Ontologies (What they are; Why you Ontologies (What they are; Why you should care; What you should know)should care; What you should know)

Deborah L. McGuinnessDeborah L. McGuinnessAssociate Director and Senior Research ScientistAssociate Director and Senior Research Scientist

Knowledge Systems LaboratoryKnowledge Systems LaboratoryStanford UniversityStanford UniversityStanford, CA 94305Stanford, CA 94305

650-723-9770650-723-9770 dlm@ksl.stanford.edudlm@ksl.stanford.edu

What is an Ontology?What is an Ontology?

Catalog/ID

GeneralLogical

constraints

Terms/glossary

Thesauri“narrower

term”relation

Formalis-a

Frames(properties)

Informalis-a

Formalinstance

Value Restrs.

Disjointness, Inverse, part-

of…

Ontologies and importance to E-CommerceOntologies 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

Ontologies and importance to E-Commerce IIOntologies 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 )

Configuration support Structured, “surgical” comparative customized

search Generalization/ Specialization … Foundation for expansion and leverage

A Few Observations about OntologiesA 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

Implications and NeedsImplications and Needs

Ontology Language Syntax and Semantics (DAML+OIL)

Environments for Creation and Maintenance of Ontologies

Training (Conceptual Modeling, reasoning implications, …)

IssuesIssues 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

Chimaera – A Ontology Chimaera – A Ontology Environment ToolEnvironment 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/chimaera

Discussion/ConclusionDiscussion/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 New generation applications need more expressive ontologies and more back end

reasoningreasoning• New generation users (the general public) need more support than previous users New generation users (the general public) need more support than previous users

of KR&R systemsof KR&R systems• Distributed ontologies need more support: merging, analysis, incompleteness, Distributed ontologies need more support: merging, analysis, incompleteness,

versioning, etc.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, …), EU, W3C, Everyone is in the game – US Government (DARPA, NSF, NIST, …), EU, W3C, consortiums, business, …consortiums, business, …

• This is THE time for ontology work!!!This is THE time for ontology work!!!

Some PointersSome Pointers

Ontologies Come of Age Paper: 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

DAML+OIL: http://www.daml.org/

ExtrasExtras

E-Commerce Search E-Commerce Search (starting point Forrester Research modified by McGuinness)(starting point Forrester Research modified by McGuinness)

Ask Queries - multiple search interfaces (surgical shoppers, advice seekers, window shoppers) - set user expectations (interactive query refinement) - anticipate anomalies Get Answers - basic information (multiple sorts, filtering, structuring) - 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) Make Decisions - manipulate results (enable side by side comparison) - dive deeper (provide additional info, multimedia, other views) - take action (buy)

The Need For KB AnalysisThe Need For KB Analysis 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 developed by multiple authors will frequently

Express overlapping knowledge in different, possibly contradictory ways Use differing assumptions and styles

For such KBs to be used as building blocks -

They must be reviewed for appropriateness and “correctness” That is, they must be analyzed

Our KB Analysis TaskOur KB Analysis Task Review KBs that:

Were developed using differing standards

May be syntactically but not semantically validated

May use differing modeling representations

Produce KB logs (in interactive environments) Identify provable problems

Suggest possible problems in style and/or modeling

Are extensible by being user programmable