Ontology Languages - Semantic Web Lab.

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20 Οκτ 2013 (πριν από 3 χρόνια και 11 μήνες)

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Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

1


Sohn Jong
-
Soo


Intelligent Information System lab.

Department of Computer Science

Korea University



Ontology Languages

Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

2

Index

1.

Ontology

2.

XML

3.

RDF

4.

OIL

5.

DAML

6.

OWL

Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

3

1. Ontology


Definition : Formal, explicit specification of a a shared
conceptualization



Ontology can be used and shared by agents



Ontology languages


To be understood by humans intuitively


Capturing of meaning (semantics) of data


Inference mechanism with completeness, preciseness and
efficiency


Interoperability and compatibility


Combined with web languages s.a. XML and RDF

Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

4

1. Ontology


Crucial role in enabling web
-
based knowledge
processing, sharing and reuse


Human
-
beings and machines communicate each other


common understanding of topics between people and
applications


Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

5

1. Ontology


Conceptual structures for machine processible data on
the web


Formal tools to structure semantic data


Formal conceptualizations of particular domains



Metadata schema with controlled vocabulary of
concepts


Semantic metadata for web pages


RDF & RDFS as metadata formats


Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

6

2. XML (eXtensible Markup Language)


Standard markup language to represent the user
-
defined markup language


meta markup language


Markup language to define another markup language


Simple, but flexible text
-
format defined from SGML


Large
-
scale electronic publishing to meet the role in
the exchange of wide variety of data on the web and
elsewhere


Hierarchical structure with tag (DTD)


DTD

Document Structure

(Markup Language)

XML

Document Contents

(instance)

Style sheet

Style language

Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

7

2. XML (eXtensible Markup Language)


XML related standards


DTD (Document Type Definition)


Defines the logic structure of XML documents


Defines contents & attributes of each component


Defines objects


XSL (eXtensible Style Sheet)


Defines the style to each component of XML documents


Documents transformation


CSS (Cascading Style Sheet)


Some functionality as XSL


Limitation in the style definition


Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

8

2. XML (eXtensible Markup Language)


Advantages


Data representation



structured & independent


Data sharing and interoperability


Hierarchical, composite data



Disadvantages


Lack of representation of relationship between objects


Lack of representation of data meaning


Lack of inheritance of meaning

Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

9

3. RDF
(Resource Description Framework)


Markup language based on XML syntax


Developed to representation the multiple, various
resources dispersed in the distributed web environment


Used as a basis for the other markup language


Data representation : triple representation as follow


<object, property, value>

Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

10

3. RDF
(Resource Description Framework)


Advantages


Representation of data with the meaning


Environment in which computer can understand and process
the data


Flexible capability to representation the meta data


Mean of information exchange in heterogeneous distributed
environment


Description of constants by the semantic network


Disadvantages


Lack of affection inference mechanism


Weak in the representation of semantic of data

Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

11

3. RDF
(Resource Description Framework)



<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22
-
rdf
-
syntax
-
ns#"
xmlns:s="http://iis.korea.ac.kr/schema/">


<rdf:Description about="http://iis.korea.ac.kr/Home/Sohn">


<s:Creator>



<rdf:Description about="http://iis.korea.ac.kr/stdId/2005020626">



<rdf:type resource="http://iis.korea.ac.kr/schema/Person"/>



<v:Name>Sohn JongSoo</v:Name>



<v:Email>mis026@korea.ac.kr</v:Email>



</rdf:Description>


</s:Creator>


</rdf:Description>

</rdf:RDF>



Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

12

4. OIL (Ontology Inference Layer)


Satisfies the requirement of semantic web


Hierarchical layer structure for extension



Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

13

4. OIL (Ontology Inference Layer)


Based on Frame
-
based System, Description Logic and
Web Languages


OIL

Frame
-
based system:

Epistemological Modeling

Primitives

Description Logics:

Formal Semantics&

Reasoning Support

Web language:

XML and RDF
-
based syntax

Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

14

4. OIL (Ontology Inference Layer)


Advantages


Hierarchical extensions


Effective inference mechanism based on the Description Logic


Well
-
defined semantics



Disadvantages


Impossible to define the default
-
value


Impossible to provide the meta
-
class


Impossible to support the concrete domain


Limitation in the OIL extension and ontology transformation

Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

15

5. DAML (DARPA Agent Markup Language)


Based on XML and RDF



Combines the advantage of various, multiple semantic
web languages


Combination of DAML + OIL


DAML
-
S


Automatic Web Service retrieval and execution


DAML
-
L


Logic representation

Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

16

5. DAML (DARPA Agent Markup Language)


Advantages


Powerful in the representation of meaning and constraints


Support for the XML
-
Schema data type


Support well
-
defined semantics


Support default value



Disadvantages


Can’t exclude the RDF and XML


Can’t be formal language


Less extensible compared with OIL

Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

17

5. DAML (DARPA Agent Markup Language)

<?xml version=”1.0”?>

<rdf:RDF xmlns:rdf=”http://www.w3.org/1999/02/22/
-
rdf
-
syntzs
-
ns#”


xmlns:rdfs=”http://www.w3.org/TR/1999/PR
-
rdf
-
schema
-
19990303#”


xmlns:daml=”http://www.daml.org/2001/03/daml+oil#”


xmlns = “http://www.daml.org/2001/03/daml+oil#”>



<daml:Ontology rdf:about=””>

<daml:versionInfo>1.0</daml:versionInfo>

<daml:import rdf:resource=”http://schema.org/base# “/>

</daml:Ontology>



<daml:Class rdf:ID=”boy
-
friend”>

<rdfs:subClassof rdf:resource=”#Male” />

<rdfs:subClassOf>


<daml:onProperty rdf:resource=”@has” />


<daml:hasClass redf:resource=”#girl
-
friend” />

</rdfs:subClassOf>

</daml:Class>




<daml:Class rdf:ID=”Animal”>


<rdfs:label>Animal</rdfs:label>

</daml:Class>



<daml:Class rdf:ID=”girl
-
friend”>


<rdfs:subClassOf rdf:resource=”#Female”/>

</daml:Class>



<daml:Class rdf:ID=”Male”>


<rdfs:subClassOf rdf:resource=”#Animal”/>


<daml:disjointWith rdf:resource=”#Female”/>

</daml:Class>



<daml:Class rdf:ID=”Female”>


<rdfs:subClassOf rdf:resource=”#Animal”/>


<daml:disjointWith rdf:resource=”#Male”/>

</daml:Class>



</rdf:RDF>


Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

18

6. OWL (Web Ontology Language)


Three species of OWL


OWL full is union of OWL syntax and RDF


OWL DL restricted to FOL fragment (
¼

DAML+OIL)


OWL Lite is

easier to implement


subset of OWL DL


Semantic layering


DL semantics officially definitive


OWL DL based on
SHIQ

Description Logic


In fact it is equivalent to
SHOIN
(D
n
)

DL


OWL DL Benefits from many years of DL research


Well defined semantics


Formal properties well understood (complexity, decidability)


Known reasoning algorithms


Implemented systems (highly optimised)

Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

19

6. OWL (Web Ontology Language)


Relationships between classes


equivalentClass


subClassOf


Intersection, union, complement, disjunction



Relationships between instances


sameAs, differentFrom



Properties of properties


Domain, Range


Cardinality


Transitive, Symmetric


allValuesFrom, someValuesFrom


Functional, InverseFunctional



Relationships between properties


subPropertyOf


inverseOf

Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

20

6. OWL (Web Ontology Language)

RDFS syntax


<owl:Class>


<owl:intersectionOf rdf:parseType=" collection">


<owl:Class rdf:about="#Person"/>


<owl:Restriction>


<owl:onProperty rdf:resource="#hasChild"/>


<owl:toClass>


<owl:unionOf rdf:parseType=" collection">


<owl:Class rdf:about="#Doctor"/>


<owl:Restriction>


<owl:onProperty rdf:resource="#hasChild"/>


<owl:hasClass rdf:resource="#Doctor"/>


</owl:Restriction>


</owl:unionOf>


</owl:toClass>


</owl:Restriction>


</owl:intersectionOf>

</owl:Class>

Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

21

7. Conclusion


온톨로지를

표현하는

언어


많은

온톨로지

언어



중요하게

연구된

것을

위주로

조사


소개된



외에도

Ontolingua, SHOE, TopicMap
등이

있음


W3C


표준화

추세


W3C
에서

표준으로

제정한

OWL


가장

유력해

보임


OWL


대한

연구가

가장

활발


OWL


확장하여

표현력을

높이는

노력이

보임


My impression


비교적

예전의

언어를

이용하여

example


만들기가

쉽지


았음


시맨틱





지능형



서비스의

과거



현재를

돌아봄으로


발전

방향에

대하여

다시한번

생각할



있는

계기

마련


Dept. Computer Science, Korea Univ.

Intelligent Information System Lab.

22






Thank you