From Knowledge Representation to Reality Representation

1. From Knowledge Representation to Reality Representation Barry Smith http://ontologist.com

2. 2002 • Institute for Formal Ontology and Medical Information Science (Germany) • initially: work on formal ontology • and on ontology-based quality control in medical terminologies • (UMLS, SNOMED, NCI Thesaurus, etc.) http://ontologist.com

3. Problem: Associative approach to word meanings SimilarTo Fruit Vegetable NarrowerThan Orange Apfelsine SynonymWith Goble & Shadbolt http://ontologist.com

4. both testes is_a testis • plant leaves is_a plant • menopause part_of death • bacterium causes experimental model of disease • not normal cell is_a cell • not abnormal cell is_a cell http://ontologist.com

5. move from associative relations between meanings to ontological relations between the entities themselves • supplementing data mining approaches with • better data • better annotations • better integration • the possibility of strong logical reasoning http://ontologist.com

6. First crack in the wall • Digital Anatomist Foundational Model of Anatomy(Department of Biological Structure, University of Washington, Seattle) • Virtual Soldier Project: • Reference Ontology of Anatomy • Reference Ontology of Physiology • Reference Ontology of Disease Pathways http://ontologist.com

7. Second Crack in the Wall • Gene Ontology Consortium Open Biological Ontologies http://ontologist.com

8. NCOR: National Center for Ontological Research • Buffalo Center of Excellence in Bioinformatics) • Stanford Medical Informatics (Protégé 2000) • Berkeley Drosophila Genome Project • (Model Organism Phenotype Ontology Project) http://ontologist.com

9. NCOR: National Center for Ontological Research • plus industrial parners • Ontology Works • ... http://ontologist.com

10. NCOR Methodology • work with content developers to ensure rigorous conformity with good principles of classification and definition • use formally defined categories and relations to ensure interoperability and support automatic reasoning • and to move beyond mere statistical / associative techniques http://ontologist.com

11. Goal in Biomedical Informatics • use the methodology of formally defined relations and a common top-level ontology to bridge the granularity gap between genomics and proteomics data and phenotype (clinical, pharmacological, patient centered) data • From molecules to diseases http://ontologist.com

12. Examples of simple formal-ontological structures • is_a hierarchies • part_of hierarchies • dependence relations http://ontologist.com

13. A Window on Reality http://ontologist.com

14. Medical Diagnostic Hierarchy a hierarchy in the realm of diseases http://ontologist.com

15. Dependence Relations Organisms Diseases http://ontologist.com

16. A Window on Reality Organisms Diseases http://ontologist.com

17. Organ Part Organ Subdivision Anatomical Space Anatomical Structure Organ Cavity Subdivision Organ Cavity Organ is_a Organ Component Serous Sac Tissue Serous Sac Cavity Subdivision Serous Sac Cavity Pleural Sac Pleura(Wall of Sac) Pleural Cavity part_of Parietal Pleura Visceral Pleura Interlobar recess Mediastinal Pleura Mesothelium of Pleura http://ontologist.com

18. A Window on Reality http://ontologist.com

19. We can reason across such hierarchies and combinations • but only if the top-level categories and associated formal-ontological relations are well-defined and used consistently http://ontologist.com

20. Formal-Ontological Categories http://ontologist.com

21. Formal-Ontological Relations http://ontologist.com

22. To support integration of ontologies • relational expressions such as • is_a • part_of • ... • should be used in the same way by all the ontologies to be integrated • NCOR goal http://ontologist.com

23. to define these relations properly • we need to take account of reality • If we remain in the realm of concepts we will forever face problems of interoperability http://ontologist.com

24. to define these relations properly • we need to take account not of concepts, • but of universals and instances in reality http://ontologist.com

25. Tom Gruber • “An ontology is a specification of a conceptualization” http://ontologist.com

26. The Concept Orientation • Work on biomedical ontologies grew out of work on medical dictionaries and thesauri • led to the assumption that all that need be said about concepts can be said without appeal to time or instances. • & fostered an impoverished regime of definitions http://ontologist.com

27. ‘Concept’ in ontology runs together: • the meaning that is shared in common by a collection of synonymous terms • an idea shared in common in the minds of those who use synonymous terms (psycho-linguistic view) • a universal, feature or property shared by entities in the world which fall under the concept http://ontologist.com

28. Problem of evaluation • if an ontology is a mere “specification of a conceptualization,” then the distinction between good and bad ontologies loses its foothold in reality http://ontologist.com

29. There are more word meanings than there are types of entities in reality • unicorn • devil • cancelled performance • avoided meeting • prevented pregnancy • imagined mammal ... http://ontologist.com

30. A is_a B =def. • ‘A’ is more specific in meaning than ‘B’ http://ontologist.com

31. unicorn is_a one-horned mammal • alien implant removal is_a surgical process • Chios energy healing is_a therapeutic process http://ontologist.com

32. This linguistic reading • yields a more or less coherent reading of relations like: • ‘is_a’ • ‘synonymous_with’ • ‘associated_to’ http://ontologist.com

33. but it fails miserably when it comes to relations of other types • part_of = def. composes, with one or more other physical units, some larger whole • contains =def. is the receptacle for fluids or other substances. http://ontologist.com

34. for how can concepts, on the linguistic reading, figure as relata of relations like: • part_of • adjacent_to • connected_to http://ontologist.com

35. connected_to =def. Directly attached to another physical unit as tendons are connected to muscles. • How can a meaning or concept be directly attached to another physical unit as tendons are connected to muscles ? http://ontologist.com

36. is_a • human is_a mammal • all instances of the universal human are as a matter of necessity instances of the universal mammal http://ontologist.com

37. Evaluation • Good ontologies are those whose general terms correspond to universals in reality, and thereby also to corresponding instances. http://ontologist.com

38. Kinds of relations • <universal, universal>: is_a, part_of, ... • <instance, universal>: this explosion instance_of the universal explosion • <instance, instance>: Mary’s heart part_of Mary http://ontologist.com

39. Instance-level relations • part_of • is_located_at • has_participant • has_agent • earlier • . . . http://ontologist.com

40. part_of • For instances: • part_of= instance-level parthood • (for example between Mary and her heart) • For universals: • A part_of B =def. given any instance a of A there is some instance b of B such that a part_of b http://ontologist.com

41. C1 C c att c att1 transformation_of http://ontologist.com

42. transformation_of • fetus transformation_of embryo • adult transformation_of child • C2 transformation_of C1 =def. any instance of C2 was at some earlier time an instance of C1 http://ontologist.com

43. derives_from • c derives_from c1 • =def c and c1 are non-identical • and exist in continuous succession http://ontologist.com

44. the initial component ceases to exist with the formation of the new component C c att C1 c1att1 the new component detaches itself from the initial component, which itself continues to exist C c att c att1 C1 c1att http://ontologist.com

45. two initial components fuse to form a new component C1 c1att1 C c att C' c' att http://ontologist.com

46. Functions • your heart has the function: to pump blood • = your heart is predisposed (has the potential or casual power) to realize a process of the type pumping blood. • has_agent (instance-level relation) • p is_functioning_of cp has_agent c http://ontologist.com

47. Example: Spatially Coinciding Objectswith thanks to Maureen Donnelly http://ontologist.com

48. Two entities coincide (partially) when they overlap (share parts) • my hand coincides with my body • the European Union coincides with the British Commonwealth • (United Kingdom … Malta, Cyprus) http://ontologist.com

49. Some entities coincide even though they share no parts • any material object coincides with its spatial region • a portion of food coincides with my stomach cavity http://ontologist.com

50. Holes may coincide with material objects • The hole in the chunk of amber coincides completely with, but does not overlap, the encapsulated insect which fills it • Sometimes holes and objects are moving independently (a bullet flying through a railway carriage moving through a tunnel) http://ontologist.com