caterpillarbutterfly t human being animal living creature me Instance-of in 1960 Instance-of since 1980 2

33. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 33 Occurrents this walking walking Instance-of this leg moving leg moving Instance-of Occurrents are changes. Occurrents unfold themselves during temporal phases. At any point in time, they exist only in part. 2

34. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 34 Independent versus dependent methis walking human being Instance-of at t living creature Is_a walking Instance-of my left leg this leg moving leg moving leg to make me walk function process Instance-of at t Instance-of at t Is_a Instance-of 3

35. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 35 Independent versus dependent Independent entities Do not require any other entity to exist to enable their own existence Dependent entities Require the existence of another entity for their existence methis walking my left leg this leg moving to make me walk 3

36. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 36 Independent versus dependent Independent entities Do not require any other entity to exist to enable their own existence Dependent entities Require the existence of another entity for their existence methis walking my left leg this leg moving to make me walk Independent continuants Dependent continuants Occurrents (are all dependent) 3

37. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 37 Dependent continuants Realized –Quality:redness (of blood) Realizable –Function:to flex (of knee joint) –Role:student –Power:boss –Disposition:brittleness (of a bone) 3

38. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 38 Dependent continuants Realized –Quality:redness (of blood) Realizable –Function:to flex (of knee joint) –Role:student –Power:boss –Disposition:brittleness (of a bone) Realizations flexing studying ordering breaking continuantsoccurrents 3

39. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Relations in realism-based ontology Smith B, Ceusters W, Klagges B, Koehler J, Kumar A, Lomax J, Mungall C, Neuhaus F, Rector A, Rosse C. Relations in biomedical ontologies, Genome Biology 2005, 6:R46.Relations in biomedical ontologies

40. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 40 Basic sorts of relationships universal particular ?

41. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 41 Universals and classes universal PPPP PPPP PPPP instance-of member-of extention-of Defined class

42. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 42 General principle about relationships All universal level relationships are defined on the basis of particular level relationships

43. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 43 Primitive instance-level relationships c instance_of C at t - a primitive relation between a continuant instance and a class which it instantiates at a specific time p instance_of P - a primitive relation between a process instance and a class which it instantiates holding independently of time c part_of c1 at t - a primitive relation between two continuant instances and a time at which the one is part of the other p part_of p1, r part_of r1 - a primitive relation of parthood, holding independently of time, either between process instances (one a subprocess of the other), or between spatial regions (one a subregion of the other) c located_in r at t - a primitive relation between a continuant instance, a spatial region which it occupies, and a time r adjacent_to r1 - a primitive relation of proximity between two disjoint continuants t earlier t1 - a primitive relation between two times c derives_from c1 - a primitive relation involving two distinct material continuants c and c1 p has_participant c at t - a primitive relation between a process, a continuant, and a time p has_agent c at t - a primitive relation between a process, a continuant and a time at which the continuant is causally active in the process

44. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 44 Is_a is defined over instance-of (1) For continuants C is_a C1 = [definition] for all c, t, if c instance_of C at t then c instance_of C1 at t. For occurrents P is_a P1 = [definition] for all p, if p instance_of P then p instance_of P1.

45. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 45 Is_a is defined over instance-of (2) human being living creature me universals particulars is_a instance-of at t

46. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 46 Is_a is defined over instance-of (3) childadultcaterpillarbutterfly human being living creature animal me More than subset or inclusion ! is_a Instance-of t1t2

47. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 47 Transformation Derivation continuation fusion fission

48. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 48 Part-of different for continuants and occurrents methis walking human being Instance-of at t living creature Is_a walking Instance-of my left leg this leg moving leg moving leg process Instance-of at t Is_a Instance-of part-of at t part-of

49. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 49 Part-of can be generalized, … with care ! me human being Instance-of at t living creature Is_a my left leg part-of at t leg Instance-of at t C part_of C1 = [def] for all c, t, if Cct then there is some c1 such that C1c1t and c part_of c1 at t. Cct = c instance-of C at t

50. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 50 Part-of can be generalized, … with care ! me human being Instance-of at t living creature Is_a my left leg part-of at t leg Instance-of at t C part_of C1 = [def] for all c, t, if Cct then there is some c1 such that C1c1t and c part_of c1 at t. Cct = c instance-of C at t Part-of ?

51. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 51 Part-of can be generalized, … with care ! me human being Instance-of at t living creature Is_a my left leg part-of at t leg Instance-of at t Horse legs are not parts of human beings Amputated legs are not parts of human beings ‘Canonical leg is part of canonical human being’, but…, there are (very likely) no such particulars … Part-of ?

52. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 52 Generalization of temporal parthood this walking walking Instance-of this leg moving leg moving process Is_a Instance-of part-of P part_of P1 = [definition] –for all p, –if Pp –then there is some p1 such that: P1p1 and p part_of p1

53. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 53 Two sorts of temporal parthood (1) methis walking Has-participant at t 2 walking Instance-of my left leg part-of at t this leg moving leg moving part-of process Is_a Instance-of Has- Participant at t ‘longitudinal’: one process evolves as part of another one. May involve stronger relationships of other types, e.g. causal

54. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 54 Two sorts of temporal parthood (2) Cuts cross temporal entities this walking this leg moving this foot moving t

55. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 55 Functions and functionings methis walking Has-participant at t 2 human being Instance-of at t living creature Is_a my left leg part-of at t leg to make me walk function Instance-of at t Instance-of at t Is-realized- in at t Has-function at t Functions are not realized all the time. Functions remain functions even after their realization becomes impossible.

56. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U Ontology evolution

57. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 57 Reality versus beliefs, both in evolution t U1 U2 p3 Reality

58. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 58 Reality versus beliefs, both in evolution IUI-#3 O-#2 O-#1 t U1 U2 p3 Reality Belief O-#0 = “denotes” = what constitutes the meaning of representational units …. Therefore: O-#0 is meaningless

59. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 59 Relevance It shows … – the complex interrelationships between What is the case; What we know about what is the case; What parts about what we know that is the case we wish to refer to in ontologies and repositories. –the need to update ontologies and repositories in line with various sorts of changes.

60. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 60 Key requirement for ontology versioning Any change in an ontology or data repository should be associated with the reason for that change to be able to assess later what kind of mistake has been made !

61. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 61 Types of mismatches changes in the underlying reality (does the appearance or disappearance of an entry in a new version of an ontology relate to the appearance or disappearance of entities or of relationships among entities?); changes in our scientific understanding; reassessments of what is relevant for inclusion in an ontology; encoding mistakes introduced during ontology curation (for example through erroneous introduction of duplicate entries reflecting lack of attention to differences in spelling).

62. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 62 Reality versus beliefs, both in evolution t U1 U2 p3 IUI-#3 O-#2 O-#1 R B O-#0 Several types of mismatches between reality and an ontology

63. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 63 And in this, I thus far ignored … t U1 U2 p3 IUI-#3 O-#2 O-#1 R B O-#0 Relationships amongst universals (R) or beliefs therein (B)

64. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 64 Mistakes, discoveries, being lucky, having bad luck t U1 U2 p3 IUI-#3 O-#2 O-#1 R B O-#0 Mistakes

65. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 65 Mistakes, discoveries, being lucky, having bad luck t U1 U2 p3 IUI-#3 O-#2 O-#1 R B O-#0 discoveries

66. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 66 Mistakes, discoveries, being lucky, having bad luck t U1 U2 p3 IUI-#3 O-#2 O-#1 R B O-#0

67. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 67 Mistakes, discoveries, being lucky, having bad luck t U1 U2 p3 IUI-#3 O-#2 O-#1 R B O-#0

68. New York State Center of Excellence in Bioinformatics & Life Sciences R T U New York State Center of Excellence in Bioinformatics & Life Sciences R T U 68 Conclusion 3D anatomical and physiologic modeling require ontologies and associated reasoning mechanisms that –can deal with three- and four-dimensional entities; –treat reality and knowledge thereof appropriately; –keep track of changes in reality, including what is believed. Realism-based ontologies can meet these expectations but the development of them requires specific skills and competencies.