2. ifomis.org 1 Die Ontologie biomedizinischer Daten Barry Smith Institute for Formal Ontology and Medical Information Science

3. ifomis.org 2 IFOMIS Institute for Formal Ontology and Medical Information Science Mission: to develop formal ontologies to support empirical research in biomedical informatics and in the life sciences in general

4. ifomis.org 3 Biomedical ontologies and terminology systems currently manifest a very low degree of formal rigour

5. ifomis.org 4 SNOMED-CT 900,000 ‘concepts’ and relations between them, such as is_a (for class subsumption) part_of causes treats

6. ifomis.org 5 SNOMED’s confused treatment of is_a beide_Hoden is_a Hoden beide_ Gebärmuttern is_a Gebärmutter

7. ifomis.org 6 Halbextraktion_aus_Steißlage is_a Extraktion_aus_Steißlage Extraktion_aus_Steißlage is_a vollständige_Steißgeburt ____________________________ Halbextraktion_aus_Steißlage is_a vollständige_Steißgeburt

8. ifomis.org 7 Confused treatment of objects and processes diagnostische_endoskopische_Untersuchung _eines_Mediastinums_NOS is_a Mediastinoskop.

9. ifomis.org 8 Confusion of object with knowledge about object Kontrazeption is_a funktionaler_Befund

10. ifomis.org 9 National Cancer Institute Thesaurus a biomedical thesaurus created specifically to meet the needs of the NCI semantically modeled cancer-related terminology built using Description Logic

11. ifomis.org 10 NCI Thesaurus root concepts Anatomic Structure, Anatomic System, or Anatomic Substance ? Or ? Does the NCI not know to which category Any item classified there belongs ? Anatomic Substance ? If yes, why is gene product not subsumed by it ? If no, why are drugs and chemicals not subsumed by it ?

12. ifomis.org 11 Conceptual entity Definition: none Semantic type: –Conceptual entity –Classification Subconcepts: –Action: definition: action; a thing done –And: Definition: an article which expresses the relation of connection or addition, used to conjoin a word with a word,...

13. ifomis.org 12 Action is_a Conceptual Entity And is_a Conceptual Entity Swimming is healthy and contains 8 letters Conceptual entity

14. ifomis.org 13 Definition of “cancer gene”

15. ifomis.org 14 NCI Thesaurus architecture Disease BreastBreast neoplasm Disease-has-associated-anatomy ISA Findings-And- Disorders-Kind Anatomy-Kind “Formal subsumption” or “inheritance” “Associative” relationships providing “differentiae” “Kinds” restrict the domain and range of associative relationships What diseases have a diameter of over 3 cm ?

16. ifomis.org 15 Confusion of objects and the states in which they participate Disease BreastBreast neoplasm Disease-has-associated-anatomy ISA Findings-And- Disorders-Kind Anatomy-Kind

17. ifomis.org 16 No one knows what ‘concept’ (or ‘conceptualization’) means 1.The linguistic reading 2.The psychological reading 3.The epistemological reading 4.The ontological reading

18. ifomis.org 17 1) The linguistic reading A concept is a meaning that is shared in common by a collection of synonymous terms

19. ifomis.org 18 Unified Medical Language System is_a = def. If one item ‘is_a’ another item then the first item is more specific in meaning than the second item.

20. ifomis.org 19 Fruit Orange Vegetable similarTo Apfelsine synonymWith NarrowerTerm Goble & Shadbolt Semantic Networks

21. ifomis.org 20 The linguistic reading is bad for work on ontologies in support of research in the natural sciences / evidence-based medicine

22. ifomis.org 21 Problem of evaluation a good ontology/terminology/vocabulary = one which corresponds to reality as it exists beyond our concepts if an ontology is a mere network of meanings, then the distinction between good and bad ontologies loses its foothold

23. ifomis.org 22 angel or devil are perfectly good concepts so are cancelled performance avoided meeting prevented pregnancy imagined mammal alien implant removal Chios energy healing

24. ifomis.org 23 The linguistic reading yields a more or less coherent reading of relations like: ‘is_a’ ‘synonymous_with’ ‘associated_to’ but it fails miserably when it comes to relations of other types

25. ifomis.org 24 part_of heart part_of human human heart part_of human testis part_of human human testis part_of human but not: human has_part human testis

26. ifomis.org 25 how can concepts, on the linguistic reading, figure as relata of relations like: part_of = def. composes, with one or more other physical units, some larger whole contains =def. is the receptacle for fluids or other substances

27. ifomis.org 26 How can a set of synonymous terms serve as a receptacle for fluids or other substances?

28. ifomis.org 27 The psychological reading of ‘concept’ Concepts are ideas in the minds of human subjects

29. ifomis.org 28 Eugen Wüster 1935 Professor of Woodworking Machinery in the Vienna Agricultural College

30. ifomis.org 29 Eugen Wüster Terminology- hobbyist and founder of International Standards Organization Technical Committee 37

31. ifomis.org 30 International Standard Bad Philosophy Wüster: concepts are inside people’s brains  ISO terminology standards

32. ifomis.org 31 Wüster a concept is a mental surrogate of a plurality of objects grouped together on the basis of perceived similarities and what makes those objects similar is another concept (Turtles all the way down)

33. ifomis.org 32 ISO: Terminologists should still postulate ‘concepts’ even when they have no idea of what the terms in question mean In the domain of woodworking equipment we can see the similarities between groups of objects to which general terms are assigned. Not so in medicine (consider: a carcinoma, or an embryo, in the successive phases of its development)

34. ifomis.org 33 Wüster / ISO on ‘objects’ object = def. anything to which human thought is or can be directed... whether material or immaterial, real or purely imagined ISO: In the course of producing a terminology, philosophical discussions on whether an object actually exists in reality … are to be avoided.

35. ifomis.org 34 3) The epistemological reading Concepts are ‘units of knowledge’ as in ‘knowledge modeling’, ‘knowledge representation’, ‘knowledge-intense disciplines’ Even errors are ‘knowledge’ on this reading – so here, too, the concept orientation draws as too far away from empirical science and too close to delusion and myth

36. ifomis.org 35 Against ‘knowledge representation’ Not ‘KNOWLEDGE-BASED SYSTEMS’ but ‘true-or-false-belief-based systems’

37. ifomis.org 36 Concepts are Triply Ethereal because they are simultaneously supposed to be 1.software proxies for entities in reality (some ghostly diabetes counterpart is needed – because “you can’t get the diabetes itself inside the computer”) 2. the ‘knowledge’ (ideas and beliefs) in the minds of human experts 3. the meanings of the terms such experts use

38. ifomis.org 37

39. ifomis.org 38 4) The ontological reading concepts are not creatures of cognition or of computation they are invariants out there in reality Better: they are what philosophers call types, kinds, universals

40. ifomis.org 39 is_a human is_a mammal all instances of the universal human are instances of the universal mammal is_a defined in terms of the primitive relation of instantiation between a particular and a universal

41. ifomis.org 40 part_of defined in terms of the primitive relation of mereological parthood defined between one instance and another (for example between Mary and her heart) A part_of B =def. given any instance a of A there is some instance b of B such that a part_of b

42. ifomis.org 41 inverse relations nucleus part_of cell cell has_part nucleus

43. ifomis.org 42 All-some definitions of relations between universals A adjacent_to B =def all instances of A are adjacent to (in the instance-level sense) some instance of B

44. ifomis.org 43 Ajacency as a relation between universals is not symmetrical nucleus adjacent_to cytoplasm Not: cytoplasm adjacent_to nucleus seminal vesicle adjacent_to urinary bladder Not: urinary bladder adjacent_to seminal vesicle

45. ifomis.org 44 Evaluation Bad ontologies are (inter alia) those whose general terms lack the relation to corresponding universals in reality, and thereby also to corresponding instances.

46. ifomis.org 45 Good ontologies = representations of universals and particulars in reality

47. ifomis.org 46 ? The concept diabetes mellitus becomes ‘associated with a diabetic patient’ concept patient concept diabetes what it is on the side of the patient ?

48. ifomis.org 47 ? The concept diabetes mellitus becomes ‘associated with a diabetic patient’ concept patient concept diabetes what it is on the side of the patient ? what is the relation here?

49. ifomis.org 48 what it is on the side of the patient Make this our starting point + substance accident

50. ifomis.org 49 A bottom-up approach begin with what confronts the physician at the point of care (or in the lab): instances in reality (patients, disorders, pains, fractures,...) = the what it is on the side of the patient and build up to terminologies from there

51. ifomis.org 50 What happens when a new disorder first begins to make itself manifest? physicians delineate a certain family of cases manifesting a new pattern of symptoms... hypothesis: they are instances of a single universal or kind (this universal still hardly understood) but already: need for a new term (e.g. ‘AIDS’)

52. ifomis.org 51 ‘SARS’ not: severe acute respiratory syndrome but: this particular severe acute respiratory syndrome, instances of which were first identified in Guangdong in 2002 and caused by instances of this particular coronavirus whose genome was first sequenced in Canada in 2003

53. ifomis.org 52 Users can point to instances in the lab or clinic – but not yet to universals The terminologist plugs the gap by postulating concepts instead

54. ifomis.org 53 Users can point to instances in the lab or clinic – but not yet to universals (The terminologist plugs the gap by postulating concepts instead)

55. ifomis.org 54 It’s sometimes hard to grasp the universals in reality to which our general terms refer. So, let’s guarantee that every general term ‘w’ has a precisely tailored referent: ‘the concept w’ We can then forget the messy job of coming to grips with reality, and substitute instead the more pleasant job of grasping the conceptual entities we ourselves have created

56. ifomis.org 55 Better: terminology building should start from the instances that we apprehend in the lab or clinic Assertions in scientific texts pertain to universals in reality Assertions in the EHR pertain to instances of these universals

57. ifomis.org 56 Universals are those invariants in reality which make possible the use of general terms in scientific inquiry and the use of standardized tests and standardized therapies in clinical care

58. ifomis.org 57 Universals have instances SNOMED CT comprehends universals in the realms of disorders, symptoms, anatomical structures,... In each case we have corresponding instances = the what it is on the side of the patient but such instances are poorly recorded in EHRs so far

59. ifomis.org 58 The Great Task of Terminology Building in an Age of Evidence-Based Medicine Terminology work should start with instances in reality, and seek to build up from there to align our terms with the corresponding universals We can then abandon the detour through concepts altogether

60. ifomis.org 59 Terminologies should be aligned not with concepts but with universals in reality including the universals instituted by therapies, acts of measurement, portions of bodily substance, etc.

61. ifomis.org 60 Define a node of a terminology: with p a preferred term (string) S p a set of synonyms d an (optional) definition Define a terminology: T = N a set of nodes L a set of links (graph-theoretical edges) v a version number

62. ifomis.org 61 The ideal: one-to-one correspond between nodes and universals in reality Problem: bad terms (‘phlogiston’, ‘diabetes’) At any given stage we will have: N = N1  N>  N< where N1 = terms which correspond to exactly one universal N> = terms which correspond to more than one universal N< = terms which correspond to less than one universal

63. ifomis.org 62 The belief in scientific progress with the passage of time, N> and N< will become ever smaller, so that N1 will approximate ever more closely to N * Assumption: the vast bulk of the beliefs expressed / presupposed in biomedical texts are true. Hence N1 already constitutes a very large portion of N (the collection of terms already in general use). *modulo the fact that the totality of universals will itself change with the passage of time

64. ifomis.org 63 There are hearts

65. ifomis.org 64 But science is an asymptotic process At all stages prior to the ideal end to our labors, we will not know where the boundaries between N1, N are to be drawn

66. ifomis.org 65 We do not know how the terms are presently distributed between N1, N, So: is the distinction of purely theoretical interest – a matter of abstract (philosophical) housekeeping ?

67. ifomis.org 66 We typically have at our disposal a whole developing series of versions of a terminology New idea: we can create locally our own alternative developing series in order to test out alternative hypotheses regarding how to classify given particulars as instances of given types of disorders or symptoms

68. ifomis.org 67 How make instances visible to reasoning systems? Create an EHR regime in which explicit alphanumerical IUIs (instance unique identifiers) are automatically assigned to each instance when it first becomes relevant to the treatment of a given patient

69. ifomis.org 68 We could then perform experiments with terminologies Our referent-tracking machinery will give us the facility to experiment with different scenarios as concerns the division between N1, N better terminologies better decision-support for diagnosis

70. ifomis.org 69 How medical terms are introduced we have a pool of cases (instances) manifesting a certain hitherto undocumented pattern of irregularities (deviations from the norm) the universal kind which they instantiate is unknown – and the challenge is to solve for this unknown (cf. the discovery of Pluto)

71. ifomis.org 70 Instance vector an ordered triple i is a IUI, p a preferred term, and t a time instance #5001 is associated with SNOMED-CT code glomus tumor at 4/28/2005 11:57:41 AM

72. ifomis.org 71 Instantiation of a terminology Let D be a set of IUIs (collected by a given hospital) For a terminology T= define an instantiation I t (T, D) as the set of all instance vectors for i in D and p in N

73. ifomis.org 72 Instantiation of a term For each term p, define its t-extension I t (T, D)(p) as the set of all IUIs i for for which is included in I t (T, D)

74. ifomis.org 73 Tracking invariants For each p we subject its t-extensions for varying t and D to statistically based factor- analysis in order to determine whether 1. p is in N1(it designates a single universal): the instances in I t (T, D)(p) manifest a common invariant pattern 2. p is in N> 3. p is in N<

75. ifomis.org 74 We can track patterns for I t (T, D)(p) e.g. in relation to the IUIs for patients in given geographical areas, or at given stages of development and growth In relation to a given patient, we can track patterns e.g. for different diagnoses, e.g. I t (T, D)(p) vs. I t (T, D)(q + r) to see which gives a better match

76. ifomis.org 75 Diagnostic decision-support Consider the characteristic patterns of correction which arise in the early phases of diagnosis of degenerative diseases such as multiple sclerosis.

77. ifomis.org 76 The (true) story of Jane Smith (with thanks to Werner Ceusters)

78. ifomis.org 77 Jane’s favourite supermarket July 4th, 1990: Jane goes shopping: The freezer section of Jane’s favourite supermarket The only available warning sign used outside A very suspiciously shaped upper leg

79. ifomis.org 78 A visit to the hospital City Health Centre Dr. Peters (City HC) Dr. Longley

80. ifomis.org 79 Diagnosis: a severe spiral fracture of the femur

81. ifomis.org 80 The City HC’s medical record captures in a structured form all of the ‘clinically significant’ information in the narrative notes

82. ifomis.org 81 Structured Medical Record www.medappz.com/ 04/07/1990 – 17:10Dr. Peters Jane Smith Orthopedics Emergency visit: 04/07/1990 – 17.00 Severe Left upper leg Since fall on floor Constant 26442006closed fracture of shaft of femur 81134009fracture, closed, spiral

83. ifomis.org 82 557204/07/199026442006closed fracture of shaft of femur 557204/07/199081134009Fracture, closed, spiral 557212/07/199026442006closed fracture of shaft of femur 557212/07/19909001224Accident in public building (supermarket) 557204/07/199079001Essential hypertension 093924/12/1991255174002benign polyp of biliary tract 230921/03/199226442006closed fracture of shaft of femur 230921/03/19929001224Accident in public building (supermarket) 4780403/04/199358298795Other lesion on other specified region 557217/05/199379001Essential hypertension 29822/08/19932909872Closed fracture of radial head 29822/08/19939001224Accident in public building (supermarket) 557201/04/199726442006closed fracture of shaft of femur 557201/04/199779001Essential hypertension PtIDDateObsCodeNarrative 093920/12/1998255087006malignant polyp of biliary tract Same patient, same hypertension code: Same (numerically identical) hypertension ? Different patients, same fracture codes: Same (numerically identical) fracture ? Same patient, different dates, same fracture codes: same (numerically identical) fracture ? Same patient, same date, 2 different fracture codes: same (numerically identical) fracture ? Problems Different patients. Same supermarket? Maybe the same (irrelevant ?) freezer section ? Or different supermarkets, but always in the freezer sections ? Same patient, different dates, Different codes. Same (numerically identical) polyp ?

84. ifomis.org 83 Main problems of EHRs Statements refer only implicitly to the concrete entities about which they give information. Codes are general: they tell us only that some instance of the class the codes refer to, is referred to in the statement, but not what instance precisely.

85. ifomis.org 84 Proposed solution: Referent Tracking Purpose: –explicit reference to the concrete individual entities relevant to the accurate description of each patient’s condition, therapies, outcomes,... Method: –Introduce an Instance Unique Identifier (IUI) for each relevant particular / instance

86. ifomis.org 85 CUI (coo-ey): Concept Unique Identifier (e.g. a SNOMED code) UUI (oo-ey): Universal Unique Identifier IUI (you-ey): Instance Unique Identifier (e.g. a Social Security Number)

87. ifomis.org 86 An ontological analysis continuants City HC The freezer section of Jane’s favourite supermarket Jane’s left femur Jane’s left femur fracture Jane Smith Dr. Peters Jane’s left femur Jane’s fracture’s image Dr. Longley City HC’s EHR system t Universals EHR system HC Freezer section Person Femur Fracture Image Jane’s falling Jane’s femur breaking Dr. Peter’s examination of Jane’s fracture Dr. Peter’s ordering of an X-ray Shooting the pictures of Jane’s leg occurrents Jane’s fracture’s healing Dr. Peter’s diagnosis making Jane dies Freezer section dismantled Dr. Longley’s examination of Jane’ s fracture

88. ifomis.org 87 IUI assignments The act of IUI assignment can be represented as: IUI a = IUI of the registering agent A i = IUI a = IUI of the author of the assertion IUI p = IUI of the particular t ap = time of assignment c = optional description t d = time of registering A i in the IUI-repository

89. ifomis.org 88 A SNOMED-CT example #IUI-0945: author of the statement #IUI-1921: the left testicle of patient #IUI-78127 367720001: the SNOMED concept-code to which “left testis” is (in SNOMED) attached as term So we can denote #IUI-1921 by means of that left testis that entire left testis that testicle, that male gonad, that testis that genital structure that physical anatomical entity BUT NOT: that SNOMED-CT concept

90. ifomis.org 89 Pragmatics of IUIs in EHRs IUI assignment requires (just a bit) more effort compared to current use of general codes from concept-based systems

91. ifomis.org 90 IUIs in structured EHRs www.medappz.com/ 04/07/1990 – 17:10Dr. Peters Jane Smith Orthopedics Emergency visit: 04/07/1990 – 17.00 Severe Left upper leg Since fall on floor Constant 26442006closed fracture of shaft of femur 81134009fracture, closed, spiral Replaced by the IUI for the patient’s left upper leg That IUI might be found by using “left upper leg” as a search term to query the RTDB Both replaced by the IUI for that fracture By means of PTCO statements is the IUI related to the SNOMED-codes

92. ifomis.org 91 Advantage: better reality representation 557204/07/199026442006closed fracture of shaft of femur 557204/07/199081134009Fracture, closed, spiral 557212/07/199026442006closed fracture of shaft of femur 557212/07/19909001224Accident in public building (supermarket) 557204/07/199079001Essential hypertension 093924/12/1991255174002benign polyp of biliary tract 230921/03/199226442006closed fracture of shaft of femur 230921/03/19929001224Accident in public building (supermarket) 4780403/04/199358298795Other lesion on other specified region 557217/05/199379001Essential hypertension 29822/08/19932909872Closed fracture of radial head 29822/08/19939001224Accident in public building (supermarket) 557201/04/199726442006closed fracture of shaft of femur 557201/04/199779001Essential hypertension PtIDDateObsCodeNarrative 093920/12/1998255087006malignant polyp of biliary tract IUI-001 IUI-003 IUI-004 IUI-005 IUI-007 IUI-002 IUI-012

93. ifomis.org 92 Other Advantages Mappings between ontologies and coding systems created as by-product of tracking –Descriptions about the same particular using different systems e.g. in different hospitals Quality control of ontologies and concept- based systems –Systematically inconsistent descriptions within or across terminologies may indicate poor definition of the respective terms

94. ifomis.org 93 Other Advantages Referent tracking can be used in decision support when making diagnoses We can consider the results of assignment of different clinical codes to one and the same collection of IUIs assembled over a period (and thereby uncover new patterns of symptoms, e.g. in a case of multiple sclerosis)

95. ifomis.org 94 Conclusion Referent tracking can solve a number of problems in an elegant way. Existing (or emerging) technologies can be used for the implementation. Old technologies can play an interesting role. Big Brother feeling is to be expected, but with adequate measures easy to fight. Pilot is being established

96. ifomis.org 95 The End http://ifomis.org