1. Chapter 4 Ontology

2. Introduction
– An ontology is an explicit specification of a
conceptualization.
– Computer ontologies are models of known
knowledge.
• Dublin Core (www.dublincore.org) is a set
of very simple elements used to describe
various resources
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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.
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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.
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5. Ontology Construction
– Acquiring the domain knowledge:
– Design the conceptual structure:
– Develop the suitable details:
– Verify:
– Commit:
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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.
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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.
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8. OWL
DAML OIL
RDF
DAML + OIL
OWL
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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.
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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.
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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>
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12. Example 4.17
<?xml version="1.0"?>
<rdf:RDF
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"
xmlns:xsd="http://www.w3.org/2001/XMLSchema#"
xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#"
xmlns:owl="http://www.w3.org/2002/07/owl#"
xmlns="http://www.owl-ontologies.com/unnamed.owl#"
xml:base="http://www.owl-ontologies.com/unnamed.owl">
<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"/>
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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="http://www.w3.org/2001/XMLSchema#int"
>3</owl:minCardinality>
<owl:onProperty>
<owl:DatatypeProperty rdf:ID="age"/>
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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"/>
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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="http://www.w3.org/2001/XMLSchema#int"/>
</owl:DatatypeProperty>
<owl:SymmetricProperty rdf:about="#eats">
<owl:inverseOf rdf:resource="#eats"/>
<rdfs:domain rdf:resource="#Animal"/>
<rdf:type rdf:resource="http://www.w3.org/2002/07/owl#ObjectProperty"/>
</owl:SymmetricProperty>
<owl:DataRange>
<owl:oneOf rdf:parseType="Resource">
<rdf:rest rdf:parseType="Resource">
<rdf:first
rdf:datatype="http://www.w3.org/2001/XMLSchema#string"
>meat</rdf:first>
<rdf:rest rdf:parseType="Resource">
<rdf:first rdf:datatype="http://www.w3.org/2001/XMLSchema#string"
>meat and platns</rdf:first>
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16. Introduction
<rdf:rest rdf:resource="http://www.w3.org/1999/02/22-rdf-syntaxns#
nil"/>
</rdf:rest>
</rdf:rest>
<rdf:first rdf:datatype="http://www.w3.org/2001/XMLSchema#string"
>plants</rdf:first>
</owl:oneOf>
</owl:DataRange>
<Plants rdf:ID="Mosses"/>
<Elephant rdf:ID="Billy">
<age rdf:datatype="http://www.w3.org/2001/XMLSchema#int">4</age>
<hasParent>
<Adult_Rabbit rdf:ID="Betty">
<hasKids rdf:resource="#Billy"/>
</Adult_Rabbit>
</hasParent>
</Rabbit>
<Plants rdf:ID="blackberry"/>
</rdf:RDF>
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17. Knowledge Representation
Description 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.CakeIcing
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18. Knowledge Representation
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19. Ontology Engineering
Feasibility Study
Domain Analysis
Documentation
Knowledge
Acquisition
Evaluation
Ontology
Reuse
Conceptualization
Implementation
Maintenance
Use
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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 5
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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>
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22. Example 4.21
<topic id="ABCU">
<instanceOf>
<topicRef xlink:href="#institution"/>
</instanceOf>
<subjectIdentity>
<subjectIndicatorRef xlink:href="http://home.abcu.in/~Gopalp/psi/hio.psi"/>
</subjectIdentity>
<baseName>
<baseNameString>ABC University</baseNameString>
</baseName>
<occurrence>
<instanceOf>
<topicRef xlink:href="#Website"/>
</instanceOf>
<resourceRef xlink:href="http://www.abcu.in/"/>
</occurrence>
</topic>
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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>
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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.
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25. Suggested Readings
1. 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. http://www.w3.org/TR/2003/CR-owl-ref-20030818/
3. 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.
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