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Top Level Ontologies Ontologies and Ontology Engineering

Top Level Ontologies Ontologies and Ontology Engineering. Ekhiotz Vergara and Maria Vasilevskaya Dept. of Computer & Information Science Linköping University 14 th June 2011. Outline. Introduction Definition Goals Main principle Some existing ontologies Upper Level Distinctions

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Top Level Ontologies Ontologies and Ontology Engineering

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  1. Top Level OntologiesOntologies and Ontology Engineering Ekhiotz Vergara and Maria Vasilevskaya Dept. of Computer & Information Science Linköping University 14th June 2011

  2. Outline • Introduction • Definition • Goals • Main principle • Some existing ontologies • Upper Level Distinctions • Selected ontologies • Cyc • DOLCE • SUMO • Application of Upper Ontologies • Merging or Upper Ontologies • Results of comparison

  3. Outline • Introduction • Definition • Goals • Main principle • Some existing ontologies • Upper Level Distinctions • Selected ontologies • Cyc • DOLCE • SUMO • Application of Upper Ontologies • Merging or Upper Ontologies • Results of comparison

  4. Definition • “An attempt to create an ontology which describes very general concepts that are the same across all domains. The aim is to have a large number on ontologies accessible under this upper ontology” [Wikipedia] • “The very first kind” [Philosophical view] • Similar concepts: Top, Foundation, Upper

  5. Goals • Semantic interoperability • To interpret information properly by the receiving system in the same sense as intended by the transmitting systems • Ontologies matching/alignment • To find correspondence among sets of ontologies Ontologies communication

  6. Main principleOntology communication Abstract terms Upper ontology Categories refer to refer to refer to Domain ontology A Domain ontology B Domain ontology C Specific terms refer to

  7. Some existing ontologies • DOLCE (Descriptive Ontology for Linguistic and Cognitive Engineering) • SUMO (Suggested Upper Merged Ontology) • BFO (Basic Formal Ontology) • GFO (General Formal Ontology) • Cyc • PROTON (PROTo ONtology) • Sowa’s ontology

  8. Outline • Introduction • Definition • Goals • Main principle • Some existing ontologies • Upper Level Distinctions • Selected ontologies • Cyc • DOLCE • SUMO • Application of Upper Ontologies • Merging or Upper Ontologies • Results of comparison

  9. Aristotle’s categories • Influence in the current understanding of ontologies • Kategoria • Kinds of predicates/predication • Different interpretations • 10 categories:

  10. Individuals and categories • Individuals: entity that cannot be instantiated • Examples: • Category: Dog, Electron, Red… • Individual: the red of an apple, my dog Wolfy.. Category Individual Instance-of

  11. Time and space • Time points and intervals • Ontologies based on time points • Ontologies based on intervals • Time intervals meet other intervals • Mixed approach, time intervals and boundaries • Brentano-time • Boundaries can coincide • Spatial point and region a b (a,b) Time (a,e) e )e,b)

  12. Objects and processes • Based on a space and time ontology, different categories of individuals can be derived • Ontologies with time points as primitives • Continuant / endurant: • Persistence through time • Identity condition  property assigned to identify it • Instance of an continuant at some time point • Occurrants: • Temporal, unfold through time • E.g. processes • Continuants may participate in continuants

  13. Objects and processes • Ontologies based on time intervals • Temporally extended objects as primitives and derive objects at time points • General Process Theory • All entities temporally extended • E.g. properties as layer of processes • Ontologies based on mixed approach • Brentano-time/space • Presentials in the boundaries • Persistance category to define identity criteria over time • Abstract entities • Independent of space and time

  14. Examples • Basic Formal Ontology • Non-abstract individuals • Real numbers to model time and space • Continuants and occurrants • DOLCE • Individuals, abstract and concrete • Real numbers to model time and space • Continuants, occurrants and abstract individuals • General Formal Ontology • Categories and individuals • Brentano-time/space • Processes, presentials and abstract individuals • Classification of ontological categories

  15. Outline • Introduction • Definition • Goals • Main principle • Some existing ontologies • Upper Level Distinctions • Selected ontologies • Cyc • DOLCE • SUMO • Application of Upper Ontologies • Merging or Upper Ontologies • Results of comparison

  16. Cyc • “Formalised representation of facts, rules of thumb and heuristics for reasoning about objects and events of everyday life”

  17. DOLCEDescription • Descriptive Ontology for Linguistic and Cognitive Engineering • Semantic Web • Cognitive bias • Natural language • Human commonsense • Mesoscopic level • Descriptive • Assist in making already formed conceptualizations explicit • Particulars (individuals) • Distinction between: • Continuants • Occurrents

  18. DOLCETop level

  19. DOLCERefined top level

  20. SUMO • Suggested Upper Merged Ontology • The largest formal public ontology • Created by merging several ontologies: • Sowa’s upper-level ontology • Russell and Norvig’s upper-level ontology • James Allen’s temporal axioms • Casati and Varzi’s formal theory and holes • …

  21. SUMOHigh Level Distinctions SUMO ontology MILO (Mid-Level Ontology) • Communication, • Distributed Computing • Countries and Regions, • Economy, • North American Industrial • Classification System • Engineering Components • Geography • Government • Military • Finance • …

  22. SUMOHigh Level Distinctions • ‘Physical’ (things which have a position in space/time) and ‘Abstract’ (things which don’t) • Partition of ‘Physical’ into ‘Objects’ and ‘Processes’ Entity Abstract Physical Physical Objects Processes

  23. SUMOTop Level Structure Physical Object SelfConnectedObject Substance CorpuscularObject Region Collection Process DualObjectProcess InternalChange ShapeChange IntentionalProcess Motion Abstract SetOrClass Relation Proposition Quantity Number PhysicalQuantity Attribute Graph GraphElement

  24. SUMOValidation • Mapping to all of WordNet lexicon • A check on coverage and completeness (at a given level of generality) • Peer review • Open source since its inception • Formal validation with a theorem prover • Free of contradictions (within a generous time bound for search) • Application to dozens of domain ontologies

  25. Outline • Introduction • Definition • Goals • Main principle • Some existing ontologies • Upper Level Distinctions • Selected ontologies • Cyc • DOLCE • SUMO • Application of Upper Ontologies • Merging or Upper Ontologies • Results of comparison

  26. Applications • Automatic ontology matching • Finding correspondences between entities belonging to two or more ontologies • DOLCE • LOIS project • SmartWeb • Language Technology for eLearning • AsIsKnown • SUMO • More than 100 papers using it • Mostly in linguistics

  27. Outline • Introduction • Definition • Goals • Main principle • Some existing ontologies • Upper Level Distinctions • Selected ontologies • Cyc • DOLCE • SUMO • Application of Upper Ontologies • Merging or Upper Ontologies • Results of comparison

  28. Merging Upper Level Ontologies • COSMO (COmmon Semantic MOdel) • Lattice of ontologies that will serve as a set of basic logically-specified concepts that can be specified in domain ontologies • Contains: • OpenCyc • SUMO • Some concepts of DOLCE and BFO • MSO (Multi-Source Ontology) • Large knowledge server • Lexical ontology • OntoMap • Semantic framework on conceptual level • No maintenance

  29. Outline • Introduction • Definition • Goals • Main principle • Some existing ontologies • Upper Level Distinctions • Selected ontologies • Cyc • DOLCE • SUMO • Application of Upper Ontologies • Merging or Upper Ontologies • Results of comparison

  30. Results of comparison

  31. Results of comparison

  32. References • Mascardi, V.; Locoro, A.; Rosso, P.; , "Automatic Ontology Matching via Upper Ontologies: A Systematic Evaluation," Knowledge and Data Engineering, IEEE Transactions on , vol.22, no.5, pp.609-623, May 2010 • Ian Niles and Adam Pease. 2001. Towards a standard upper ontology. In Proceedings of the international conference on Formal Ontology in Information Systems - Volume 2001 (FOIS '01), Vol. 2001. • Viviana Mascardi, Valentina Cordì and Paolo Rosso. A comparison of upper ontologies. Technical report. 2006 • Aldo Gangemi, Nicola Guarino, Claudio Masolo, Alessandro Oltramari, and Luc Schneider. 2002. Sweetening Ontologies with DOLCE. In Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web (EKAW '02), Springer-Verlag, London, UK, 166-181. • D. B. Lenat and R. V. Guha. Building large knowledge-based systems: representation and inference in the cyc project. Journal of Artificial Intelligence. 1990. • Pierre Grenon and Barry Smith and Louis Goldberg. Biodynamic Ontology: Applying BFO in the Biomedical Domain. 2004. • Ontogenesis. What is an upper level ontology? 2011. • Ludger Jansen. Chapter 8, Categories: The top-level ontology.

  33. Thanks!

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