Semantic_Web3.ppt

(1)

Semantic Web:

State of the Art and Opportunities

(2)

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Web Limitations

Doubles in size every six months Average WWW searches examine

only about 25% of potentially relevant sites and return a lot of

unwanted information

Information on web is not suitable for software agents

World Wide Web

Semantic Web

The Semantic Web is a vision: the idea of having data on the Web defined and linked in a way that it can be used by machines not just for display purposes, but for automation, integration and reuse of data across various applications.

7

B e f o r e S e m a n t i c W e b

W e b c o n t e n t

U s e r s C r e a t o r s

W W W a n d B e y o n d

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S em an tic W eb S tru ctu re

S em an tic

A nn o tatio ns O nto log ies L o g ical S u pp o rt

L an gu ag es T oo ls A p p lication s /_{S ervices}

W e b co n te nt

U se rs C reators

W W W a n d B ey o n d

S em a n tic W e b

Motivation for Semantic Web

(3)

Limitations of the Web today

(4)

Summarizing the Problem:

Computers don’t understand Meaning

•

“My mouse is broken. I need a

new one…”

Use of ontology

“My mouse is

broken

”

(5)

(6)

(7)

(8)

(9)

(10)

Approach: Semantic Web

“The Semantic Web is a vision: the idea of having data on the

Web defined and linked in a way that it can be used by

machines not just for display purposes,

but for automation, integration and reuse

of data across various applications”

http://www.w3.org/sw/

(11)

(12)

Semantic Web Stack

(13)

Semantic Web: New “Users”

Semantic

Annotations Ontologies Logical Support

Languages Tools Applications / Services

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Semantic Web: Annotations

Semantic

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Semantic annotations are specific sort of metadata, which provides information about particular domain objects, values of their

(15)

Semantic Web: Ontologies

Semantic

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Ontologies make metadata interoperable and ready for efficient sharing and reuse. It provides shared and common understanding of a domain, that can be used both by people and machines. Ontologies are used as a form of agreement-based

(16)

Semantic Web: Rules

Semantic

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Logical support in form of rules is needed to

(17)

Semantic Web: Languages

Semantic

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Languages are needed for machine-processable formal descriptions of: metadata (annotations) like e.g. RDF; ontologies like e.g. OWL.; rules like e.g. RuleML. The challenge is to provide a framework for specifying the syntax (e.g. XML) and semantics of all of these languages in a uniform and coherent way. The strategy is to translate the various

(18)

Semantic Web: Tools

Semantic

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(19)

Semantic Web: Applications and Services

Semantic

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(20)

The Semantic Web

(21)

Semantic Web basics…



RDF:

•

is a W3C standard, which provides tool to describe Web

resources

•

provides interoperability between applications that

exchange machine-understandable information



RDF Schema:

–

is a W3C standard which defines vocabulary for RDF

–

organizes this vocabulary in a typed hierarchy

–

capable to explicitly declare semantic relations between

(22)

Where we are Today:

the Syntactic Web

(23)

Most of the Current Web (dumb links)

(24)

Semantic Web

(data connected by relationships)

(25)

Mary

Director

Secretary

to_be_in_

love_with

has_job

John

has_homepage

Ontology

(26)

Resources

• All things being described by RDF

expressions are called

resources

:

– entire Web page;

– a specific XML element;

– whole collection of pages;

(27)

44

Different Ways to Represent

properties

RED

Tomato

has_color

Tomato

has_red_color

Tomato

instance_of

Red Thing

C

in RDF

(28)

45

RDF Statement

Resource_i

Property_k

Value_n

Resource_i

Property_r

Resource_ j

(29)

46

Semantic Relation as RDF statement

(so called “object property”)

Ai Aj

Lk

Relation (i  j)

http://www.cs.jyu.fi/ai/vagan/index.html

Personal web page of Terziyan V.

http://www.jyu.fi/agora-center/indexEng.html

Web page of Agora Center

refers_to

Resource Relation Resource

Subject Predicate object

http://www.cs.jyu.fi/ai/vagan/#vagan

URI of Terziyan V.

employed_by

Dereferenceable URI (“Hash vs. Slash”)

URI of Agora Center

http://www.jyu.fi/agora-center/#AC

(30)

47

Semantic Property as RDF statement

(so called “datatype property”)

Literal

has_birthday

Resource Property

Subject Predicate object Literal

Ai

Lk

Property (i = j)

15.02.2000

URI of Terziyan V.

has_birthday

27.12.1958

Dereferenceable URI (“Hash vs. Slash”)

“Birthday” of the web-page

(31)

48

Semantic Network of Web Resources

http://www.jyu.fi/agora-center/indexEng.html

Web page of Agora Center

refers_to

URI of Terziyan V.

employed_by

URI of Agora Center

http://www.jyu.fi/agora-center/#AC

hasWebPage

isWebPageOf

hasWebPage

isWebPageOf

27.12.1958

(32)

Resources and URIs

• A resource can be anything that has identity

•

Uniform Resource Identifiers

(URI)* provide

a simple and extensible means for identifying

a resource

• Not all resources are network "retrievable";

e.g., human beings, corporations, and books

in a library can also be considered resources

*

The term "Uniform Resource Locator" (URL) refers to the subset of URI that identify

(33)

•

Subject

of an RDF statement is a

resource

•

Predicate

of an RDF statement is a

property of a resource

•

Object

of an RDF statement is the value

of a property of a resource

(34)

Example of RDF Statement

Subject (resource)

http://www.w3.org/Home/Lassila

Predicate (property)

Creator

Object (literal)

“Ora Lassila”

(35)

RDF Example (subject of

statement)

Ora Lassila is the creator of the resource

http://www.w3.org/Home/Lassila.

<rdf:RDF>

<rdf:Description

about

=

"

">

<s:Creator>

Ora Lassila

</s:Creator>

</rdf:Description>

</rdf:RDF>

(36)

RDF Example (predicate of

statement)

<rdf:RDF>

<rdf:Description

about

=

"

">

<s:Creator>

Ora Lassila

</s:Creator>

</rdf:Description>

</rdf:RDF>

(37)

RDF Example (object of

statement)

<rdf:RDF>

<rdf:Description

about

=

"

">

<s:Creator>

Ora Lassila

</s:Creator>

</rdf:Description>

(38)

RDF Example (reference to

ontology)

<rdf:RDF>

<rdf:Description

about

=

"

">

<s:Creator>

Ora Lassila

</s:Creator>

</rdf:Description>

</rdf:RDF>

a specific namespace prefix as reference to

ontology where predicates are defined, e.g.

(39)

Full XML Document for the Example

<?xml

version

="

1.0

"?>

<rdf:RDF

xmlns:

rdf

="

http://www.w3.org/1999/02/22-rdf-syntax-ns#

”

xmlns:

s=

"

http://description.org/

schema/

">

<rdf:Description

about

=

"

">

<s:Creator>

Ora Lassila

</s:Creator>

</rdf:Description>

</rdf:RDF>

(40)

What is RDFS ?

• RDF Schema

– Defines vocabulary for RDF

– Organizes this vocabulary in a typed hierarchy

(

Class, subClassOf, type, Property, subPropertyOf

)

• Rich, web-based publication format for declaring

semantics (XML for exchange)

(41)

RDF Schema

• Semantic network on the Web

• Nodes are identified by URIs

• rdfs:

Class

• rdfs:

Property

(42)

Traditional RDF Statement

Resource_i

Property_k

Literal

Resource_i

Property_r

Resource_ j

OR

•

Subject

of an RDF statement is a resource

•

Predicate

of an RDF statement is a property of a

resource

(43)

HUMAN

#Vagan

Vagan Terziyan 27/12/58 _#JyU

#John

#Aino

…

C

Properties (predicate)

R

es

ou

rc

es

(

su

bj

ec

t)

ha sB irt hd ay is E m pl oy ed B y ha sN am e ha sS u rn am e

:#JyU :hasTitle “University of Jyvaskyla”

:#JyU :hasLocation “Finland”

:#JyU :hasWorldRank “204”

:#JyU :hasRector :#Aino

:#JyU a UNIVERSITY

UNIVERSITY

#MIT

#JyU

University of

Jyvaskyla Finland 204 #Aino

#KNURE

…

C

ha sW o rld R an k ha sR ec to r ha sT itl e h as Lo ca tio n

:#Vagan :hasName “Vagan”

:#Vagan :hasSurname “Terziyan”

:#Vagan :hasBirthday “27/12/58”

:#Vagan :isEmployedBy :#JyU

:#Vagan a HUMAN

:#Aino a HUMAN

Each cell is an

RDF triple

Each cell is an

RDF triple

RDF triples

RDF triples (continue)

… … …

!

RDF Illustrated

(44)

67

Dublin Core

• A set of fifteen basic properties for

describing generalised Web resources

• ISO Standard 15836-2003 (February

2003):

http://www.niso.org/international/SC4/n515.pdf

http://dublincore.org/

(45)

68

Dublin Core

(15 basic properties):

• Title

• Creator

• Subject

• Description

• Publisher

• Contributor

• Date

• Type

• Format

• Identifier

• Source

(46)

<?

xml

version

="

1.0

"?>

<

rdf:RDF

xmlns:rdf

=“

http://www.w3.org/1999/02/22-rdf-syntax-ns#

”

xmlns:dc

="

http://purl.org/dc/elements/1.0/

">

<

rdf:Description

rdf:about

="

http://www.ukoln.ac.uk/metadata/resources/dc/datamodel/WD-dc-rdf/

">

<

dc:title

> Guidance on expressing the Dublin Core within the RDF </

dc:title

>

<

dc:creator

> Eric Miller </

dc:creator

>

<

dc:creator

> Paul Miller </

dc:creator

>

<

dc:creator

> Dan Brickley </

dc:creator

>

<

dc:subject

> Dublin Core; RDF; XML </

dc:subject

>

<

dc:publisher

> Dublin Core Metadata Initiative </

dc:publisher

>

<

dc:contributor

> Dublin Core Data Model Working Group </

dc:contributor

>

<

dc:date

> 1999-07-01 </

dc:date

>

<

dc:format

> text/html </

dc:format

>

<

dc:language

> en </

dc:language

>

</

rdf:Description

>

</

rdf:RDF

>

(47)

Ontological Vision of Semantic

Web

Semantic Web needs ontologies

An ontology is



document or file that formally and in a

standardized way defines the hierarchy of

classes within the domain, semantic

relations among terms and inference rules

Use of ontologies:

(48)

(49)

Studer(98):

Formal, explicit specification of a shared conceptualization

Machine

readable

Concepts, properties,

functions, axioms

are explicitly defined

Consensual

knowledge

Abstract model of

some phenomena

in the world

(50)

79

What is an Ontology?

(51)

80

A model of (some aspect of) the world

(52)

81

•

Introduces

vocabulary

relevant to domain, e.g.:

– Anatomy

(53)

82

•

Introduces

vocabulary

– Anatomy

– Cellular biology

(54)

83

What is an Ontology?

•

Introduces

vocabulary

– Anatomy

– Aerospace

(55)

84

•

Introduces

vocabulary

– Anatomy

– Aerospace

– Dogs

(56)

85

•

Introduces

vocabulary

– Anatomy

– Aerospace

– Dogs

– Hotdogs

– …

(57)

86

•

Introduces

vocabulary

relevant to domain

•

Specifies

meaning

of terms

Heart

is a

muscular organ

that

is part of

the

circulatory system

(58)

87

•

Introduces

vocabulary

relevant to domain

•

Specifies

meaning

of

terms

Heart

is a

muscular organ

that

is part of

the

circulatory system

•

Formalised

using suitable logic

(59)

88

DL Semantics

Semantics given by standard FO model theory:

John

Mary

Lawyer

Doctor

Vehicle

hasChild

owns

(Lawyer

and

Doctor)

(60)

Ontology Elements

•Concepts(classes) + their hierarchy

•Concept properties (slots/attributes)

•Property restrictions (type, cardinality, domain)

•Relations between concepts (disjoint, equality)

(61)

How to build an ontology?

Steps:

•determine domain and scope

•enumerate important terms

•define classes and class hierarchies

•define slots

(62)

Step 1: Determine Domain and Scope

Domain: geography

Application: route planning agent

Possible questions:

Distance between two cities?

What sort of connections exist between two cities?

In which country is a city?

(63)

Step 2: Enumerate Important Terms

country

city

capital

border

connection

Connection_on_land

Connection_in_air

Connection_on_water

road

railway

(64)

(65)

Step 4: Define Slots of Classes

Step 5: Define slot constraints

•Slot-cardinality

Ex: Borders_with

multiple

, Start_point

single

•Slot-value type

Ex: Borders_with-

Country

Geographic_entity

Country

_{Has_capital}

City

Capital_of Borders_with

Connection

Start_point End_point

(66)

OWL became standard

• 10 February 2004 the World Wide Web

Consortium announced final approval of two

key Semantic Web technologies, the revised

Resource Description Framework (RDF) and

the

Web Ontology Language

(OWL).

• Read more in:

(67)

• What is OWL?

– OWL is a language for defining Web

Ontologies and their associated Knowledge

Bases

– The OWL language is a revision of the

DAML+OIL web ontology language

incorporating learning from the design and

application use of DAML+OIL.

OWL Introduction

(68)

Example

• There are two types of animals,

Male

and

Female

.

<

rdfs:Class

rdf:ID="

Male

">

<

rdfs:subClassOf

rdf:resource="

#Animal

"/>

</

rdfs:Class

>

• The

subClassOf

element asserts that its subject -

Male

- is a

subclass of its object -- the resource identified by

#Animal

.

<

rdfs:Class

rdf:ID="

Female

">

<

rdfs:subClassOf

rdf:resource="

#Animal

"/>

<

owl:disjointWith

rdf:resource="

#Male

"/>

</

rdfs:Class

>

• Some animals are

Female

, too, but nothing can be both

(69)

OWL Example in Protégé (1)

• Class

– Person superclass

– Man, Woman subclasses

• Properties

– isWifeOf, isHusbandOf

• Property characteristics, restrictions

– inverseOf

– domain

– range

– Cardinality

• Class expressions

(70)

(71)

(72)

• Symmetric: if P(x, y) then P(y, x)

• Transitive: if P(x,y) and P(y,z) then P(x, z) • Functional: if P(x,y) and P(x,z) then y=z • InverseOf: if P1(x,y) then P2(y,x)

• InverseFunctional: if P(y,x) and P(z,x) then y=z • allValuesFrom: P(x,y) and y=allValuesFrom(C)

• someValuesFrom: P(x,y) and y=someValuesFrom(C) • hasValue: P(x,y) and y=hasValue(v)

• cardinality: cardinality(P) = N

• minCardinality: minCardinality(P) = N • maxCardinality: maxCardinality(P) = N • equivalentProperty: P1 = P2

• intersectionOf: C = intersectionOf(C1, C2, …) • unionOf: C = unionOf(C1, C2, …)

• complementOf: C = complementOf(C1) • oneOf: C = one of(v1, v2, …)

• equivalentClass: C1 = C2 • disjointWith: C1 != C2 • sameIndividualAs: I1 = I2 • differentFrom: I1 != I2

• AllDifferent: I1 != I2, I1 != I3, I2 != I3, … • Thing: I1, I2, …

OWL on one Slide

Legend:

Properties are indicated by: P, P1, P2, etc Specific classes are indicated by: x, y, z Generic classes are indicated by: C, C1, C2 Values are indicated by: v, v1, v2

Instance documents are indicated by: I1, I2, I3, etc. A number is indicated by: N

(73)

An Example

• Woman ≡ Person

⊓

Female

• Man ≡ Person

⊓



Woman

• Mother ≡ Woman

⊓



hasChild.Person

• Father ≡ Man

⊓



hasChild.Person

• Parent ≡ Father

⊔

Mother

• Grandmother ≡ Mother

⊓



hasChild.Parent

We can further infer (though not explicitly stated):



Grandmother Person

⊑

Grandmother Man

⊑

⊔

Woman

(74)

OWL-2 adds new functionality with respect to OWL.:

• keys;

• disjoint union of classes

• property chains;

• richer datatypes, data ranges;

• qualified cardinality restrictions;

• asymmetric, reflexive, and disjoint properties;

• enhanced annotation capabilities .

(75)

• W3C Documents

– Guide: http://www.w3.org/TR/owl-guide/

– Reference: http://www.w3.org/TR/owl-ref/

– Semantics and Abstract Syntax:

http://www.w3.org/TR/owl-semantics/

• OWL Tutorials

– Ian Horrocks, Sean Bechhofer:

http://www.cs.man.ac.uk/~horrocks/Slides/Innsbruck-tutorial/

– Roger L. Costello, David B. Jacobs:

http://www.xfront.com/owl/

• Example Ontologies, e.g. here:

http://www.daml.org/ontologies/

(76)

Tutorial: Designing Ontologies with

Protégé

http://www.cs.man.ac.uk/~horrocks/Teaching/cs646/

http://www.co-ode.org/resources/tutorials/ProtegeOWLTutorial.pdf

• Protégé is an ontology editor and a

knowledge-base editor (download

from:

http://protege.stanford.edu

).

• Protégé is also an open-source,

Java tool that provides an

extensible architecture for the

creation of customized

knowledge-based applications.

• Protégé's OWL Plug-in now

provides

support

for

editing

Semantic Web ontologies.

PLEASE !!!

Download

version:

Protégé 3.4.8.

http://www.cs.jyu.fi/ai/vagan/Ontologies.ppt

7

8

(77)

Six Challenges for the Semantic Web

Richard Benjamins, Jesus Contreras,

Oscar Corcho, Asuncion Gomez-Perez

(78)

• Currently, there is little Semantic Web content

available. There is a need need to create a set of

annotation services (middleware) concerning static

and dynamic web documents, which may include

multimedia, and web services

.

Challenge 1: Availability of Content

(79)

• Constructing of

kernel

ontologies to be used by all

the domains.

• Managing evolution of ontologies and their relation

to already annotated data.

Challenge 2: Ontology Availability,

Development and Evolution

(80)

• Once we have the Semantic Web content, we need to

worry about how to manage it in a scalable manner, that

is, how to organize it, where to store it and how to find

the right content.

Challenge 3: Scalability of Semantic

Web Content

(81)

• Multilinguality plays an increasing role at the level of

ontologies, of annotations and of user interface.

Challenge 4: Multilinguality

(82)

• With the increasing amount of information overload,

intuitive visualization of content will become more and

more important.

Challenge 5: Visualization

(83)

• WWW

consortium

is

producing

recommendations on the languages and

technology that will be used in Semantic Web

area.

• In order to advance the state of the art in the

Semantic Web, it is important that such

standards appear fast and will be adopted by the

community.

Challenge 6: Semantic Web

Language Standardization

(84)

Summary

• The semantic web is based on

machine-processable

semantics of data.

• Its backbone technology are

Ontologies

.

(85)

Conclusion

• Semantic Web is not only a technology

technology

as many

used to name it;

• Semantic Web is not only an environment

environment

as

many naming it now;

http://www.cs.jyu.fi/ai/vagan/Ontologies.ppt