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Realism-Based Ontology Development: Philosophy and Applications

Join Prof. Werner Ceusters as he explores realism-based ontology development from a software engineering perspective. This lecture will cover the philosophical foundations of ontology, the relation with referent tracking, and its applications in fields such as medicine, pharmacogenomics, and computational linguistics. Don't miss this opportunity to gain insights into the importance of realism in ontology development.

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Realism-Based Ontology Development: Philosophy and Applications

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  1. VUB Leerstoel 2009-2010Theme: Ontology for Ontologies, theory and applicationsPrevented abortions, absent nipples and other unicorns: the need for realism-based ontology developmentMay 18, 2010; 17h00-19h00Vrije Universiteit Brussel, Pleinlaan 2, 1050 BrusselsRoom D0.08 Prof. Werner CEUSTERS, MD Ontology Research Group, Center of Excellence in Bioinformatics and Life Sciences and Department of Psychiatry, University at Buffalo, NY, USA

  2. Knowledge Representation Informatics Linguistics Ontology Philosophy Computational Linguistics Realism-Based Ontology Medical Natural Language Understanding Electronic Health Records Translational Research Referent Tracking Medicine Pharmacogenomics Performing Arts Defense & Intelligence Biology Pharmacology Context of this lecture series

  3. Today’s topic • May 18: Realism-based ontology development • A software engineering perspective • What ontology should be • philosophical realism, applied to … • … ‘knowledge representation’ • Generic/specific distinction • relation with Referent Tracking Ontology Philosophy Realism-Based Ontology Referent Tracking

  4. The many faces of “ontologies” (For if you missed the first lecture in this series)

  5. The word ‘Ontology’ has two meanings • Ontology: the science of what entities exist and how they relate to each other. • An ontology:a representation of some domain which • (1) is intelligible to a domain expert, and • (2) is formalized in a way that allows it to support automatic information processing.

  6. Within the context of ‘anontology’,the word ‘domain’ has two meanings • For most computer scientists: • A representation of an agreed upon conceptualization about which man and machine can communicate using an agreed upon vocabulary • For philosophical ontologists: • A representation of a portion of reality • Still allowing for a variety of entities to be recognised by one school and refuted by another one

  7. Few embrace both and they should be applauded • ‘A message to mapmakers: highways are not painted red, rivers don't have county lines running down the middle, and you can't see contour lines on a mountain.’ Bill Kent 1936-2005 William Kent, Data and Reality. First published by North Holland in 1978. Republished in 1998 by 1stBooks.

  8. Three types of ontologies • Upper level ontologies: • (should) describe the most generic structure of reality • Domain ontologies: • (should) describe the portion of reality that is dealt with in some domain • Special case: reference ontologies • Application ontologies: • To be used in a specific context and to support some specific application

  9. The dispute between … • “Practical engineers”: • If it works for our purposes, it is ok • Good philosophers: • If it works always, it is ok, and • It can only always work if it represents the relevant portion of reality faithfully.

  10. OntologyA computer science and software engineering perspective

  11. is a computer-based, shared, agreed, formal, conceptualization of a domain.  by distinct software agents  by the developers thereof  no room for misinterpretation  concretization of the cognitive representation of the domain by the authors Ontology (CS/SE) R. Meersman. Hybrid ontologies in a tr-sortal internet of humans, systems and enterprises. In: B. Smith, R. Mizoguchi, S. Nakagawa. Interdisciplinary Ontology vol.3. Keio University, Tokyo, 2010;43-50.

  12. An example: the domain of laser pointers

  13. An example: the domain of laser pointers

  14. ‘This unique laser pointer projects a red dot’ • One could then produce statements (‘triples’) of the sort: < Laser Pointer, projects, Dot > < Dot, with_color, Red > < Red, subtypes_of, Color > • But what does this mean? • only this specific pointer (the one from which an image was taken) or all similar pointers of the same model? • does such a laser pointer projects a dot all the time? • is only the red of the dot a subtype of color or is the red of whatever is red a subtype of color ? • do laser pointers only project red dots? • ...

  15. More esoterically • this one does not project a dot

  16. More esoterically • this one does neither

  17. More esoterically • now it does, although nothing at all changed in the pointer • projecting a dot does not depend on the pointer only

  18. More esoterically now this pointer projects a brown dot

  19. More esoterically these two pointers project the very same dot

  20. Conclusion • Triples of this sort don’t mean a thing !

  21. Better: ‘lexons’ in DOGMA • Example lexons are: < γ, Laser Pointer, projects, projection_of, Dot > < γ, Dot, with_color, color_of, Red > < γ, Red, subtypes_of, has_subtype, Color > • where: • γ: a context identifier (pointing f.i. to the text about laser pointers) • Laser Pointer, Dot, Red, Color: terms corresponding to unique concepts within context γ • projects, projection_of, with_color, color_of: terms corresponding to roles played by the concepts in context γ M. Jarrar, R. Meersman. Formal Ontology Engineering in the DOGMA Approach. Lecture Notes In Computer Science;2519: 1238 – 1254, 2002.

  22. ‘This unique laser pointer projects a red dot’ • And, in addition, commitments of the sort: • each Dot has at most one Color • each Laser Pointer projects at least one Dot • … M. Jarrar, R. Meersman. Formal Ontology Engineering in the DOGMA Approach. Lecture Notes In Computer Science;2519: 1238 – 1254, 2002.

  23. This has advantages • Lexons provide some sort of common sense knowledge accessible to humans, • Commitments provide an interpretation of lexons, • Applications pick and choose what is relevant for their purpose.

  24. The DOGMA dogma • ‘It is fundamental to realize that this formalism implies that to the application agents, the ontology (i.e. the ontology base (= lexons) plus the agent’s commitment to a part of it) is the real world, nothing more nor less. Lexons in a DOGMA ontology base are always "true", i.e. free of further "interpretation". • Alternative truths, or partial ones as typically emerge during the engineering process have to be provided in separate conceptualizations or contexts. Contexts that specify improbable or impossible (contradictory) worlds are possible, especially in the early stages of engineering an ontology, but in practice will have few or no applications that can commit to them.’ M. Jarrar, R. Meersman. Formal Ontology Engineering in the DOGMA Approach. Lecture Notes In Computer Science;2519: 1238 – 1254, 2002.

  25. Another (simple) example in DOGMA M. Jarrar, R. Meersman. Formal Ontology Engineering in the DOGMA Approach. Lecture Notes In Computer Science;2519: 1238 – 1254, 2002.

  26. The corresponding lexons

  27. … and commitments

  28. Crucial questions • To which commitments should an application commit? • How can application developers judge whether lexons and corresponding commitments make sense? • Is the notion of ‘context’ formal enough to be the basis for such decisions?

  29. < γ1, Dot, with_color, color_of, Green > < γ3, Dot, with_color, color_of, Green > < γ3, Dot, with_color, color_of, Red > < γ2, Dot, with_color, color_of, Red > Laser pointers again ‘lexons are assumed (by an outside cognitive agent such as a human understanding that document) to be "true within that context's source“’ M. Jarrar, R. Meersman. Formal Ontology Engineering in the DOGMA Approach. Lecture Notes In Computer Science;2519: 1238 – 1254, 2002.

  30. Further questions • Do we need now an ontology of contexts of laser pointers ? e.g. • < γ? ,γ1, part_of, has_part,γ3> • < γ? ,γ1, part_of, has_part,γ3> • what context goes here? • If γ1 and γ2are part of γ3, then what remains of the ‘unique concepts’ < γ3, Dot>, < γ1, Dot>, and < γ2, Dot>? • Can inγ3dots have more than one color? < γ1, Dot, with_color, color_of, Green > < γ3, Dot, with_color, color_of, Green > < γ3, Dot, with_color, color_of, Red > < γ2, Dot, with_color, color_of, Red >

  31. But what, after all, should we represent? Ontology: conceptualization of this or that?

  32. Ontology:The philosophical realism perspective

  33. Laser pointer document Ontology is-about The realist view ≠ Laser pointer Ontology is-about is-about

  34. Basic axioms of philosophical realism • There is an external reality which is ‘objectively’ the way it is; • That reality is accessible to us; • We build in our brains cognitive representations of reality; • We communicate with others about what is there, and what we believe there is there. Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, Biomedical Ontology in Action, November 8, 2006, Baltimore MD, USA

  35. Realism Conceptualism Nominalism Universal Concept Collection of particulars yes: in particulars perhaps: in minds no Three major views on reality • Basic questions: • What does a general term such as ‘laser pointer’ refer to? • Do generic things exist?

  36. Realism Conceptualism Nominalism Universal Concept Collection of particulars yes: in particulars perhaps: in minds no Dominant view in computer science is conceptualism • Basic questions: • What does a general term such as ‘laser pointer’ refer to? • Do generic things exist?

  37. concept Embedded in Terminology Semantic Triangle object term Dominant view in computer science is conceptualism Realism Conceptualism Nominalism

  38. ‘Terminology’: one word, two meanings • Terminology is the study of identifying and labelling ‘concepts’ pertaining to a subject field. • Terminology related activities: • analysing the concepts and concept structures, • identifying the terms assigned to the concepts, • establishing correspondences between terms, possibly in various languages, • compiling a terminology, on paper or in databases, • managing terminology databases, • creating new terms, as required.

  39. However … • Terminology: • solves certain issues related to language use, i.e. with respect to how we talk about entities in reality (if any); • Relations between terms / concepts • does not provide an adequate means to represent independent of use what we talk about, i.e. how reality is structured; • Women, Fire and Dangerous Things (Lakoff). • Ontology (of the right sort): • Language and perception neutral view on reality. • Relations between entities in first-order reality This is the ‘terminology / ontology divide’

  40. urine bladder gallbladder inflammation gall bladder urinary bladder gall biliary cystitis ‘urinary’ inflammation ‘gall’ cystitis ‘urinary bladder’ ‘inflammation’ ‘gallbladder’ ‘bladder’ ‘gallbladder inflammation’ ‘urinary bladder inflammation’ Important to differentiate betweenLexical, semantic and ontological relations

  41. Representation and Reference terms concepts about First Order Reality The semantic triangle revisited concepts objects terms

  42. representational units universals particulars Terminology Realist Ontology Representation and Reference terms concepts about objects First Order Reality

  43. Terminology Realist Ontology Representation and Reference terms concepts representational units about objects universals particulars First Order Reality

  44. Terminology Realist Ontology Representation and Reference representational units terms concepts cognitive units communicative units about objects universals particulars First Order Reality

  45. Representational units in various • forms about (1), (2) or (3) (2) Cognitive entities which are our beliefs about (1) (1) Entities with objective existence which are not about anything Three levels of reality in Realist Ontology Terminology Realist Ontology Representation and Reference representational units cognitive units communicative units universals particulars First Order Reality

  46. Three levels of reality • The world exists ‘as it is’ prior to a cognitive agent’s perception thereof; Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, November 8, 2006, Baltimore MD, USA

  47. R Reality exist before any observation

  48. R And also most structures in reality are there in advance. Reality exist before any observation • Humans had a brain well before they knew they had one. • Trees were green before humans started to use the word “green”.

  49. Three levels of reality • The world exists ‘as it is’ prior to a cognitive agent’s perception thereof; • Cognitive agents build up ‘in their minds’ cognitive representations of the world; Smith B, Kusnierczyk W, Schober D, Ceusters W. Towards a Reference Terminology for Ontology Research and Development in the Biomedical Domain. Proceedings of KR-MED 2006, November 8, 2006, Baltimore MD, USA

  50. The ontology author acknowledges the existence of some Portion Of Reality (POR) B R

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