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Ontologies: What you should know and why you might care

Ontologies: What you should know and why you might care. Deborah McGuinness Associate Director and Senior Research Scientist Knowledge Systems Laboratory Stanford University Stanford, CA USA dlm@ksl.stanford.edu http://www.ksl.stanford.edu/people/dlm. What is an Ontology?. General

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Ontologies: What you should know and why you might care

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  1. Ontologies: What you should know and why you might care Deborah McGuinness Associate Director and Senior Research Scientist Knowledge Systems Laboratory Stanford University Stanford, CA USA dlm@ksl.stanford.edu http://www.ksl.stanford.edu/people/dlm COGNA October 3, 2003

  2. What is an Ontology? General Description Logics Thesauri “narrower term” relation Formal taxonomy Frames (properties) Catalog/ ID Term Hierarchy (e.g. Yahoo!) Formal instance General Logic Terms/ glossary Value Restrs. *based on AAAI ’99 Ontologies panel – Gruninger, Lehmann, McGuinness, Uschold, Welty Updated by McGuinness, additional input from Gruninger, Uschold, and Rockmore COGNA October 3, 2003

  3. General Nature of Descriptions class a WINE superclass a LIQUID a POTABLE grape: chardonnay, ... [>= 1] sugar-content: dry, sweet, off-dry color: red, white, rose price: a PRICE winery: a WINERY grape dictates color (modulo skin) harvest time and sugar are related general categories number/card restrictions structured components Roles/ properties value restrictions interconnections between parts COGNA October 3, 2003

  4. Some uses of Ontologies Simple ontologies (taxonomies) provide: • Controlled shared vocabulary (search engines, authors, users, databases, programs/agents all speak same language) • Site Organization, Navigation Support, Expectation setting • “Umbrella” Upper Level Structures (for extension e.g., UNSPSC) • Browsing support (tagged structures such as Yahoo!) • Search support (query expansion approaches such as FindUR, e-Cyc; structured search) • Sense disambiguation (e.g., TAP) COGNA October 3, 2003

  5. Semantic Web Vision Today’s web enriched with information encoding term meaning enabling applications that are: • Able to understand term meaning and user background • Interoperable (can translate between applications and vocabularies) • Programmable (thus agent operational) • Explainable (thus maintains context and can adapt) • Capable of filtering (thus limiting display and human intervention requirements) • Capable of executing services COGNA October 3, 2003

  6. Semantic Enablers • Languages for representing terms in vocabularies • Tools for generating, maintaining, and evolving ontologies • Tools for reasoning with and using semantically enhanced applications Facilitated by W3C, Govt - DARPA, ARDA, NSF, NIST, EU, … COGNA October 3, 2003

  7. DARPA’s DAML/W3C’s OWL Language • Web Languages • RDF/S • XML DAML-ONT DAML+OIL (OWL) OIL Formal Foundations Description Logics Frame Systems FACT, CLASSIC, DLP, … COGNA October 3, 2003

  8. Ontology Resources… • Upper Level Ontologies- UNSPSC, SUMO, OpenCyc, OpenDirectory, TAP, … • Specialized Ontologies (Many beyond just GML) • Geography Ontology CIA World Fact Book geographic regions; WFB climate data interpreted using Koeppen Climate Classification system- www.fao.org/WAICENT/FAOINFO/sustdev/EIdirect/climate/EIsp0002.htm 3. Sea Level definitions - www.pol.ac.uk/psmsl/puscience/index.html • Geography Ontology - geographical ontology & theory in FOL capable of accessing and utilizing information from a variety of agents, including Alexandria Digital Library Gazetteer, TerraVision, the CIA World Factbook, Teknowledge's ASCS, and Landsat and GDACC satellite data repositories. Using axiomatic characterizations of these agents’ capabilities, in conjunction with SNARK's procedural-attachment mechanism and the OAA agent library, the combined theory is capable of finding answers that must be inferred from more than one of these sources because no one source has the entire answer • Ontology Libraries • http://www.daml.org/ontologies/ • http://www.ksl.stanford.edu/ontolingua • “Advisory” bodies - Semantic Web Science Foundation, NIST, Ontology.org • Ontology Consultants COGNA October 3, 2003

  9. Ontology Tools Tools developing: http://www.daml.org/tools/ and http://www.w3.org/2001/sw/WebOnt/impls#Implementations Annotation Ontology Translation Browser Persistence Crawler Query Tools Editor RDMS Mapping Graph Visualizer Report Generation Transformation Search Validator Ontology Analyzer Importer Ontology Editor Inference Engine Merging Many are in research labs, but companies emerging and lasting… Network Inference, Sandpiper, Ontoprise, AppliedSemantics, Sentius, …. COGNA October 3, 2003

  10. Conclusion/Discussion • Ontologies are taking off in terms of languages, tools, environments, and applications • Rich representation languages exist for representing taxonomies, thesauri, and beyond. • Transition paths exist from standard languages such as XML to other web standards like RDF and OWL • Ontology toolkits for ontology building, evolution, merging, etc. exist today and are growing quickly (academics, government, and industry) • Ontology libraries exist and are worth considering for leverage, connections, and merging COGNA October 3, 2003

  11. Selected Papers: • McGuinness. Ontologies come of age, 2003 • Das, Wei, McGuinness, Industrial Strength Ontology Evolution Environments, 2002. • Kendall, Dutra, McGuinness. Towards a Commercial Strength Ontology Development Environment, 2002. • McGuinness Description Logics Emerge from Ivory Towers, 2001. • McGuinness. Ontologies and Online Commerce, 2001. • McGuinness. Conceptual Modeling for Distributed Ontology Environments, 2000. • McGuinness, Fikes, Rice, Wilder. An Environment for Merging and Testing Large Ontologies, 2000. • Brachman, Borgida, McGuinness, Patel-Schneider. Knowledge Representation meets Reality, 1999. • McGuinness. Ontological Issues for Knowledge-Enhanced Search, 1998. • McGuinness and Wright. Conceptual Modeling for Configuration, 1998. • Selected Tutorials: • -Smith, Welty, McGuinness. OWL Web Ontology Language Guide, 2003. • Noy, McGuinness. Ontology Development 101: A Guide to Creating your First Ontology. 2001. • Brachman, McGuinness, Resnick, Borgida. How and When to Use a KL-ONE-like System, 1991. • Languages, Environments, Software: • OWL - http://www.w3.org/TR/owl-features/ , http://www.w3.org/TR/owl-guide/ • DAML+OIL: http://www.daml.org/ • - Inference Web - http://www.ksl.stanford.edu/software/iw/ • - Chimaera - http://www.ksl.stanford.edu/software/chimaera/ • FindUR - http://www.research.att.com/people/~dlm/findur/ • - TAP – http://tap.stanford.edu/ • - DQL - http://www.ksl.stanford.edu/projects/dql/ Pointers COGNA October 3, 2003

  12. EXTRAS COGNA October 3, 2003

  13. OWL Lite Features • RDF Schema Features • Class, rdfs:subClassOf , Individual • rdf:Property, rdfs:subPropertyOf • rdfs:domain , rdfs:range • Equality and Inequality • sameClassAs , samePropertyAs , sameIndividualAs • differentIndividualFrom • Restricted Cardinality • minCardinality, maxCardinality (restricted to 0 or 1) • cardinality (restricted to 0 or 1) • Property Characteristics • inverseOf , TransitiveProperty , SymmetricProperty • FunctionalProperty(unique) , InverseFunctionalProperty • allValuesFrom, someValuesFrom (universal and existential local range restrictions) • Datatypes • Following the decisions of RDF Core. • Header Information • imports , Dublin Core Metadata , versionInfo COGNA October 3, 2003

  14. OWL Features • Class Axioms • oneOf (enumerated classes) • disjointWith • sameClassAs applied to class expressions • rdfs:subClassOf applied to class expressions • Boolean Combinations of Class Expressions • unionOf • intersectionOf • complementOf • Arbitrary Cardinality • minCardinality • maxCardinality • cardinality • Filler Information • hasValue Descriptions can include specific value information COGNA October 3, 2003

  15. Chimaera: Ontology Environment Tool • An interactive web-based tool aimed at supporting: • Ontology analysis (correctness, completeness, style, …) • Merging of ontological terms from varied sources • Maintaining ontologies over time • Validation of input • Features: multiple I/O languages, loading and merging into multiple namespaces, collaborative distributed environment support, integrated browsing/editing environment, extensible diagnostic rule language • Used in commercial and academic environments, basis of some commercial re-implementations (Ontobuilder/Ontoserver, …) • Available as a hosted service from www-ksl-svc.stanford.edu • Information:www.ksl.stanford.edu/software/chimaera COGNA October 3, 2003

  16. Layer Cake Foundation COGNA October 3, 2003

  17. XML • World Wide Web Consortium (W3C) standard • Provides important solution to syntax problem and simple semantics and schemas: <SSN>555-17-1234</SSN> • Now we can describe the meaning of words • Many applications of XML appearing: • Geographic Markup Language (GML) • Extensible rights Markup Language (XrML) • Chemical Markup Language (CML) Problem: Limited semantics, limited ontology creation COGNA October 3, 2003

  18. DARPA Agent Markup Language • http://www.daml.org/about.html • Extends the vocabulary of XML and RDF/S • Provides rich ontology representation language • Language features chosen so language may have efficient implementations COGNA October 3, 2003

  19. DAML+OIL -> W3C • W3C Webont working group formed with DAML+OIL submission as starting point http://www.w3.org/Submission/2001/12/ COGNA October 3, 2003

  20. WEBONT participation…. • Includes over 50 members from over 30 organizations. • Industry including: • Large companies such as Daimler Chrysler, EDS, Fujitsu, HP, IBM, Intel, Lucent, Nokia, Philips Electronics, Sun, Unisys, … • Newer/smaller companies such as IVIS Group, Network Inference, Stilo Technology, Unicorn Solutions, … • Government and Not-For-Profits: • Defense Information Systems Agency, Interoperability Technology Association for Information Processing, Japan (INTAP) , Intelink Mgt Office, Mitre, … • Universities and Research Centers: • University of Bristol, University of Maryland, University of Southamptom, Stanford University, … • DFKI (German Research Center for Artificial Intelligence), Forschungszentrum Informatik • Invited Experts • Well-known academics from non-W3C members COGNA October 3, 2003

  21. Simple Ontology-Enhanced Apps COGNA October 3, 2003

  22. COGNA October 3, 2003

  23. Human Human Today: Rich Information Source for Human Manipulation/Interpretation COGNA October 3, 2003

  24. “I know what was input” • Global documents and terms indexed and available for search • Search engine interfaces • Entire documents retrieved according to relevance (instead of answers) • Human input, review, assimilation, integration, action, etc. • Special purpose interfaces required for user friendly applications The web knows what was input but does little interpretation, manipulation, integration, and action. Analogous to a new assistant who is thorough yet lacks common sense, context, and adaptability COGNA October 3, 2003

  25. Human Agent Agent Tomorrow: Rich Information Source for Agent Manipulation/Interpretation COGNA October 3, 2003

  26. “I know what was meant” • Understand term meaning and user background • Interoperable (can translate between applications) • Programmable (thus agent operational) • Explainable (thus maintains context and can adapt) • Capable of filtering (thus limiting display and human intervention requirements) • Capable of executing services COGNA October 3, 2003

  27. Contact Information dlm@ksl.stanford.edu www.ksl.stanford.edu/people/dlm COGNA October 3, 2003

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