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Semantic Web & Ontology

Reyhan Aydoğan20/02/2007

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Semantic Web Information on the Web

Both human and machine understandable Deal with

Presentation of information Meaning of content and structure

Example Applications [1] Task-Centered Knowledge Support through

Semantic Markup Semantic Gadget in a museum Advance Search Engines

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Example 1 [2]

Search the web for performing particular task The system understands the task of users and

gives better service in order to achieve the goal.

E.g. when the user search the car keyword, if the system can understand the user’s task is to repair the car, it can perform search in accordance with the task instead of a general search.

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Example 1: Two dimensions

Anticipatability: measures the how easy or difficult to anticipate the question US History “Who was the 19th U.S. present” Easy “Is Pat Hayes related to Rutherford Hayes” Difficult

Frequency of occurrence: Who the current U.S. president is, is more frequent

than who the 19th U.S. president is. By limiting the domain, we can better

anticipate the kinds of tasks people working on.

Support in the frequently asked and moderately anticipatable questions.

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Example2 [3]

Apply Semantic Web onto Ubiquitous Computing Semantic gadget in a museum Guide and recommend in accordance

with environmental conditions with using semantics

If the temperature is too warm and we do not like to carry our coat, the gadget may suggest leaving it in the car

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Ontology “Specification of concepts and their

meanings” Shared and common understanding

of knowledge concerning domain of interests

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Gruber Ontology Definition

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Describing Semantics [4]

Individual

PropertyClass

Wine

ChateauMorgonBordeaux

hasColor

is an instance of

has value for

restrict

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Class Construct

The ontological class concept Related to Object class in OOP

Class Represents a group of individuals

with similar property Eg. Food, Wine, Person,

Restaurant

Class

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Property Construct Property construct associates

Attribute/ value pairs with instances Binary association relating an instance

to another instance or a simple data value

E.g. price, size, name, color Similar to accessor method in OOP

But, a property can be associated with multiple unrelated classes rather than a single class

Property

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Individuals Individuals represent

Class object instances in the domain Similar to objects in OOP

But individuals are only information representations and not have associated functionality

E.g. Mark, MyPieSlice, KnightRestaurant “It is difficult to differentiate between

individuals and classes” [4]

Individual

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Meanings

<Sentence><Subject>

Wine</Subject><Verb>

is made from</Verb><Object>

Grape </Object>

</Sentence>

DocumentOntology

Natural Language

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Ontology Main elements of an ontology:

Concepts Relationships

Hierarchical Logical

Properties Instances (individuals)

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Semantic Relationships [4]

Synonymy Relation (Equivalence) Two names for the same meaning Eg. “Restaurant and “Eating

Establisment” [class-class] “Cost” and “price” [property-property] “John Smith” and

“Restaurant123Owner”[individual-individual]

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Semantic Relationships cont.

Antonymy Relation Identifies opposite concepts Disjointness: An item cannot be an

instance of both of the disjoint items E.g. “Regular Priced Menu Item” and

“Sale Priced Menu Item”

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Semantic Relationships cont.

Hyponymy Relation (is-a relationship) Specialization or generalization Taxonomical hierarchies

Dessert

Pie Cake

Specialization

Generalization

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Semantic Relationships cont.

Meronymy/Holonymy Relation Part-of relation Defines composition or part-of

relationsSpaghetti and Meatballs Dish

Spaghetti Meatballs

Holonymy Meronymy

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RDF (Resource Description Framework)

Simple language Captures statements

Triples of <subject, predicate, object> E.g. <Eric Miller, hasTitle, Dr. >

Express the content itself Resources uniquely identified to

prevent confusion

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Example= Resources (URI)

=Literals

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Xml-based syntax

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Example <?xml version="1.0"?><RDF> <Description about="http://www.w3schools.com/RDF"> <author>Jan Egil Refsnes</author><homepage>http://www.w3schools.com</homepage></Description> </RDF> Subject: "http://www.w3schools.com/RDF"> Predicate : author Object: Jan Egil Refsnes

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Attributes

The <rdf:Description> element contains the description of the resource identified by the rdf:about attribute.

<rdf:ID> is for identification of resource where <rdf:about> is for referring a resource.

Rdf:type specifies the type of subject

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RDF Schema Language for describing RDF vocabulary Extension of RDF RDF talks about the object where RDF

Schema defines classes for objects Be able to represent a hierarchy of

classes “subClassOf” property

Use some constraints on properties Domain and range

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Example <?xml version="1.0"?><rdf:RDF xmlns:rdf= "http://www.w3.org/1999/02/22-rdf-syntaxns#" xmlns:rdfs=http://www.w3.org/2000/01/rdf-schema#xml:base= "http://www.animals.fake/animals#"><rdf:Description rdf:ID="animal"><rdf:type

rdf:resource="http://www.w3.org/2000/01/rdfschema#Class"/>

</rdf:Description><rdf:Description rdf:ID="horse"> <rdf:type

rdf:resource="http://www.w3.org/2000/01/rdfschema#Class"/>

<rdfs:subClassOf rdf:resource="#animal"/> </rdf:Description></rdf:RDF>

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SubClassOF

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RDF Schema Example

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Discussion from 494 course slide [Pinar Yolum] JAVA: Class book has an attribute author of typeperson RDF: There is an author property between a bookand a person JAVA: If you are talking about a newspaper, youneed to define a new author attribute (Local scope) RDF: Define an author property once. (Globalscope) JAVA: You can’t talk about an author attributewithout a class RDF: You can if you don’t specify a domain

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Discussion from 494 course slide [Pinar Yolum] JAVA:

– Class sportsarcticle has an attribute author of type male– Class newsarticle has an attribute author of type female

RDF: Cannot match different domains with ranges JAVA is prescriptive

- Won’t allow a male as the author of a news article RDF is descriptive; usage is application-dependent

– Enforce constraints (like JAVA)– If the author of a news article is not known infer female– Accept the existence of a news article without an author– Accept a news article with an editor attribute instead

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OWL

Web Ontology Language Two types of property

Data property: string, int and so on Object property has characteristics:

Symmetric Transitive Functional inverseOf Inverse functional

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Symmetric Property P(x,y) iff P(y,x)

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Transitive Property P(x,y) and P(y,z) implies P(x, z)

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Functional Property P(x,y) and P(x,z) implies y = z

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InverseOf P1(x,y) iff P2(y,x)

<owl:ObjectProperty rdf:ID="hasMaker"><rdf:type

rdf:resource="&owl;FunctionalProperty" /></owl:ObjectProperty> <owl:ObjectProperty

rdf:ID="producesWine"> <owl:inverseOf rdf:resource="#hasMaker" />

</owl:ObjectProperty>

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Property Constraints

allValuesFrom, someValuesFrom <owl:onProperty rdf:resource="#hasMaker" />

<owl:allValuesFrom rdf:resource="#Winery" />

cardinality <owl:onProperty rdf:resource="#hasVintageYear"/>

<owl:cardinality rdf:datatype="&xsd;nonNegativeInteger">1

</owl:cardinality>

hasValue <owl:onProperty rdf:resource="#hasSugar" />

<owl:hasValue rdf:resource="#Dry" />

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Others Disjoint

Equivalence <owl:Class rdf:ID="TexasThings"> <owl:equivalentClass> <owl:Restriction> <owl:onProperty rdf:resource="#locatedIn" />

<owl:someValuesFrom rdf:resource="#TexasRegion" /> </owl:Restriction>

</owl:equivalentClass> </owl:Class>

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SPARQL: Query Language

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Conclusion

Ontology Tool Protégé

Ontology API KAON2 & JENA

Query Language: SPARQL

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References [1] Fensel, D., J. Hendler, H. Lieberman and W. Wahlster,

Spinning the Semantic Web, MIT Press, Cambridge, 2003. [2] Jasper, R. and M. Uschold, “Enabling Task-Centered

Knowledge Support though Semantic Markup”, In Spinning the Semantic Web, pp. 223-251, MIT Press, Cambridge,2003.

[3] Lassila, O. and M. Adler, “Ubiquitous Computing Meets the Semantic Web”, In Spinning the Semantic Web, pp. 363-376, MIT Press, Cambridge, 2003.

[4] Lee, W. L. , OWL: Representing Informaton Using the Web Ontology Language, Trafford Publishing, 2005.

[5] Munindar P. Singh and Michael N. Huhns, Service-Oriented Computing: Semantics, Processes, Agents, Wiley, 2004

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References For examples:

http://www.w3schools.com/ [5] Service-Oriented Computing: Semantics, Processes,

Agents

Discussion http://www.cmpe.boun.edu.tr/courses

/cmpe494/fall2005/slides/soc-slides-rdf.pdf

OWL http://www.w3.org/TR/owl-guide/