1. Part 4 Ontology: Philosophical and Computational

2. Coarse-grained Partition

3. Fine-Grained Partition

4. Many partitions are transparent to reality TEE is a ragbag of skew partitions, some of them transparent One job of the ontological realist is to understand how different partitions of the same reality interrelate -- notion of projection

5. Distinct transparent partitions of reality

6. Contrast this with ‘knowledge representation’

7.  problem of ‘knowledge representation’

8. problem of ‘knowledge representation’ solved by looking at the world

9. How solve the problem? Ontology as maximally opportunistic theory of reality (not of ‘knowledge’)

10. Much ‘knowledge’ is not knowledge at all, it is mere beliefs (sometimes false beliefs) or it may be tacit (knowledge how, rather than knowledge that) ‘Knowledge representation’ rests on lazy use of ‘knowledge’

11. Maximally opportunistic means: don’t just look at beliefs look at the objects themselves from every possible direction, formal and informal scientific and non-scientific collect documents, read textbooks …

12. Maximally opportunistic means: don’t just look at beliefs in an unquestioning fashion don’t just swallow what the customer says

13. Maximally opportunistic means: look at beliefs critically and always in the context of a wider view which includes looking at other beliefs and embracing independent ways to access the objects themselves

14.  problem of ‘knowledge representation’ “Leprechauns”

15.  problem of ‘knowledge representation’ “Leprechauns” concepts are in the head objects (including universals) are in the world not all concepts correspond to objects not all concepts are relevant to ontology

16. Ontology (if it is interested in concepts at all) is interested only in those concepts which correspond to something in reality therefore: ontology MUST IN ANY CASE BE INTERESTED IN REALITY (perhaps the step through concepts is redundant)

17. Ontology (if it is interested in models at all) is interested only in those models which correspond to something in reality therefore: ontology MUST IN ANY CASE BE INTERESTED IN REALITY (perhaps the step through models is redundant)

19. Conceptual Models are TWO steps removed from reality!

21. Perspectivalism Different views/partitions may represent cuts through the same reality which are skew to each other

22. But they should be cuts through reality which means: the partitions used by the ontologist should be compatible a good medical ontology should NOT be compatible with the conceptualization of disease as: something caused by evil spirits and demons and cured by leprechauns

23.  problem of ‘merging’ ontologies “Leprechauns” primitive Irish people

24.  problem of ‘merging’ ontologies garbage in garbage out the job of the ontologist is not to merge poor quality conceptualizations … it is to find a way of building good depictions of reality

25. Ontology should be a real constraint cf. Ontoclean methodology

27. All veridical perspectives are equal Each veridical perspective (which is to say: each transparent partition) captures some corresponding part of reality at some level of granularity

28. Scientific partitions (like the periodic table)... are transparent to the corresponding order of an associated domain of objects

29. Question: which sorts of partitions have this feature of transparency? the partitions of science the partitions of common sense (folk biology, folk physics,...)

30. The Empty Mask (Magritte) mama mouse milk Mount Washington

31. Both scientific partitions and common-sense partitions are based on reference-systems which have survived rigorous empirical tests

32. Many transparent partitions at different levels of granularity will operate with species-genus hierarchies and with an ontology of substances (objects) and accidents (attributes, processes) along the lines described by Aristotle

33. Good conceptualizatons Philosophical ontologists are interested in: 1. transparent conceptualizations, veridical perspectives on reality 2. which are at the same time interesting = science, and what else?

34. Criteria of quality of partitions serves communiction -- standardization, wide accessibility robust (have survived rigorous empirical tests) learnable (including: via scientific training) serves prediction

35. ‘An ontology is a specification of a conceptualization’ (Tom Gruber, SRI) Tom Gruber’s Definition... designed to provide a stable forum for translation and interoperability as between different conceptualizations Ontolingua = Esperanto for Information Systems

36. Ontology, for Gruber, starts with our conceptualizations, and sees how far we can push through from there to a description of a corresponding domain of objects Conceptualizations are associated with: stories, sciences, organizations, etc.

37. Ontology, for Gruber, deals with surrogate created worlds with ‘models’... with the generated correlates of both good and bad conceptualizations

38. Two sorts of conceptualizations bad = those which relate merely to a created, surrogate world good = those which are transparent to some independent reality beyond

39. Not all conceptualizations are equal Bad conceptualizations:... lying, story-telling, dreaming, astrology, metaphysical error... Good conceptualizations: science common sense (folk biology) what else?

40. Description Language vs. Representation Language languages for describing the world vs. languages for representing other peoples’s theories

41. Set Theory Is the language of set theory a good language for describing the world (a good ontological language)? Are there sets in reality? Set theory as Representation Language (Representation Theorems) Set theory as a mathematical tool

42. Heinrich Set theory yields a description language for the world of mathematical objects -- the Plato-Frege heaven -- is this true? What do differential equations depict? -- rates of change, acceleration

43. Problems with Set Theory as Basis for an Ontological Description Language for Ordinary (Non-Mathematical Reality)

44. Problems with Set Theory 1. What are the urelements? an exclusively set-theoretic ontology is forced to begin with atoms and work upwards from there. Mereological ontology can deal with mesoscopic entities and with their mesoscopic constituents (for example in medicine) without caring about smallest- scale parts

45. Problems with Set Theory 2. Reality is an ocean of mass-energy constantly changing in time. The causally relevant wholes (organisms, species, …) within this totality are constantly gaining and losing parts. Sets are abstract entities defined entirely via the specification of their members. Sets do not change

46. Problems with Set Theory 3. The ontology of reality is quite different from the ontology of pure mathematics. For the ontology of reality the cardinal number constructions (2 א o, etc.) are artifacts of the theory. An ontology powerful enough for medicine needs to avoid detours into realms of such mathematical artifacts

47. The End

48. Slides on website http://ifomis.de Events Ontological Spring

49. Recruitment

50. Thanks

51. Dinner

52. Problems with Set Theory 4. The urelements from out of which the continuum is to be set-theoretically constructed must be extensionless points. Even if we can model real continua via set-theoretical constructions out of such extensionless points, real continua are not sums or totalities of unextended building blocks.

53. Brentano A real continuum is a whole which allows parts (including points) to be distinguished within it. The whole comes first.

54. Against Fantology For the fantologist “(F(a)”, “R(a,b)” … is the description language for ontology The fantologist sees reality as being made up of atoms plus abstract (1- and n-place) ‘properties’ or ‘attributes’ … confuses logical form with ontological form

55. Two senses of ‘situoid’ Two senses of ‘Poland’ Two senses of ‘triangle in the sand’ Projecting situoids as granular entities (John is kissing Mary) onto the underlying thought-independent reality

56. No God’s Eye Partition Some draw the conclusion that there is no such thing as reality, … but rather different socially constructed 'realities' (in sneer quotes)

57.  problem of ‘knowledge representation’ “Leprechauns” X knows that p  p is true

58. The world of common sense = the world as apprehended via that conceptualization we call common sense = the normal environment (the niche) shared by children and adults in everyday perceiving and acting

59. mothers, milk, and mice... do genuinely exist

60. Scientific conceptualizations = those based on reference-systems which have survived rigorous empirical tests Referential realism vs. Theory realism