R T U New York State Center of

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 3 D Anatomical Human – EU Marie Curie Research Network Realism-based Ontology for Building Three-dimensional Functional Models of Human Motion 3 rd General Meeting – London, UK – October 5 th, 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

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

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

R T U New York State Center of Excellence in Bioinformatics & Life Sciences Context of this presentation • Goal of the 3 D 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 4

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

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

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 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’. 7

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 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 • idea shared in common by synonymous terms shared in common in the minds of those who use these terms describing meanings • unit of 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 8

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 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: These views require the involvement of a cognitive entity: • 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 9

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 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: These views require the involvement of a cognitive entity: • 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 This view does not presuppose cognition at all 10

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 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. 11

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

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 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 13

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 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 14

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

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 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. 16

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 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 17

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

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

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

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

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

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 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. 23

R T U New York State Center of Excellence in Bioinformatics & Life Sciences Basic components of a realist view of the world • The world consists of – entities that are • Either particulars or universals; • Either occurrents or continuants; and, – relationships between these entities of the form • Either dependent or independent; • <particular , universal> • <particular , particular> • <universal , universal> 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 24

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

R T U New York State Center of Excellence in Bioinformatics & Life Sciences Basic entities in realism-based ontology: three main distinctions 1 2 3

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

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

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

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

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 2 Continuants function leg human being Instance-of at t my left leg me Instance-of at t to make me walk 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”. 31

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

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

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

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 3 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 to make me walk this leg moving my left leg me this walking 35

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

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

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

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 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: R 46.

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

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

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

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 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 c 1 at t - a primitive relation between two continuant instances and a time at which the one is part of the other p part_of p 1, r part_of r 1 - 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 r 1 - a primitive relation of proximity between two disjoint continuants t earlier t 1 - a primitive relation between two times c derives_from c 1 - a primitive relation involving two distinct material continuants c and c 1 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 43

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

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

R T U New York State Center of Excellence in Bioinformatics & Life Sciences Is_a is defined over instance-of (3) More than subset or inclusion ! living creature is_a human being animal child is_a adult is_a caterpillar butterfly Instance-of t 1 t 2 me 46

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

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

R T U New York State Center of Excellence in Bioinformatics & Life Sciences Part-of can be generalized, … with care ! living creature Is_a leg human being Instance-of at t part-of at t me Instance-of at t C part_of C 1 = [def] for all c, t, if Cct then there is some c 1 such that C 1 c 1 t and c part_of c 1 at t. my left leg Cct = c instance-of C at t 49

R T U New York State Center of Excellence in Bioinformatics & Life Sciences Part-of can be generalized, … with care ! living creature Is_a human being Instance-of at t part-of at t me ? leg Part-of Instance-of at t C part_of C 1 = [def] for all c, t, if Cct then there is some c 1 such that C 1 c 1 t and c part_of c 1 at t. my left leg Cct = c instance-of C at t 50

R T U New York State Center of Excellence in Bioinformatics & Life Sciences Part-of can be generalized, … with care ! living creature Is_a human being Instance-of at t part-of at t me ? leg Part-of Instance-of at t my left leg • 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 • … 51

R T U New York State Center of Excellence in Bioinformatics & Life Sciences Generalization of temporal parthood • P part_of P 1 = [definition] – for all p, – if Pp – then there is some p 1 such that: P 1 p 1 and p part_of p 1 process Is_a leg moving walking Instance-of this leg moving part-of Instance-of this walking 52

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

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

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

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

R T U New York State Center of Excellence in Bioinformatics & Life Sciences Reality versus beliefs, both in evolution t U 1 Reality U 2 p 3 57

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

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 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. 59

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 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 ! 60

R T U New York State Center of Excellence in Bioinformatics & Life Sciences 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). 61

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

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

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

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

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

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

R T U New York State Center of Excellence in Bioinformatics & Life Sciences Conclusion • 3 D 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. 68