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Towards a Reference Terminology for Talking about Ontologies and Related Artifacts

Towards a Reference Terminology for Talking about Ontologies and Related Artifacts. Barry Smith http://ontology.buffalo.edu/smith with thanks to Werner Ceusters, Waclaw Kusnierczyk, Daniel Schober. Problem of ensuring sensible cooperation in a massively interdisciplinary community. concept

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Towards a Reference Terminology for Talking about Ontologies and Related Artifacts

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  1. Towards a Reference Terminology for Talking about Ontologies and Related Artifacts Barry Smith http://ontology.buffalo.edu/smith with thanks to Werner Ceusters, Waclaw Kusnierczyk, Daniel Schober

  2. Problem of ensuring sensible cooperation in a massively interdisciplinary community concept type instance model representation data

  3. What do these mean? ‘conceptual data model’ ‘semantic knowledge model’ ‘reference information model’ ‘an ontology is a specification of a conceptualization’

  4. natural language labels to make the data cognitively accessible to human beings and algorithmically tractable

  5. compare: legends for maps compare: legends for maps

  6. ontologies are legends for data

  7. compare: legends for cartoons

  8. legends help human beings use and understand complex representations of reality help human beings create useful complex representations of reality help computers process complex representations of reality

  9. computationally tractable legends help human beings find things in very large complex representations of reality

  10. legends for mathematical equations xi = vector of measurements of gene i k = the state of the gene ( as “on” or “off”) θi = set of parameters of the Gaussian model ... ...

  11. Glue-ability / integration rests on the existence of a common benchmark called ‘reality’ the ontologies we want to glue together are representations of what exists in the world not of what exists in the heads of different groups of people

  12. truth is correspondence to reality

  13. simple representations can be true

  14. a network diagram can be a veridical representation of reality

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

  16. an image can be a veridical representation of reality a labeled image can be a more useful veridical representation of reality

  17. an image labelled with computationally tractable labels can be an even more useful veridical representation of reality

  18. annotations using common ontologies can yield integration of image data

  19. if you’re going to semantically annotate piles of data, better work out how to do it right from the start

  20. two kinds of annotations

  21. names of types

  22. names of instances

  23. First basic distinction type vs. instance (science text vs. diary) (human being vs. Tom Cruise)

  24. For ontologies it is generalizations that are important = ontologies are about types, kinds

  25. Ontology types Instances

  26. Ontology = A Representation of types

  27. An ontology is a representation of types We learn about types in reality from looking at the results of scientific experiments in the form of scientific theories experiments relate to what is particular science describes what is general

  28. There are created types bicycle steering wheel aspirin Ford Pinto we learn about these by looking at manufacturers’ catalogues

  29. measurement units are created types

  30. Inventory vs. CatalogTwo kinds of representational artifact Roughly: Databases represent instances Ontologies represent types

  31. Catalog vs. inventory

  32. Catalog vs. inventory

  33. Catalog of types/Types

  34. object organism animal cat siamese types mammal frog instances

  35. Ontologies are here

  36. or here

  37. ontologies represent general structures in reality (leg)

  38. Ontologies do not represent concepts in people’s heads

  39. They represent types in reality

  40. which provide the benchmark for integration

  41. if you’re going to semantically annotate piles of data, better work out how to do it right from the start

  42. Entity =def anything which exists, including things and processes, functions and qualities, beliefs and actions, documents and software (Levels 1, 2 and 3)

  43. what are the kinds of entity?

  44. First basic distinction universal vs. instance (science text vs. diary) (human being vs. Tom Cruise)

  45. Ontology Universals Instances

  46. Ontology = A Representation of Universals

  47. Ontology = A representation of universals • Each node of an ontology consists of: • preferred term (aka term) • term identifier (TUI, aka CUI) • synonyms • definition, glosses, comments

  48. An ontology is a representation of universals We learn about universals in reality from looking at the results of scientific experiments in the form of scientific theories experiments relate to what is particular science describes what is general

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