1. 17 April 2005Sharif University of Tech Page 1 Ontologies Come of Age Amir Hossein Assiaee a_assiaee@ce.sharif.edu

2. Sharif University of TechPage 2 17 April 2005 Outline Introduction: Web’s growing needs Ontologies  Definition  Ontology Spectrum Uses of Ontology  Simple  Structured Ontology Acquisition Ontology-based application Needs  Language  Environment Conclusion

3. Sharif University of TechPage 3 17 April 2005 Outline Introduction: Web’s growing needs Ontologies  Definition  Ontology Spectrum Uses of Ontology  Simple  Structured Ontology Acquisition Ontology-based application Needs  Language  Environment Conclusion

4. Sharif University of TechPage 4 17 April 2005 Introduction: Web’s growing needs The web continues to grow at an astounding rate Finding the exact information one is seeking on the web today is hard web pages do not contain markup information about the contents of the page We need to add intelligence to search Solution: Semantic Web

5. Sharif University of TechPage 5 17 April 2005 Introduction: Web’s growing needs (Cont.) Berner’s Lee Architecture

6. Sharif University of TechPage 6 17 April 2005 Introduction: Web’s growing needs (Cont.) Berner’s Lee Architecture We will consider at:

7. Sharif University of TechPage 7 17 April 2005 Outline Introduction: Web’s growing needs Ontologies  Definition  Ontology Spectrum Uses of Ontology  Simple  Structured Ontology Acquisition Ontology-based application Needs  Language  Environment Conclusion

8. Sharif University of TechPage 8 17 April 2005 Ontologies: Definition The term ontology has been in use for many years. 1720 Merriam Webster: Dates Ontology There are two historical definition: A branch of metaphysics concerned with the nature and relations of being A particular theory about the nature of being or the kinds of existents From the view point of computational audience:  “A specification of a conceptualization” by Gruber

9. Sharif University of TechPage 9 17 April 2005 Ontologies: Ontology Spectrum One might visualize a simple (linear) spectrum of definitions Catalog/ ID General Logical constraints Terms/ glossary Thesauri “narrower term” relation Formal is-a Frames (properties) Informal is-a Formal instance Value Restrs. Disjointnes s, Inverse, part-of…

10. Sharif University of TechPage 10 17 April 2005 Ontologies: Ontology Spectrum (Cont.) Catalogs: (a finite list of terms) can provide an unambiguous interpretation of terms Glossary: (a list of terms and meanings) provides a kind of semantics, since humans can read the natural language statements and interpret them Thesauri: provide some additional semantics in their relations between terms They provide information such as synonym relationships. They do not provide an explicit hierarchy

11. Sharif University of TechPage 11 17 April 2005 Ontologies: Ontology Spectrum (Cont.) Hierarchical:  People prefer to have an explicit hierarchy  Yahoo, for example, provides a small number of top-level categories This hierarchy should not be just “isa” or strict subclasses (informal is-a) Sometimes it is strict subclass hierarchy (formal is- a)

12. Sharif University of TechPage 12 17 April 2005 Ontologies: Ontology Spectrum (Cont.) Frames:  Classes include property information Example: “apparel” has property “price” and “isMadeFrom” All subclasses of these categories would inherit these properties Value Restriction:  Here we may place restrictions on what can fill a property “isMadeFrom” and the value restriction of material a “price” property might be restricted to have a filler that is a number

13. Sharif University of TechPage 13 17 April 2005 Ontologies: Ontology Spectrum (Cont.) Logical Constraints  Ontologies need to express more information  Expressive ontology languages needed Example: Ontolingua, CycL

14. Sharif University of TechPage 14 17 April 2005 Outline Introduction: Web’s growing needs Ontologies  Definition  Ontology Spectrum Uses of Ontology  Simple  Structured (sophisticated) Ontology Acquisition Ontology-based application Needs  Language  Environment Conclusion

15. Sharif University of TechPage 15 17 April 2005 Uses of ontology Simple ontology example:  DMOZ, for example, leverages over 35,000 volunteer editors and at publication time, had over 360,000 classes in a taxonomy Sophisticated ontology example:  the unified medical language system (UMLS), developed by the national library of medicine is a large sophisticated ontology about medical terminology

16. Sharif University of TechPage 16 17 April 2005 Uses of ontology: simple provide a controlled vocabulary  Every one can use the same vocabulary  Programs can generate interfaces to encourage usage of the controlled terms site organization and navigation support  Many web sites today expose on the left hand side of a page the top levels of a generalization hierarchy of terms.  Categories can expand to subcategories

17. Sharif University of TechPage 17 17 April 2005 Uses of ontology: simple (Cont.) support expectation setting  By exploring the top level categories you can determine, if the site have your interest content taxonomies may be used as “umbrella” structures from which to extend content  There are some freely categories at high level that you can inherit some terms form them.  Example: Universal Standard Products and Services Classification (UNSPSC)

18. Sharif University of TechPage 18 17 April 2005 Uses of ontology: simple (Cont.) browsing support  Content on a site may be tagged with terms from the taxonomy  Can be done: manually automatically (using a clustering approach)  It can help search engines to use enhanced search capabilities search support  A query expansion method may be used in order to expand a user query with terms from more specific categories in the hierarchy

19. Sharif University of TechPage 19 17 April 2005 Uses of ontology: simple (Cont.) sense disambiguation support  If the same term appears in multiple places in a taxonomy, an application may move to a more general level  Example: “Jordan” as a name of Basket-ball player and name of a country

20. Sharif University of TechPage 20 17 April 2005 Uses of ontology: Structured Once ontologies begin to have more structure, they can provide more power in applications.

21. Sharif University of TechPage 21 17 April 2005 Uses of ontology: Structured (Cont.) consistency checking  If ontologies contain value restrictions on the properties, then type checking can be done within applications  example, “Goods” has a property called “price” that has a value restriction of number Completion  By an ontology we can complete needed information about things  “HighResolutionScreen” contains “verticalResolution” and “horizontalResolution”

22. Sharif University of TechPage 22 17 April 2005 Uses of ontology: Structured (Cont.) Interoperability support  Since different users/applications are using the same set of terms,  We can use equality axioms to express one term precisely in terms of another  Example: StanfordEmployee ≡ Person ∩ Employer(Stanford University) exploit generalization/specialization information  One may get too many answers for a query, by using ontology search application can suggest specializing that term  And vice versa

23. Sharif University of TechPage 23 17 April 2005 Uses of ontology: Structured (Cont.) support structured, comparative, and customized search  if one is looking for televisions, a class description for television may be obtained from an ontology, its properties may be obtained (such as diagonal, price, manufacturer, etc)  a comparative presentation may be made of televisions by presenting the values of each of the properties  Search interfaces can help you by showing more detailed properties of product

24. Sharif University of TechPage 24 17 April 2005 Uses of ontology: Structured (Cont.) The foundation for configuration support  Classes defined so that they contain descriptions of what kinds of parts may be in a system  Interactions between properties can be defined so that filling in a value for one property can cause another value to be filled in for another slot  Example: a class of HighQualityTelevisions is defined so that users may choose from this class and the configurator will automatically fill in limited sets of manufacturers to choose from minimum price ranges

25. Sharif University of TechPage 25 17 April 2005 Outline Introduction: Web’s growing needs Ontologies  Definition  Ontology Spectrum Uses of Ontology  Simple  Structured Ontology Acquisition Ontology-based application Needs  Language  Environment Conclusion

26. Sharif University of TechPage 26 17 April 2005 Ontology Acquisition Some sources of ontologies:  many ontologies exist in the public domain  Many taxonomic structures exist on the web or in the table of contents of documents Where to look for exiting ontologies:  Standard organizations: NIST (the National Institute of Standards and Technology - http://www.nist.gov/) http://www.nist.gov/ Some consortiums are forming to generate ontologies RosettaNet (http://www.rosettanet.org)http://www.rosettanet.org

27. Sharif University of TechPage 27 17 April 2005 Outline Introduction: Web’s growing needs Ontologies  Definition  Ontology Spectrum Uses of Ontology  Simple  Structured Ontology Acquisition Ontology-based application Needs  Language  Environment Conclusion

28. Sharif University of TechPage 28 17 April 2005 Ontology-based application Needs Two major concerns  Language  Environment

29. Sharif University of TechPage 29 17 April 2005 Ontology-based application Needs: Language An ontology must be encoded in some language As we saw the spectrum is very wide and it contains simple and sophisticated ontologies  The language should support both  More expressive = More complex ontologies = More sophisticated language needed

30. Sharif University of TechPage 30 17 April 2005 Ontology-based application Needs: Language (Cont.) Some candidates: KRSS – the Knowledge Representation System Specification [Patel-Schneider-Swartout 1992] KIF -the Knowledge Interchange Format OKBC – Open Knowledge Base Connectivity [Chaudhri-et-al, 1997] Current solution: DAML+OIL

31. Sharif University of TechPage 31 17 April 2005 Ontology-based application Needs: Environment We need an environment for ontologies to analyze, modify, and maintain an ontology over time Some examples: “Verity” is a topic editor to generating taxonomies Ontolingua [Farquhar-et-al 1997] Stanford University Chimaera [McGuinness-et-al. 2000] Stanford University OilEd from Manchester University [Protégé 2000] from Stanford Medical Informatics

32. Sharif University of TechPage 32 17 April 2005 Ontology-based application Needs: Environment (Cont.) There are some issues to consider for choosing ontology environment: Collaboration and distributed workforce support: (allow users to share a session –i.e., see each other’s work environments) Platform interconnectivity: example Java-based applications Scale Versioning Security:  Differing access to portions of ontology  Environment should expose portions of ontology based on security model

33. Sharif University of TechPage 33 17 April 2005 Ontology-based application Needs: Environment (Cont.) Analysis:  To support acquisition, evolution and maintenance  Analysis can support users attention to modification and … Lifecycle issues:  ontologies become larger and longer lived  It should be supported for evolution, breaking apart, multiple namespaces etc. Ease of use Diverse user support  Allow users to customize environments as appropriate to the type of user  Work for power users and naïve users

34. Sharif University of TechPage 34 17 April 2005 Ontology-based application Needs: Environment (Cont.) Presentation Style  textual, graphical, or other Extensibility  can adapt along with the needs of the users and the projects

35. Sharif University of TechPage 35 17 April 2005 Outline Introduction: Web’s growing needs Ontologies  Definition  Ontology Spectrum Uses of Ontology  Simple  Structured Ontology Acquisition Ontology-based application Needs  Language  Environment Conclusion

36. Sharif University of TechPage 36 17 April 2005 Conclusion Ontologies have a wide spectrum of definitions They grows with growth of needs More complex ontologies can define more precise relations in taxonomies They have many types of applications Important issues to build ontologies are Language Environment