1. The Semantic Web 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

2. Today: Rich Information Source for Human Manipulation/Interpretation Human

3. “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

4. Information Discovery… but not much more Human intensive (requiring input reformulation and interpretation) Display intensive (requiring filtering) Not interoperable Not agent-operational Not adaptive Limited context Limited service Analogous to a new assistant who is thorough yet lacks common sense, context, and adaptability

5. Future: Rich Information Source for Agent Manipulation/Interpretation HumanAgent

6. “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

7. Semantic Markup Languages such as DAML+OIL (www.daml.org)www.daml.org Encoding background info User modeling info Annotating web pages Annotating services thereby limiting needs for human disambiguation input, human interpretation, multiple answer display, translation assistance, agent assistance, adaptivity support, etc.) Ontologies DAML-enabled web pages

8. The Semantic Web enables… New models of intelligent services E-commerce solutions M-commerce Web assistants … E-commerce solutions M-commerce The Semantic Web Enables… New forms of web assistants/agents that act on a human’s behalf requiring less from humans and their communication devices…

9. Under the covers Meaning needs to be encoded, understood, and reasoned with. -- Ontologies capture meanings of terms and their interrelationships

10. What is an Ontology? Catalog/ ID General Logical constraints Terms/ glossary Thesauri “narrower term” relation Formal is-a Frames (properties) Informal is-a Formal instance Value Restrs. Disjointness, Inverse, part- of…

11. Ontologies and importance to E-Commerce Simple ontologies (taxonomies) provide: Controlled shared vocabulary (search engines, authors, users, databases, programs/agents all speak same language) Site Organization and Navigation Support Expectation setting (left side of many web pages) “Umbrella” Upper Level Structures (for extension) Browsing support (tagged structures such as Yahoo!) Search support (query expansion approaches such as FindUR, e-Cyc) Sense disambiguation

12. Ontologies and importance to E-Commerce II Consistency Checking Completion Interoperability Support 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 Configuration support Structured, “surgical” comparative customized search Generalization/ Specialization … Foundation for expansion and leverage

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

14. Implications and Needs Ontology Language Syntax and Semantics (DAML+OIL) Environments for Creation and Maintenance of Ontologies Training (Conceptual Modeling, reasoning implications, …)

15. Issues –Collaboration among distributed teams –Interconnectivity with many systems/standards –Analysis and diagnosis –Scale –Versioning –Security –Ease of use –Diverse training levels /user support –Presentation style –Lifecycle –Extensibility

16. 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 Available as a hosted service from www-ksl-svc.stanford.edu Information: www.ksl.stanford.edu/software/chimaerawww.ksl.stanford.edu/software/chimaera

17. XML World Wide Web Consortium (W3C) standard Provides important solution to syntax problem and simple semantics and schemas: 444-23-2656 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 and ontology

18. DARPA Agent Markup Language Builds on top of XML and RDF Provides rich ontology representation Key starting point for W3C Semantic Web activity Future releases will provide logic and rules capabilities Problem: Tools to help create DAML ontologies, markup, and to facilitate access are still emerging

19. EXAMPLES Fred Jones Information About Fred Jones Fred Jones is in the U.S. Air Force. He is a Captain stationed at AFRL. HTML Fred Jones U.S. Air Force AFRL Captain XML Fred Smith http://www.w3.org/1999/02/22-rdf-syntax-ns#http://www.daml.org/2001/03/daml+oil#http://www.dod.mil/personnel#http://www.af.mil/personnel#http://www.rl.af.mil/personnel#http://www.dod.mil/services#AirForcehttp://www.af.mil/personnel#Captainhttp://www.af.mil/stations#AFRL_Rome DAML

20. DAML Status DAML ontology language specification released and in use DAML services language specification draft released http://www.daml.org provides public Web site with DAML information Research and corporate teams are developing DAML tools Supported by W3C in the Semantic Web Activity Endorsed by companies and interest growing

21. Trustworthy Web Resources HyperText Markup Language HyperText Transfer Protocol Resource Description Framework eXtensible Markup Language Self-Describing Documents Foundation of the Current Web Proof, Logic and Ontology Languages Shared terms/terminology Machine-Machine communication 1990 2000 2010? (from Berners-Lee, Hendler; Nature, 4/01)

22. 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 Scale and distribution of the web force mind shiftScale and distribution of the web force mind shift Markup languages will revolutionize web applicationsMarkup languages will revolutionize web applications Agents can be human proxies enabling new applications and modes of interactionAgents can be human proxies enabling new applications and modes of interaction

23. Some Pointers Ontologies Come of Age Paper: http://www.ksl.stanford.edu/people/dlm/papers/ ontologies-come-of-age-abstract.html http://www.ksl.stanford.edu/people/dlm/papers/ ontologies-come-of-age-abstract.html Ontologies and Online Commerce Paper: http://www.ksl.stanford.edu/people/dlm/papers/ ontologies-and-online-commerce-abstract.html http://www.ksl.stanford.edu/people/dlm/papers/ ontologies-and-online-commerce-abstract.html DAML+OIL: http://www.daml.org/http://www.daml.org/

24. Extras

25. What Is An Agent? Software module Intended to act as a proxy for you in some way May be: –Tightly controlled –Autonomous –Mobile

26. Why Is This Important? Humans work sequentially Agents work in parallel and 24x7 Therefore, agents can be a major productivity multiplier

27. Web Trends Web is evolving from a provider of documents and images (information retrieval) To a provider of services Web service discovery - Find me an airline service that offers flights to Singapore Web service execution - Buy me “Harry Potter and the Sorcerer’s Stone” at www.amazon.com Web service selection, composition and interoperation - Make my travel arrangements for my Internet World conference trip Both retrieval and services lend themselves to agent technologies

28. Problems Average Web searches examine only 25% of available information Web searches return a lot of unwanted information Information content of the Web doubles approximately every six months Problem continues to worsen as Web grows