1 / 29

Semantic Web Ontologies

Semantic Web Ontologies. CS 431 – 20040317 Carl Lagoze – Cornell University. Acknowledgements: Alun Preece. Components of the Semantic Web. Knowledge Representation and AI meeting the Web. Knowledge representation is not new Formalisms Semantic networks Frame systems Frames (objects)

jana
Télécharger la présentation

Semantic Web Ontologies

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Semantic Web Ontologies CS 431 – 20040317 Carl Lagoze – Cornell University Acknowledgements: Alun Preece

  2. Components of the Semantic Web

  3. Knowledge Representation and AI meeting the Web • Knowledge representation is not new • Formalisms • Semantic networks • Frame systems • Frames (objects) • Slots (attributes and properties) • Languages • LOOM • Classic • Cyc-L • Logics • Description Logics (DLs)

  4. So why re-invent it for the Web • Not re-invention • Same underlying formalisms (frames, slots, description logic) • But new factors • Massive scale • Tractability • Knowledge expressiveness must be limited or reasoning must be incomplete • Lack of central control • Need for federation • Inconsistency, lies, re-interpretations, duplications • New facts appear and modify constantly • Open world vs. Close world assumptions • Contrast to most reasoning systems that assume anything absent from knowledge base is not true • Need to maintain monotonicity with tolerance for contradictions • Need to build on existing standards • URI, XML, RDF

  5. Why aren’t XML schema good enough? • XML schema is designed to primarily describe structure and constraints on documents • Rich datatypes • Grammar for describing structure of elements (and attributes) • Incomplete modeling of is-a relationships • Top-down inheritance of attributes from superclasses to subclasses with extension and restriction is clumsy • E.g., student as person with a student # and age<28 • Bottom-up inheritance of instances to superclasses is not automatic

  6. Brief review of RDF • Data model for defining machine-processible semantics of data • Three main object types: • Resources • Primitive metadata is URI • Properties • Sub-class of resource • Statements • (:s :p :o) • Graph model that is serializable in XML

  7. RDF Schemas A building block for assembling ontology languages • Declaration of vocabularies • Classes and class hierarchies • properties defined by a particular community • characteristics of properties and/or constraints on corresponding values • Provides substructure for inferences based on existing triples • Schema language is an expression of basic RDF model • Schema Type System - Basic Types • Property, Class, SubClassOf, Domain, Range • Minimal (but extensible) at this time • Expressible in the RDF model and syntax

  8. What is an Ontology? • A formal specification of conceptualization shared in a community • Vocabulary for defining a set of things that exist in a world view • Formalization allows communication across application systems and extension • Parallel concepts in other areas: • Domains: database theory • Types: AI • Classes: OO systems • Types/Sorts: Logic • Global vs. Domain-specific

  9. “An ontology is an explicit, partial specification of a conceptualization that is expressible as a meta-level viewpoint on a set of possible domain theories for the purpose of modular design, redesign and reuse of knowledge-intensive system components” (Schreiber, Wielinga & Janswijer, 1995) Relevant relations Universe of discourse <{a, b, c, d, e}, {on, above, clear, table}>

  10. XML and RDF are ontologically neutral • No standard vocabulary just primitives • Resource, Class, Property, Statement, etc. • Compare to classic first order logic • Conjunction, disjunction, implication, existential, universal quantifier

  11. Components of an Ontology • Vocabulary (concepts) • Structure (attributes of concepts and hierarchy) • Logical characteristics of concepts & attributes • Domain and range restrictions • Properties of relations (symmetry, transitivity)

  12. Wordnet • On-line lexical reference system, domain-independent • >100,000 word meanings organized in a taxonomy with semantic relationships • Synonymy, meronymy, hyponymy, hypernymy • Useful for text retrieval, etc. • http://www.cogsci.princeton.edu/~wn/online/

  13. CYC • Effort in AI community to accommodate all of human knowledge!!! • Formalizes concepts with logical axioms specifying constraints on objects and classes • Associated reasoning tools • Contents are proprietary but there is OpenCyc • http://www.opencyc.org/

  14. Ontologies for the Web • Lots of Participants and $$$ • Web Ontology Working Group • Distributed Agent Markup Language • Ontology Inference Layer • OntoWeb • Schemas Project • OWL (Web Ontology Language) – develop standard for encoding ontologies on top of RDF Schema

  15. Web Ontology Language (OWL) • W3C Web Ontology Working Group (WebOnt) • Follow on to DAML, OIL efforts • W3C Recommendation • Vocabulary extension of RDF

  16. Extending RDF(S) with OWL RDFS OWL • Class definition: Conjunction, disjunction, negation • Property constraints: universality, existence, cardinality • Properties of properties: transitivity, symmetry • Class, sub-class definition • Property (attribute), sub-property definition • Domain, range constraints

  17. Species of OWL • OWL Lite • Good for classification hierarchies with simple constraints (e.g., thesauri) • Reasoning is computational simple and efficient • OWL DL • Computationally complete and decidable (computation in finite time) • Correspondence to description logics (decidable fragment of first-order logic) • OWL Full • Maximum expressiveness • No computational guarantees (probably never will be) • Each language is extension of simpler predecessor

  18. Description Logics • Fragment of first-order logic designed for logical representation of object-oriented formalisms • Frames/classes • Do not stress representation of behaviors • High expressivity with decidability and completeness • Universal and existential quantification, disjunction, conjunction, negation • Concepts, roles, individuals • Representation as a collection of statements, with unary and binary predicates that stand for concepts and roles, from which deductions can be made

  19. OWL Lite Summary

  20. OWL DL and Full Summary

  21. Namespaces and OWL

  22. OWL Class Definition

  23. Why owl:class vs. rdfs:class • Rdfs:class is “class of all classes” • In DL class can not be treated as individuals (undecidable) • Thus owl:class, which is expressed as rdfs:subclass of rdfs:class • No problem for standard rdf processors since an owl:class “is a” rdfs:class • Note: there are other times you want to treat class of individuals • Class drinkable liquids has instances wine, beer, …. • Class wine has instances merlot, chardonnay, zinfandel, …

  24. OWL class building operations • disjointWith • No vegetarians are carnivores • sameClassAs (equivalence) • Enumerations (on instances) • The Ivy League is Cornell, Harvard, Yale, …. • Boolean set semantics (on classes) • Union (logical disjunction) • Class parent is union of mother, father • Intersection (logical conjunction of class with properties) • Class WhiteWine is conjunction of things of class wine and have property white • complimentOf (logical negation) • Class vegetarian is disjunct of class carnivore

  25. OWL Properties

  26. OWL property building operations & restrictions • Transitive Property • P(x,y) and P(y,z) -> P(x,z) • SymmetricProperty • P(x,y) iff P(y,x) • Functional Property • P(x,y) and P(x,z) -> y=z • inverseOf • P1(x,y) iff P2(y,x) • InverseFunctional Property • P(y,x) and P(z,x) -> y=z • Cardinality • Only 0 or 1 in lite and full

  27. OWL DataTypes • Full use of XML schema data type definitions • Examples • Define a type age that must be a non-negative integer • Define a type clothing size that is an enumeration “small” “medium” “large”

  28. OWL Instance Creation • Create individual objects filling in slot/attribute/property definitions <Person ref:ID=“William Arms”> <rdfs:label>Bill</rdfs:label> <age><xsd:integer rdf:value=“57”/></age> <shoesize><xsd:decimal rdf:value=“10.5”/></shoesize></Person>

  29. Language Comparison

More Related