Ontologies Come of Age Deborah L. McGuinness Stanford University “The Semantic Web: Why, What, and How, MIT Press, 2001” Presented by Jungyeon, Yang

Copyright  2008 by CEBT Page 2 Outline  Introduction: Web’s growing needs  Ontologies Definition Ontology Spectrum  Uses of Ontology Simple Ontology (taxonomy) Structured Ontology  Ontology-based application Needs Language Environment  Conclusion

Copyright  2008 by CEBT Page 3 Introduction: Web’s growing needs  The web continues to grow at an astounding rate  It’s hard to find the exact information that we want on the web  web pages typically do not contain markup information about the contents of the page  We need to add intelligence to search  Solution: Semantic Web

Copyright  2008 by CEBT Page 4 Introduction: Web’s growing needs  Berners-Lee’s Architecture (Semantic Web Layer cake–old ver.)  In this paper, the ontology and logic layer are discussed What is the mean of them on the web How ontologies could be generated How we use them in applications

Copyright  2008 by CEBT Page 5 Ontologies: Definition  The term ontology has been in use for many years 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

Copyright  2008 by CEBT Page 6 Ontologies: Ontology Spectrum  Web ontologies may be viewed as a spectrum of detail in their specification.  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… A finite list of terms. Controlled vocabularies A finite list of terms. Controlled vocabularies A list of terms and meanings. (natural language statements) A list of terms and meanings. (natural language statements) Additional semantics between terms (Synonyms) Additional semantics between terms (Synonyms) Should not be just “is-a” or strict subclasses Should not be just “is-a” or strict subclasses Strict subclass hierarchy

Copyright  2008 by CEBT Page 7 Uses of ontology : examples  Simple ontology Not as costly to build and potentially more importantly, many are available. 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 Some company such as Cycorp makes available portions of large, detailed ontologies

Copyright  2008 by CEBT Page 8 Uses of simple ontology  provide a controlled vocabulary Every one can use the same vocabulary A start for interoperability  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  support expectation setting By exploring the top level categories, you can quickly determine if the site might have your interest contents Some of the ways that simple ontologies may be used in practice

Copyright  2008 by CEBT Page 9 Uses of simple ontology (Cont.)  “umbrella” structures from which to extend content Some freely available ontologies are attempting to provide the high level taxonomic organization from which many efforts may inherit terms. Example: Universal Standard Products and Services Classification (UNSPSC)  Provide browsing support Content on a site may be tagged with terms from the taxonomy It can help search engines to use enhanced search capabilities

Copyright  2008 by CEBT Page 10 Uses of simple ontology (Cont.)  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  sense disambiguation support If the same term appears in multiple places in a taxonomy, an application may move to a more general level in the taxonomy in order to find the sense of the word Example: “Jordan” as a name of Basket-ball player and name of a country

Copyright  2008 by CEBT Page 11 Uses of structured ontology  Once ontologies begin to have more structure, they can provide more power in applications.  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 Using an ontology, we can complete needed information about things Example: “HighResolutionScreen” contains “verticalResolution” and “horizontalResolution”

Copyright  2008 by CEBT Page 12 Uses of structured ontology (Cont.)  Interoperability support When different users/applications uses 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 If we get too many answers for a query, by using ontology search application can suggest specializing term Opposite case is same.

Copyright  2008 by CEBT Page 13 Uses of structured ontology (Cont.)  support structured, comparative, and customized search if one is looking for televisions, its properties may be obtained in search. 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  The foundation for configuration support Class terms may be defined – they contain descriptions of what kinds of parts may be in a system Interactions between properties can be defined – filling in a value for one property can cause another value to be filled in for another slot

Copyright  2008 by CEBT Page 14 Ontology-based application Needs  Two major concerns Language Environment

Copyright  2008 by CEBT Page 15 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  Solution (in 2001) : DAML+OIL DAML(DARPA Agent Markup Language) program ended in early 2006 OIL(Ontology Inference Language) was incorporated into the OWL  Recent : OWL (Web Ontology Language)

Copyright  2008 by CEBT Page 16 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 OntoEdit

Copyright  2008 by CEBT Page 17 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 – 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 Ease of use

Copyright  2008 by CEBT Page 18 Ontology-based application Needs: Environment (Cont.) Analysis – To support acquisition, evolution and maintenance of ontologies – Analysis can support user’s attention to modification Lifecycle issues – As ontologies become larger and longer lived, it should be supported for evolution, breaking apart, multiple namespaces etc. Diverse user support – Allow users to customize environments as appropriate to the type of user – Work for power users and naïve users Presentation Style – textual, graphical, or other Extensibility – can adapt along with the needs of the users and the projects

Copyright  2008 by CEBT Page 19 Conclusion  Ontologies have a wide spectrum of definitions  Ontologies grows with growth of needs  More complex ontologies can define more precise relations in taxonomies  Ontology have many types of applications  Important issues to build ontologies are Language Environment

Copyright  2008 by CEBT Page 20 My Opinion  Several ways that ontologies may be used in practice and issues are good references when we apply ontologies to specific application.  We have to focus on roles of an ontology A form of an ontology is not fixed. It can be changed according to the purpose of the application.  When we use ontologies, there are some trade-offs between the practical usage and expressive power of it.