1. 1 Ontologie als konkretisierte Darstellung der Wirklichkeit Barry Smith

2. 2 MeSH Medical Subject Headings National Library of Medicine

3. 3 What MeSH is for Indexing (Tagging) Medical Literature

4. 4 MeSH Descriptors Index Medicus Descriptor Anthropology, Education, Sociology and Social Phenomena (MeSH Category) Social Sciences Political Systems National Socialism

5. What (bio-)ontologies are for

6. 6 what molecular function ? what disease process ? need for semantic annotation of data

7. 7 through labels (nouns, noun phrases) which are algorithmically processable

8. 8

9. 9 warum ist die Gene Ontologie so erfolgreich?

10. 10

11. 11 natural language tags to make the data cognitively accessible to human beings

12. 12 compare: legends for maps

13. 13 or legends for cartoons

14. 14

15. 15

16. 16 ontologies are legends for data

17. 17 ontologies are legends for images

18. 18 what brain region ? what brain function ?

19. 19 x i = vector of measurements of gene i k = the state of the gene ( as “on” or “off”) θ i = set of parameters of the Gaussian model... ontologies are legends for mathematical equations

20. 20 The Gene Ontology as Integrator MouseEcotope GlyProt DiabetInGene GluChem sphingolipid transporter activity

21. 21 annotation using common ontologies yields integration of databases MouseEcotope GlyProt DiabetInGene GluChem Holliday junction helicase complex

22. 22 annotation using common ontologies can yield integration of image data

23. 23 annotation using common ontologies can support comparison of image data

24. 24 truth

25. 25 simple representations can be true

26. 26 there are true cartoons

27. 27 a cartoon can be a veridical representation of reality

28. 28 Cartographic Projection

29. 29 maps may be correct by reflecting topology, rather than geometry

30. 30 a fully labeled image can be an even more veridical representation of reality an image can be a veridical representation of reality

31. 31 cartoons, like maps, always have a certain threshold of granularity

32. 32 grain resolution

33. 33 grain resolution serves cognitive accessibility we transform true images into true cartoons

34. 34 instances vs. types

35. 35 two kinds of annotations

36. 36 names of instances

37. 37 names of types

38. 38 pathway maps are representations of complexes of types

39. 39 molecular images and radiographic images are representations of instances

40. 40 MIAKT system

41. 41

42. 42

43. 43

44. 44

45. 45 Patient #47920

46. 46

47. 47 Mammography #31667

48. 48 Mammography #31667 Medical-Image #44922

49. 49 MRI-Exam #32388 Medical-Image #44922 Mammography #31667 Patient #47920 Breast #1388 Abnormality #86023

50. 50 There is only one reality but many different representations thereof, including many different ontologies different ontologies can be simultaneously veridical, e.g. because of non-overlapping domains, or because of differential selection (“multi-perspectivalism”)

51. 51 Reality exists before any representation R And also most structures in reality are there a priori

52. 52 The ontologist becomes with a mental representation (‘Bild’) R B1B1 Some portions of reality escape his attention.

53. 53 R a part of which he concretizes in an ontology O1O1 B1B1 #1 both mental representation and ontology refer to the same reality

54. 54 R A second ontologist makes a different selection O1O1 B2B2 B1B1 O2O2

55. 55 R Veridical ontologies can always be mapped by taking reality as benchmark O1O1 B2B2 B1B1 O2O2 OmOm

56. 56 but ontologies can be non- veridical, because of different kinds of errors errors of mismatch with reality errors of understanding errors of coding

57. 57 Typology of errors (Werner Ceusters)

58. 58 http://org.buffalo.edu