1. Ontologies Come of Age Deborah L. McGuinness Associate Director and Senior Research Scientist Knowledge Systems Laboratory Stanford University Stanford, CA 94305 650-723-9770 dlm@ksl.stanford.edu dlm@ksl.stanford.edu

2. June 12, 2003 1McGuinness - Mitre What is an Ontology? Catalog/ ID General Description Logics Terms/ glossary Thesauri “narrower term” relation Formal taxonomy Frames (properties) Term Hierarchy (e.g. Yahoo!) Formal instance Value Restrs. General Logic *based on AAAI ’99 Ontologies panel – Gruninger, Lehmann, McGuinness, Uschold, Welty Updated by McGuinness, additional input from Gruninger, Uschold, and Rockmore

3. June 12, 2003 2McGuinness - Mitre General Nature of Descriptions a WINE 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 structured components interconnections between parts number/card restrictions value restrictions class superclass Roles/ properties

4. June 12, 2003 3McGuinness - Mitre Some uses of Ontologies Simple ontologies (taxonomies) provide: Controlled shared vocabulary (search engines, authors, users, databases, programs/agents all speak same language) Controlled shared vocabulary (search engines, authors, users, databases, programs/agents all speak same language) Site Organization, Navigation Support, Expectation setting Site Organization, Navigation Support, Expectation setting “Umbrella” Upper Level Structures (for extension e.g., UNSPSC) “Umbrella” Upper Level Structures (for extension e.g., UNSPSC) Browsing support (tagged structures such as Yahoo!) Browsing support (tagged structures such as Yahoo!) Search support (query expansion approaches such as FindUR, e-Cyc) Search support (query expansion approaches such as FindUR, e-Cyc) Sense disambiguation (e.g., TAP) Sense disambiguation (e.g., TAP)

5. June 12, 2003 4McGuinness - Mitre FindUR Architecture Search Engine Content to Search: Search Technology: User Interface: Verity (and topic sets) Content (Web Pages or Databases CLASSIC Knowledge Representation System Results (domain specific) Verity SearchScript, Javascript, HTML, CGI, CLASSIC Content Classification Domain Knowledge Results (standard format) GUI supporting browsing and selection Research Site Technical Memorandum Calendars (Summit 2005, Research) Yellow Pages (Directory Westfield) Newspapers (Leader) Internal Sites (Rapid Prototyping) AT&T Solutions Worldnet Customer Care Medical Information Domain Knowledge Collaborative Topic Set Tool

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10. June 12, 2003 9McGuinness - Mitre Uses of Ontologies II Consistency Checking Consistency Checking Completion Completion Interoperability Support Interoperability Support Support for validation and verification testing (e.g. http://ksl.stanford.edu/projects/DAML/chimaera- jtp-cardinality-test1.daml ) Support for validation and verification testing (e.g. http://ksl.stanford.edu/projects/DAML/chimaera- jtp-cardinality-test1.daml ) http://ksl.stanford.edu/projects/DAML/chimaera- jtp-cardinality-test1.daml http://ksl.stanford.edu/projects/DAML/chimaera- jtp-cardinality-test1.daml Configuration support Configuration support Structured, “surgical” comparative customized search Structured, “surgical” comparative customized search Generalization / Specialization Generalization / Specialization … Foundation for expansion and leverage … Foundation for expansion and leverage

11. June 12, 2003 10McGuinness - Mitre KSL Wine Agent Semantic Web Integration Wine Agent receives a meal description and retrieves a selection of matching wines available on the Web, using an ensemble of emerging standards and tools: DAML+OIL / OWL for representing a domain ontology of foods, wines, their properties, and relationships between them JTP theorem prover for deriving appropriate pairings DQL for querying a knowledge base consisting of the above Inference Web for explaining and validating the response [Web Services for interfacing with vendors] Utilities for conducting and caching the above transactions

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13. June 12, 2003 12McGuinness - Mitre Processing Given a description of a meal, Given a description of a meal, Use DQL to state a premise (the meal) and query the knowledge base for a suggestion for a wine description or set of instances Use DQL to state a premise (the meal) and query the knowledge base for a suggestion for a wine description or set of instances Use JTP Theorem Prover to deduce answers (and proofs) Use JTP Theorem Prover to deduce answers (and proofs) Use Inference Web to explain results (descriptions, instances, provenance, reasoning engines, etc.) Use Inference Web to explain results (descriptions, instances, provenance, reasoning engines, etc.) Access relevant web sites (wine.com, wine commune, …) to access current information Access relevant web sites (wine.com, wine commune, …) to access current information Use DAML-S for markup and protocol* Use DAML-S for markup and protocol* http://www.ksl.stanford.edu/projects/wine/explanation.html

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17. June 12, 2003 16McGuinness - Mitre A Few Observations about Ontologies Simple ontologies can be built by non-experts Simple ontologies can be built by non-experts Verity’s Topic Editor, Collaborative Topic Builder, GFP, Chimaera, Protégé, OIL-ED, etc. Verity’s Topic Editor, Collaborative Topic Builder, GFP, Chimaera, Protégé, OIL-ED, etc. Ontologies can be semi-automatically generated Ontologies can be semi-automatically generated from crawls of site such as yahoo!, amazon, excite, etc. from crawls of site such as yahoo!, amazon, excite, etc. Semi-structured sites can provide starting points Semi-structured sites can provide starting points Ontologies are exploding (business pull instead of technology push) Ontologies are exploding (business pull instead of technology push) e-commerce - MySimon, Amazon, Yahoo! Shopping, VerticalNet, … e-commerce - MySimon, Amazon, Yahoo! Shopping, VerticalNet, … Controlled vocabularies (for the web) abound - SIC codes, UMLS, UNSPSC, Open Directory (DMOZ), Rosetta Net, SUMO Controlled vocabularies (for the web) abound - SIC codes, UMLS, UNSPSC, Open Directory (DMOZ), Rosetta Net, SUMO Business interest expanding – ontology directors, business ontologies are becoming more complicated (roles, value restrictions, …), VC firms interested, Business interest expanding – ontology directors, business ontologies are becoming more complicated (roles, value restrictions, …), VC firms interested, Markup Languages growing XML, RDF, DAML, RuleML, xxML Markup Languages growing XML, RDF, DAML, RuleML, xxML “Real” ontologies are becoming more central to applications “Real” ontologies are becoming more central to applications Search companies moving towards them – Yahoo, recently Google Search companies moving towards them – Yahoo, recently Google

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20. June 12, 2003 19McGuinness - Mitre Implications and Needs for Ontology-enhanced applications Ontology Language Syntax and Semantics (DAML+OIL, OWL) Ontology Language Syntax and Semantics (DAML+OIL, OWL) Upper Level/Core ontologies for reuse (Cyc, SUMO, CNS coalition, DAML-S…) Upper Level/Core ontologies for reuse (Cyc, SUMO, CNS coalition, DAML-S…) Environments for Creation of Ontologies (Protégé, Sandpiper, Construct, OilEd, …) Environments for Creation of Ontologies (Protégé, Sandpiper, Construct, OilEd, …) Environments for Maintenance of Ontologies (Chimaera, OntoBuilder, …) Environments for Maintenance of Ontologies (Chimaera, OntoBuilder, …) Reasoning Environments (Cerebra, Fact, JTP, Snark, …) Reasoning Environments (Cerebra, Fact, JTP, Snark, …) Distributed explanation support (Inference Web) Distributed explanation support (Inference Web) Training (Conceptual Modeling, reasoning usage, tutorials – OWL Guide, Ontologies 101, OWL Tutorial, …) Training (Conceptual Modeling, reasoning usage, tutorials – OWL Guide, Ontologies 101, OWL Tutorial, …)

21. June 12, 2003 20McGuinness - Mitre Discussion/Conclusion Ontologies are exploding; core of many applicationsOntologies are exploding; core of many applications Business “pull” is driving ontology language tools and languagesBusiness “pull” is driving ontology language tools and languages New generation applications need more expressive ontologies and more back end reasoningNew generation applications need more expressive ontologies and more back end reasoning New generation users (the general public) need more support than previous users of KR&R systemsNew generation users (the general public) need more support than previous users of KR&R systems Distributed ontologies need more support: merging, analysis, explanation support, incompleteness techniques, versioning, etc.Distributed ontologies need more support: merging, analysis, explanation support, incompleteness techniques, versioning, etc. Scale and distribution of the web force mind shiftScale and distribution of the web force mind shift Everyone is in the game – US Government (DARPA, NSF, NIST, ARDA…), EU, W3C, consortiums, business, …Everyone is in the game – US Government (DARPA, NSF, NIST, ARDA…), EU, W3C, consortiums, business, … Consulting and product companies are in the space (not just academics)Consulting and product companies are in the space (not just academics) This is THE time for ontology work!!!

22. June 12, 2003 21McGuinness - MitrePointers Selected Papers: - McGuinness. Ontologies come of age, 2003Ontologies come of age - Das, Wei, McGuinness, Industrial Strength Ontology Evolution Environments, 2002.Industrial Strength Ontology Evolution Environments - Kendall, Dutra, McGuinness. Towards a Commercial Strength Ontology Development Environment, 2002.Towards a Commercial Strength Ontology Development Environment - McGuinness Description Logics Emerge from Ivory Towers, 2001.Description Logics Emerge from Ivory Towers - McGuinness. Ontologies and Online Commerce, 2001.Ontologies and Online Commerce - McGuinness. Conceptual Modeling for Distributed Ontology Environments, 2000.Conceptual Modeling for Distributed Ontology Environments - McGuinness, Fikes, Rice, Wilder. An Environment for Merging and Testing Large Ontologies, 2000.An Environment for Merging and Testing Large Ontologies - Brachman, Borgida, McGuinness, Patel-Schneider. Knowledge Representation meets Reality, 1999.Knowledge Representation meets Reality - McGuinness. Ontological Issues for Knowledge-Enhanced Search, 1998.Ontological Issues for Knowledge-Enhanced Search - McGuinness and Wright. Conceptual Modeling for Configuration, 1998. Selected Tutorials: -Smith, Welty, McGuinness. OWL Web Ontology Language Guide, 2003.OWL Web Ontology Language Guide -Noy, McGuinness. Ontology Development 101: A Guide to Creating your First Ontology. 2001.Ontology Development 101: A Guide to Creating your First Ontology - 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/http://www.w3.org/TR/owl-features/http://www.w3.org/TR/owl-guide/ - DAML+OIL: http://www.daml.org/http://www.daml.org/ - Inference Web - http://www.ksl.stanford.edu/software/iw/http://www.ksl.stanford.edu/software/iw/ - Chimaera - http://www.ksl.stanford.edu/software/chimaera/http://www.ksl.stanford.edu/software/chimaera/ - FindUR - http://www.research.att.com/people/~dlm/findur/http://www.research.att.com/people/~dlm/findur/ - TAP – http://tap.stanford.edu/http://tap.stanford.edu/ - DQL - http://www.ksl.stanford.edu/projects/dql/http://www.ksl.stanford.edu/projects/dql/

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25. June 12, 2003 24McGuinness - Mitre DAML/OWL Language Web Languages RDF/S XML DAML-ONT Formal Foundations Description Logics FACT, CLASSIC, DLP, … Frame Systems DAML+OIL OWL OIL Extends vocabulary of XML and RDF/S Rich ontology representation language Language features chosen for efficient implementations

26. June 12, 2003 25McGuinness - MitreIssues Collaboration among distributed teams Collaboration among distributed teams Interconnectivity with many systems/standards Interconnectivity with many systems/standards Analysis and diagnosis Analysis and diagnosis Scale Scale Versioning Versioning Security Security Ease of use Ease of use Diverse training levels / user support Diverse training levels / user support Presentation style Presentation style Lifecycle Lifecycle Extensibility Extensibility

27. June 12, 2003 26McGuinness - Mitre Services Ontologies DAML-S http://www.daml.org/services/ publication references publication references ontology specifications ontology specifications examples examples A few interesting projects using DAML-S: MyGrid: (http://mygrid.man.ac.uk) MyGrid: (http://mygrid.man.ac.uk) AgentCities (http://www.agentcities.org) AgentCities (http://www.agentcities.org) Services composer (http://www.mindswap.org/~evren/composer/) Services composer (http://www.mindswap.org/~evren/composer/)

28. June 12, 2003 27McGuinness - Mitre General Nature of Descriptions a WINE 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 structured components interconnections between parts

29. June 12, 2003 28McGuinness - MitreSUMO Available in KIF (first order logic), DAML, LOOM and XML Available in KIF (first order logic), DAML, LOOM and XML May be used without fee for any purpose (including for profit) May be used without fee for any purpose (including for profit) Mapped by hand to 100,000 synsets of WordNet lexicon Mapped by hand to 100,000 synsets of WordNet lexicon Validated with formal theorem proving Validated with formal theorem proving 52 publicly released versions created over two years (approximately 1,000 concepts, 4000 assertions, and 750 rules so far) 52 publicly released versions created over two years (approximately 1,000 concepts, 4000 assertions, and 750 rules so far) Specialized with dozens of free domain ontologies Specialized with dozens of free domain ontologies In use by companies, universities and government around the world In use by companies, universities and government around the world Acadmica Sinica – Taiwan, U Arizona, lookwayup.com, NIST etc Acadmica Sinica – Taiwan, U Arizona, lookwayup.com, NIST etc Available at http://ontology.teknowledge.com Available at http://ontology.teknowledge.com

30. June 12, 2003 29McGuinness - Mitre Chimaera – A 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; used in HORUS to support counter-terrorism ontology generation Available as a hosted service from www-ksl-svc.stanford.edu Information: www.ksl.stanford.edu/software/chimaerawww.ksl.stanford.edu/software/chimaera

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34. June 12, 2003 33McGuinness - Mitre Some Pointers Ontologies Come of Age Paper: http://www.ksl.stanford.edu/people/dlm/papers/ontol ogies-come-of-age-abstract.html Ontologies Come of Age Paper: http://www.ksl.stanford.edu/people/dlm/papers/ontol ogies-come-of-age-abstract.html http://www.ksl.stanford.edu/people/dlm/papers/ontol ogies-come-of-age-abstract.html http://www.ksl.stanford.edu/people/dlm/papers/ontol ogies-come-of-age-abstract.html Ontologies and Online Commerce Paper: http://www.ksl.stanford.edu/people/dlm/papers/ontol ogies-and-online-commerce-abstract.html Ontologies and Online Commerce Paper: http://www.ksl.stanford.edu/people/dlm/papers/ontol ogies-and-online-commerce-abstract.html http://www.ksl.stanford.edu/people/dlm/papers/ontol ogies-and-online-commerce-abstract.html http://www.ksl.stanford.edu/people/dlm/papers/ontol ogies-and-online-commerce-abstract.html DAML+OIL: http://www.daml.org/ DAML+OIL: http://www.daml.org/http://www.daml.org/ WEBONT: http://www.w3.org/2001/sw/WebOnt/ WEBONT: http://www.w3.org/2001/sw/WebOnt/http://www.w3.org/2001/sw/WebOnt/ OWL: http://www.w3.org/TR/owl-features/ OWL: http://www.w3.org/TR/owl-features/http://www.w3.org/TR/owl-features/

35. June 12, 2003 34McGuinness - Mitre E-Commerce Search (starting point Forrester Research modified by McGuinness) Ask Queries Ask Queries - multiple search interfaces (surgical shoppers, advice seekers, window shoppers) - multiple search interfaces (surgical shoppers, advice seekers, window shoppers) - set user expectations (interactive query refinement) - set user expectations (interactive query refinement) - anticipate anomalies - anticipate anomalies Get Answers Get Answers - basic information (multiple sorts, filtering, structuring) - basic information (multiple sorts, filtering, structuring) - modify results (user defined parameters for refining, user profile info, narrow query, broaden query, disambiguate query) - modify results (user defined parameters for refining, user profile info, narrow query, broaden query, disambiguate query) - suggest alternatives (suggest other comparable products even from competitor’s sites) - suggest alternatives (suggest other comparable products even from competitor’s sites) Make Decisions Make Decisions - manipulate results (enable side by side comparison) - manipulate results (enable side by side comparison) - dive deeper (provide additional info, multimedia, other views) - dive deeper (provide additional info, multimedia, other views) - take action (buy) - take action (buy)

36. June 12, 2003 35McGuinness - Mitre The Need For KB Analysis Large-scale knowledge repositories will necessarily contain KBs produced by multiple authors in multiple settings Large-scale knowledge repositories will necessarily contain KBs produced by multiple authors in multiple settings KBs for applications will typically be built by assembling and extending multiple modular KBs from repositories that may not be consistent KBs for applications will typically be built by assembling and extending multiple modular KBs from repositories that may not be consistent KBs developed by multiple authors will frequently KBs developed by multiple authors will frequently Express overlapping knowledge in different, possibly contradictory ways Express overlapping knowledge in different, possibly contradictory ways Use differing assumptions and styles Use differing assumptions and styles For such KBs to be used as building blocks - For such KBs to be used as building blocks - They must be reviewed for appropriateness and “correctness” That is, they must be analyzed That is, they must be analyzed

37. June 12, 2003 36McGuinness - Mitre Our KB Analysis Task Review KBs that: Review KBs that: Were developed using differing standards Were developed using differing standards May be syntactically but not semantically validated May be syntactically but not semantically validated May use differing modeling representations May use differing modeling representations Produce KB logs (in interactive environments) Produce KB logs (in interactive environments) Identify provable problems Identify provable problems Suggest possible problems in style and/or modeling Suggest possible problems in style and/or modeling Are extensible by being user programmable Are extensible by being user programmable