Ontology and Ontology-Based Applications C. Farkas Some of the slides were obtained from presentations of Ian Horrocks

Reading List Ian Horrock’s papers: –Ian Horrocks. DAML+OIL: a reason-able web ontology language. In Proc. of EDBT 2002, number 2287 in Lecture Notes in Computer Science, pages Springer, March –Ian Horrocks, Peter F. Patel-Schneider, and Frank van Harmelen. From SHIQ and RDF to OWL: The making of a web ontology language. Journal of Web Semantics, 2003 OWL Web Ontology Language Overview, features/ features/ Webinar - "Solution Envisioning for Ontology-Based Applications“, DAML+OIL, SWRL: A Semantic Web Rule Language Combining OWL and RuleML,

Web Evolution First generation Web: human generated HTML Second generation Web: machine generated HTML, active HTML pages Third generation Web: automated processing of Web pages, annotations

What is an Ontology Hierarchical description of important concepts in a domain Description of properties of each concepts Example applications: –E-commerce –Search engines –Web services

Ontology Languages Graphical notations –Semantic networks –Topic maps –UML –RDF Logic based –Description Logics (e.g., OIL, DAML+OIL, OWL) –Rules (e.g., RuleML, LP/Prolog) –First Order Logic

Ontology Languages Wide variety of languages for “Explicit Specification” –Logic based –Bayesian/probabilistic/fuzzy Degree of formality varies widely –Increased formality makes languages more amenable to machine processing (e.g., automated reasoning) Copyright: I. Horrocks

Objects/Instances/Individuals –Elements of the domain of discourse –Equivalent to constants in FOL Types/Classes/Concepts –Sets of objects sharing certain characteristics –Equivalent to unary predicates in FOL Relations/Properties/Roles –Sets of pairs (tuples) of objects –Equivalent to binary predicates in FOL Many languages use “object oriented” model based on: Copyright: I. Horrocks

From RDF to OWL Two languages developed to satisfy above requirements –OIL: developed by group of (largely) European researchers (several from EU OntoKnowledge project) –DAML-ONT: developed by group of (largely) US researchers (in DARPA DAML programme) Efforts merged to produce DAML+OIL –Development was carried out by “Joint EU/US Committee on Agent Markup Languages” –Extends (“DL subset” of) RDF DAML+OIL submitted to W3C as basis for standardisation –Web-Ontology (WebOnt) Working Group formed –WebOnt group developed OWL language based on DAML+OIL –OWL language now a W3C Candidate Recommendation –Will soon become Proposed Recommendation Copyright: I. Horrocks

DAML+OIL Design Objectives Well designed –Intuitive to (human) users –Adequate expressive power –Support machine understanding/reasoning Well defined –Clearly specified syntax (obviously) –Formal semantics (equally important) Extend existing web standards –DAML+OIL is built on top of RDF(S) Copyright: I. Horrocks

Why Build on RDF Provides basic ontological primitives –Classes and relations (properties) –Class (and property) hierarchy Can exploit existing RDF infrastructure Provides mechanism for using ontologies –RDF triples assert facts about resources –Use vocabulary from DAML+OIL ontologies Copyright: I. Horrocks

How DAML+OIL Builds ON RDFS (1) Extends expressive power –Constraints (restrictions) on properties of classes (existential/universal/cardinality) –Boolean combinations of classes and restrictions –Equivalence, disjointness –Necessary and sufficient conditions –Constraints on properties Copyright: I. Horrocks

How DAML+OIL Builds ON RDFS (2) Provides well defined semantics –Meaning of DAML+OIL statements is formally specified –Both model theoretic and axiomatic specifications provided –Allows for machine understanding and automated reasoning Copyright: I. Horrocks

Well Designed(?) Intuitive to (human) users –Supports common ontological idioms Adequate expressive power –Extends RDF in several directions Support for machine understanding/reasoning –Designed to be “implementable” –No features for which it is difficult or impossible to define clear semantics (e.g., defaults) –Decidable and (empirically) tractable reasoning Copyright: I. Horrocks

Why Automated Reasoning? Semantic web requires machine understanding (of resource descriptions) –Reasoning is integral to understanding Supports design and use of ontologies –Checking class consistency –Checking/deriving subClassOf hierarchy –Particularly useful when ontologies are large, multi- authored and rapidly evolving –Also useful when integrating/sharing ontologies Does not tell us how to deal with inconsistencies –But we should be able to determine when they exist Copyright: I. Horrocks

DAML+OIL Class Constructs intersectionOf, e.g., Human  Female unioOf, e.g., Female  Scientist complementOf, e.g.,  Female oneOf, e.g., {John, Mary} toClass, e.g.,  hasChild.Scientist hasClass, e.g.,  hasChild.Scientist hasValue, e.g.,  childName.{Peter} minCardinalityQ, e.g., => 2 hasChild.Scientist maxCardinalityQ, e.g., <= 1 hasChild.Scientist cardinalityQ, e.g., =2 hasChild.Scientist

DAML+OIL Syntax Human  Female => 2 hasChild.Scientist

Axioms subClassOf sameClassAs subPropertyOf samePropertyAs disjointWith sameIndividualAs differentIndividualFrom inverseOf transitiveProperty UniqueProperty unambiguousProperty

DAML+OIL Infrastructure Can exploit existing RDF tools/services Ontology editors being built/adapted –OilEd (Manchester) –Protégé (Stanford) –OntoEdit (Karlsruhe) Ontology integration tools being built/adapted –Chimera (Stanford) Reasoning services –DL derived reasoners, e.g., FaCT (used by OilEd) –Rule based reasoners, e.g. SiLri (Karlsruhe) Markup tools Additional tools/infrastructure urgently required Copyright: I. Horrocks

DAML+OIL Summary Ontology language for Semantic Web Extends RDF –More expressive power –Well defined semantics Implementable –Decidable and tractable reasoning –Cost is some restriction on expressive power Extensible –Cost may be loss of (some of) above properties Copyright: I. Horrocks