Chapter 4 semantic web


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Chapter 4 semantic web

  1. 1. Chapter 4 Ontology
  2. 2. Introduction – An ontology is an explicit specification of a conceptualization. – Computer ontologies are models of known knowledge.• Dublin Core ( is a set of very simple elements used to describe various resourcesAkerkar: Foundations of © Narosa Publishing House, 2009 2Semantic Web.
  3. 3. Introduction• Definition 4.4: A taxonomy is a hierarchically-organised controlled vocabulary. – Taxonomies are semantically weak and are commonly used when navigating without a precise research goal in mind.• Definition 4.5: A thesaurus is a controlled vocabulary arranged in a known order and structured so that equivalence, homographic, hierarchical, and associative relationships among terms are displayed clearly and identified by standardized relationship indicators.Akerkar: Foundations of © Narosa Publishing House, 2009 3Semantic Web.
  4. 4. Meta-model• A meta-model is an explicit description of the constructs and rules needed to build specific models within a domain of interest.• Meta-model – Ontology: – Formalization: must be expressed in a formal language to enable consistency checks and automated reasoning, – Consensuality: must be agreed upon by a community. – Identifiability: must be unambiguously identified and ubiquitously accessible over the Internet.Akerkar: Foundations of © Narosa Publishing House, 2009 4Semantic Web.
  5. 5. Ontology Construction – Acquiring the domain knowledge: – Design the conceptual structure: – Develop the suitable details: – Verify: – Commit:Akerkar: Foundations of © Narosa Publishing House, 2009 5Semantic Web.
  6. 6. Ontology Languages – be compatible with existing Web standards, – define terms precisely and formally with adequate expressive power, – be easy to understand and use, – provide automated reasoning support, – provide richer service descriptions which could be interpreted by intelligent agents, – be sharable across applications.Akerkar: Foundations of © Narosa Publishing House, 2009 6Semantic Web.
  7. 7. DAML+OIL – Constraints on properties (existential/universal and cardinality), – Boolean combinations of classes and restrictions, e.g., union, complement and intersection, – Equivalence and disjointness, – Necessary and sufficient conditions.Akerkar: Foundations of © Narosa Publishing House, 2009 7Semantic Web.
  8. 8. OWL DAML OIL RDF DAML + OIL OWLAkerkar: Foundations of © Narosa Publishing House, 2009 8Semantic Web.
  9. 9. OWL• With the formal semantics of OWL, we can reason about – Class membership. If x is an instance of a class C, and C is a subclass of D, then we can infer that x is an instance of D. – Equivalence of classes. If class A is equivalent to class B, and class B is equivalent to class C, then A is equivalent to C, too. – Consistency. Suppose we have declared x to be an instance of the class A and that A is a subclass of B n C, A is a subclass of D, and B and D are disjoint. Then we have an inconsistency because A should be empty, but has the instance x. This is an indication of an error in the ontology. – Classification. If we have declared that certain property-value pairs are a sufficient condition for membership in a class A, then if an individual x satisfies such conditions, we can conclude that x must be an instance of A.Akerkar: Foundations of © Narosa Publishing House, 2009 9Semantic Web.
  10. 10. OWL Sub-languages – OWL Full: It is the entire language, thus provides for maximum expressivity. – It allows an ontology to enhance the meaning of the pre-defined (RDF or OWL) vocabulary. – However, it offers no computational guarantees. – OWL DL: This language has theoretical properties of Description Logic. – It permits efficient reasoning. – Every legal OWL DL document is a legal RDF document. – OWL DL is intended in instances where completeness and decidability are important. – OWL Lite: It uses simple constraints and reasoning, and has the lower formal complexity among the OWL sublanguages. – This language is basically intended for class hierarchies and limited constraints.Akerkar: Foundations of © Narosa Publishing House, 2009 10Semantic Web.
  11. 11. Example 4.5 <owl:Indian Subcontinent> <owl:oneOf rdf:parseType="Collection"> <owl:Thing rdf:about="#India"/> <owl:Thing rdf:about=“#Bangala Desh"/> <owl:Thing rdf:about="#Pakistan"/> </owl:oneOf> </owl:Indian Subcontinent>Akerkar: Foundations of © Narosa Publishing House, 2009 11Semantic Web.
  12. 12. Example 4.17 <?xml version="1.0"?> <rdf:RDF xmlns:rdf="" xmlns:xsd="" xmlns:rdfs="" xmlns:owl="" xmlns="" xml:base=""> <owl:Ontology rdf:about=""/> <owl:Class rdf:ID="Animal"/> <owl:Class rdf:ID="Herbivore"> <owl:equivalentClass> <owl:Class> <owl:intersectionOf rdf:parseType="Collection"> <owl:Class rdf:about="#Animal"/> <owl:Restriction> <owl:onProperty> <owl:SymmetricProperty rdf:ID="eats"/>Akerkar: Foundations of © Narosa Publishing House, 2009 12Semantic Web.
  13. 13. </owl:onProperty> <owl:allValuesFrom> <owl:Class rdf:ID="Plants"/> </owl:allValuesFrom> </owl:Restriction> </owl:intersectionOf> </owl:Class> </owl:equivalentClass> </owl:Class> <owl:Class rdf:ID="Adult_Rabbit"> <owl:equivalentClass> <owl:Class> <owl:intersectionOf rdf:parseType="Collection"> <owl:Class rdf:ID="Rabbit"/> <owl:Restriction> <owl:minCardinality rdf:datatype="" >3</owl:minCardinality> <owl:onProperty> <owl:DatatypeProperty rdf:ID="age"/>Akerkar: Foundations of © Narosa Publishing House, 2009 13Semantic Web.
  14. 14. </owl:onProperty> </owl:Restriction> </owl:intersectionOf> </owl:Class> </owl:equivalentClass> </owl:Class> <owl:Class rdf:about="#Rabbit"> <rdfs:subClassOf rdf:resource="#Animal"/> </owl:Class> <owl:ObjectProperty rdf:ID="hasKids"> <rdfs:range rdf:resource="#Rabbit"/> <rdfs:domain rdf:resource="#Adult_Rabbit"/> <owl:inverseOf> <owl:ObjectProperty rdf:ID="hasParent"/> </owl:inverseOf> </owl:ObjectProperty> <owl:ObjectProperty rdf:about="#hasParent"> <rdfs:range rdf:resource="#Adult_Rabbit"/>Akerkar: Foundations of © Narosa Publishing House, 2009 14Semantic Web.
  15. 15. <owl:inverseOf rdf:resource="#hasKids"/> <rdfs:domain rdf:resource="#Rabbit"/> </owl:ObjectProperty> <owl:DatatypeProperty rdf:about="#age"> <rdfs:domain rdf:resource="#Animal"/> <rdfs:range rdf:resource=""/> </owl:DatatypeProperty> <owl:SymmetricProperty rdf:about="#eats"> <owl:inverseOf rdf:resource="#eats"/> <rdfs:domain rdf:resource="#Animal"/> <rdf:type rdf:resource=""/> </owl:SymmetricProperty> <owl:DataRange> <owl:oneOf rdf:parseType="Resource"> <rdf:rest rdf:parseType="Resource"> <rdf:first rdf:datatype="" >meat</rdf:first> <rdf:rest rdf:parseType="Resource"> <rdf:first rdf:datatype="" >meat and platns</rdf:first>Akerkar: Foundations of © Narosa Publishing House, 2009 15Semantic Web.
  16. 16. Introduction <rdf:rest rdf:resource=" nil"/> </rdf:rest> </rdf:rest> <rdf:first rdf:datatype="" >plants</rdf:first> </owl:oneOf> </owl:DataRange> <Plants rdf:ID="Mosses"/> <Elephant rdf:ID="Billy"> <age rdf:datatype="">4</age> <hasParent> <Adult_Rabbit rdf:ID="Betty"> <hasKids rdf:resource="#Billy"/> </Adult_Rabbit> </hasParent> </Rabbit> <Plants rdf:ID="blackberry"/> </rdf:RDF>Akerkar: Foundations of © Narosa Publishing House, 2009 16Semantic Web.
  17. 17. Knowledge RepresentationDescription logics:Cake, Icing and CakeBase are disjunctive concepts/classes.• We use three inclusion axioms: • Cake ⊆ ¬Icing • Cake ⊆ ¬CakeBase • Icing ⊆ ¬CakeBase• A chocolate cake is defined as a cake, having an icing and having a cake base. The icing is a chocolate icing, while the base is a CakeBase. A chocolate icing is a icing. • ChocolateCake = Cake • ∩ (∃ hasIcing.ChocolateIcing) • ∩ (∃ hasCakeBase.CakeBase) • ChocolateIcing ⊆ Icing• The domain of the relation icing is cake, while the range is icing. We use two following axioms. The first axiom defines the domain, the second defines the range. ∃ hasIcping. ? ⊆ Cake ?⊆ ∀ hasIcing.CakeIcingAkerkar: Foundations of © Narosa Publishing House, 2009 17Semantic Web.
  18. 18. Knowledge RepresentationAkerkar: Foundations of © Narosa Publishing House, 2009 18Semantic Web.
  19. 19. Ontology Engineering Feasibility Study Domain Analysis Documentation Knowledge Acquisition Evaluation Ontology Reuse Conceptualization Implementation Maintenance UseAkerkar: Foundations of © Narosa Publishing House, 2009 19Semantic Web.
  20. 20. Topic Maps Topic A Topic Maps Topic AA Topic AB Resources Web Page 1 Web Page 2 Web Page 3 Web Page 4 Web Page 5Akerkar: Foundations of © Narosa Publishing House, 2009 20Semantic Web.
  21. 21. Example 4.20 <topic id="Gopal"> <instanceOf> <topicRef xlink:href="#employee"/> </instanceOf> <instanceOf> <topicRef xlink:href="#teacher"/> </instanceOf> <baseName> <baseNameString>Gopal Sharma</baseNameString> </baseName> <occurrence> <instanceOf> <topicRef xlink:href="#description"/> </instanceOf> <resourceData>Gopal has worked at ABC University since 2001</resourceData> </occurrence> </topic>Akerkar: Foundations of © Narosa Publishing House, 2009 21Semantic Web.
  22. 22. Example 4.21 <topic id="ABCU"> <instanceOf> <topicRef xlink:href="#institution"/> </instanceOf> <subjectIdentity> <subjectIndicatorRef xlink:href=""/> </subjectIdentity> <baseName> <baseNameString>ABC University</baseNameString> </baseName> <occurrence> <instanceOf> <topicRef xlink:href="#Website"/> </instanceOf> <resourceRef xlink:href=""/> </occurrence> </topic>Akerkar: Foundations of © Narosa Publishing House, 2009 22Semantic Web.
  23. 23. Example 4.22 <association id=" Gopal-abcu-association"> <instanceOf> <topicRef xlink:href="#employment"/> </instanceOf> <member> <roleSpec><topicRef xlink:href="#employee"/></roleSpec> <topicRef xlink:href="#Gopal"/> </member> <member> <roleSpec><topicRef xlink:href="#employer"/></roleSpec> <topicRef xlink:href="#hio"/> </member> </association>Akerkar: Foundations of © Narosa Publishing House, 2009 23Semantic Web.
  24. 24. RDF and Topic Maps• RDF is predictive: it can ad hoc describe verbs in the role of direct relationships.• In Topic Maps: connections can be made between events in this context.• Some more distinct points are, – There are two ways of using URIs to identify things, whereas only one way URI can be used. – There are different approaches for reification and qualification. – The distinction between three types of assertions in Topic Maps, and only one in RDF.Akerkar: Foundations of © Narosa Publishing House, 2009 24Semantic Web.
  25. 25. Suggested Readings1. F. Baader, I. Horrocks & U. Sattler. Description Logics as Ontology Languages for the Semantic Web. Lecture Notes in Artificial Intelligence. Springer, 2003.2. M. Dean & G. Schreiber. ‘OWL Web Ontology Language: Reference’. World Wide Web Consortium, 2003. A. Gomez-Perez & M. D. Rojas. Ontological Reengineering and Reuse. 11th European Workshop on Knowledge Acquisition, Modeling and Management (EKAW ’99, Germany). Lecture Notes in Artificial Intelligence LNAI 1621 Springer- Verlag, 139-156, 1999. (Eds., Fensel D. & Studer R).4. J. Heflin. OWL Web Ontology Language Use Cases and Requirements. W3C Recommendation, 2004.5. I. Horrocks. DAML+OIL: a reasonable Web ontology language. Proc. of EDBT 2002, Lecture Notes in Computer Science 2287, 2-13, Springer, 2002.6. A. Maedche. Ontology Learning for the Semantic Web. Kluwer Academic Publishers, 2002.7. TopicMaps.Org XTM Authoring Group. XTM: XML Topic Maps (XTM) 1.0, TopicMaps.Org Specification, 2001.8. M. Uschold & M. King. Towards a Methodology for Building Ontologies. IJCAI’95 Workshop on Basic Ontological Issues in Knowledge Sharing. Ed. D., Skuce, 6.1- 6.10, 1995.9. McGuinness D.L. & van Harmele, F. OWL Web Ontology Language – Overview, W3C Recommendation, 2004.Akerkar: Foundations of © Narosa Publishing House, 2009 25Semantic Web.