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Semantic Web:Semantic Web:State of the Art and OpportunitiesState of the Art and Opportunities
Vagan TerziyanCompiled, partly based on various online tutorialsand presentations, with respect to their authors
Industrial Ontologies Group
http://www.cs.jyu.fi/ai/OntoGroup/index.html
University of Jyvskyl
Industrial Ontologies GroupIndustrial Ontologies Group
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Tutorial Online
http://www.cs.jyu.fi/ai/OntoGroup/pres/SW_Tutorial_2004_Part_1.ppt
http://www.cs.jyu.fi/ai/OntoGroup/pres/SW_Tutorial_2004_Part_2.ppt
http://www.cs.jyu.fi/ai/OntoGroup/pres/SW_Tutorial_2004_Part_3.ppt
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Researchers
Vagan Terziyan
Oleksandr Kononenko
Andriy Zharko
Oleksiy Khriyenko Olena Kaykova
Industrial Ontologies Group
Industrial Ontologies Group: http://www.cs.jyu.fi/ai/OntoGroup/
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Speakers Profile
Vagan Terziyan
Profile:
Artificial Intelligence
Knowledge Management
Agent Technology Semantic Web
Machine Learning
Data Mining
1981 M s. Eng. (Applied mathematics)
1985 Dr. Tech. (Cybernetics andIT)
1993 Dr. (Habil) Tech. (IS and AI)
1996 P rofessor (Software Engineering)
2001 Docent, University of Jyvaskyla
(AI and Knowledge Management)
2002-2004 Ass. Prof., Department ofMathematical
Information Technology, Senior Researcher,
Agora Center, University of Jyvaskyla,
VisitingProf., Free University of Amsterdam
Kharkov National University ofRadioelectronics
Ukraine
University of Jyvskyl
Finland
Head of AI Department, Professor, Dr. (Habil) Tech.
Associate Professor, Senior Researcher
(Agora Centre)
http://www.cs.jyu.fi/ai/vagan/
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Industrial Ontologies Group:Industrial Ontologies Group:
Our HistoryOur History
1978-1984 We took part in development of the
first in USSR Industrial Natural Language
Processing System DESTA, which included
semantic analysis and ontologiesontologies;
1985-1989 - We took part in development of the
first in USSR Industrial Automated Natural
Language Programming System ALISA, which
Enabled Semantic AnnotationEnabled Semantic Annotation, DiscoveryDiscoveryand
IntegrationIntegration of software components (prototype of
today's Semantic Web ServicesSemantic Web Services concept);
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Industrial Ontologies Group:Industrial Ontologies Group:
Our HistoryOur History
1990-1993 under name ofMetaintelligence Lab.we were piloting concept of a MetasemanticNetwork (triplet-based (meta-)knowledge
representation model) prototype of todays RDF-based knowledge representation in Semantic WebSemantic Web;
1994-2000 various projects with industrialpartners, e.g. MetaAtom Semantic Diagnostics of
Ukrainian Nuclear Power Stations based onMetaknowledge;MetaHuman industrial medicaldiagnostics expert system based onMetaknowledge;Jeweler metamodelling andcontrol of industrial processes, etc.; got several
research grants from Finnish Academy;
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Industrial Ontologies Group:Industrial Ontologies Group:
Our HistoryOur History
2000-2001 we have created branches in VrijeUniversiteit Amsterdam (heart of Semantic Webactivities in Europe) where now working 5 our
former team members, in Jyvaskyla University(several tens of researchers) and establishedresearch groups in Kharkov (Ukraine) on DataMining, Educational Ontologies, Telemedicine, etc.
200
1-2003
we took part in MultiMeetMobileTekes Project, in InBCT Tekes Project in Tempus
EU Compact Project in (or in cooperation with)University of Jyvaskyla where we further promoteSemantic WebSemantic Web concepts.
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Industrial Ontologies Group:Industrial Ontologies Group:
Important ObjectiveImportant Objective
For us there are no doubts about the
possibilities, which Semantic Web opens for
industry.
that is why one important objective of our
activities is to study appropriate industrial cases,
collect arguments, launch industrial projects and
develop prototypes for the industrial companies
to not only believe together with us but also
benefit from the Semantic Web.
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Why andWhere SemanticWeb ?Why andWhere SemanticWeb ?
WWW
Business
Knowledge
Management
more then 3,000,000,000 web-pages
Information burst
ICT needs comprehensive resource management technology
Needs for integration of businesses
Web Services for e-Business
Standardization and Interoperability problems
Consolidate and reuse experience
Standardize knowledge sharing technology Needs for the intelligent tools to use humans knowledge
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4
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 suitablefor software agents
World Wide Web
Semantic Web
The SemanticWeb 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 andreuse of data across various
applications.
7
Before Semantic Web
Web content
UsersCreatorsWWW
and
Beyond
8
Semantic Web Structure
Semantic
AnnotationsOntologies Logical Support
Languages ToolsApplications /
Services
Web content
UsersCreatorsWWW
and
Beyond
Semantic
Web
Motivation for SemanticWebMotivation for SemanticWeb
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What is the Transactional
Web
Today: The eye-ball Web- the
architecture of the Web is geared towards
delivering information visually.
Tomorrow: The transactional Web the
architecture of the Web geared towards
intelligently exchanging informationbetween applications.
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Summarizing the Problem:
Computers dont understand Meaning
My mouse is broken. I need a
new one
Use of ontology
My mouse is broken
vs. My mouse is dead
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Approach: SemanticWebApproach: SemanticWeb
The Semantic Web is a vision: the idea of having data on theWeb 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 applicationshttp://www.w3.org/sw/
The Semantic Web is an initiative with the goal of extending thecurrent Web and facilitating Web automation, universally accessibleweb resources, and the 'Web of Trust', providing a universallyaccessible platform that allows data to be shared and processed byautomated tools as well as by people.
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WordWord--Wide CorrelatedActivitiesWide CorrelatedActivities
Semantic Web
Grid Computing
Web Services
Agentcities
Global, collaborative effort
to construct an open network of on-line systems
hosting diverse agent based services.
Providing technologies for automated communication,
discovery and integration ofWeb services,
to enable on-the-fly software composition through
the use of loosely coupled, reusable software components.
FIPA
Producing standards for the interoperation
of heterogeneous software agents.
Extending current web by giving information
a given well-defined meaning, better enabling
computers and people to work in cooperation
Utilizing the global Internet to build
distributed computing and communications
infrastructures.
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HTML
100%
50%
0%
XML
DAML+OIL
2000 2005 2010
Fifty percent of the content on theWeb will be in XML format by the endof 2003 .Gartner Group
In 30 years e-commerce will have become second
nature. Lifelike, intelligent virtual assistants will beperforming most routine transactions and simplenegotiations electronically on our behalf. Moretechnological change will have taken place in thatperiod than during the entire twentieth century, andthe curve will continue to steepen exponentially intothe foreseeable future. Ray Kurzweil
Web Migration to New TechnologyWeb Migration to New Technology
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Tim Berners-Lee's Vision of
Semantic Web (IJCAI-01)
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SemanticWeb: New UsersSemanticWeb: New Users
Semantic
AnnotationsOntologies Logical Support
Languages ToolsApplications /
Services
Web content
UsersCreatorsWWW
and
Beyond
Semantic
Web
Semantic Web
content
UsersSemantic
Web and
Beyond
Creators
applications
agents
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Content
Agents Annotations
Ontologies
Software engineersOntology engineers
Web designers
Content creators
Logic, Proof
and Trust
AI Professionals
Mobile Computing
Professionals
Professions around SemanticWebProfessions around SemanticWeb
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SemanticWeb: Resource IntegrationSemanticWeb: Resource Integration
Shared
ontology
Web resources /
services / DBs / etc.
Semantic
annotation
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SemanticWeb:What toAnnotate ?SemanticWeb:What toAnnotate ?
Web resources /
services / DBs / etc.
Shared
ontology
Web users(profiles,
preferences)
Web access
devices
Web agents /applications
External world
resources
Smart
machines
and devices
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The Semantic Web
The Ontology Articulation Toolkithelps agents to understand
unknown ontologies
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Cant we just use XML?
This is what a web-page in natural language
looks like for a mach
ine
J. Hendler
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J. Hendler
XML helps
CV
name
education
work
private
< >
< >
< >
< >
< >
XML allowsmeaningful tags to be added toparts of the text
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J. Hendler
XML { machine accessible meaning
CV
name
education
work
private
< >
< >
< >
< >
< >
< ': >
< REQI >
But to your machine,
the tags look like this.
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J. Hendler
Schemas take a step in the right
direction
Schemas help.
CV
name
education
work
private
< >
< >
< >
< >
< >
< ': >
CV
name
education
work
private
< >
< >
< >
< >
< >
< ': >
< ': > by relating
common terms
between documentsTVMZEXI
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But other people use other schemas
CV
name
education
work
private
< >
< >
< >
< >
< >
< &9 >
QDPH>
!
Someone elseh
as one like th
is.
J. Hendler
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The semantics isnt there
CV
name
education
work
private
< >
< >
< >
< >
< >
< ': >
CV
name
education
work
private
< >
< >
< >
< >
< >
< ': >
< ': >
which dont fit inTVMZEXI
CV
name
education
work
private
< >
< >
< >
< >
< >
< &9 >
!
J. Hendler
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KR provides external
referents to merge on
CV
name
education
work
private
< >
< >
< >
< >
< >
< ': >
CV
name
education
work
private
< >
< >
< >
< >
< >
< ': >
CV
name
education
work
private
< >
< >
< >
< >
< >
< ': >
Semantic Web languages add
mappings and structure.
QPH
[SVO
ZEXI
IHYG ':
':':
HG
XF
CV
name
education
work
private
< >
< >
< >
< >
< >
!
CV
name
education
work
private
< >
< >
< >
< >
< >
!
CV
name
education
work
private
< >
< >
< >
< >
< >
< &9 >
!
CV
name
education
work
private
< >
< >
< >
< >
< >
< &9 >
!
CV
name
education
work
private
< >
< >
< >
< >
< >
!
J. Hendler
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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
vocabulary terms
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Mary
Director
Secretary
to_be_in_
love_with
has_job
has_job
John
has_homepage
has_homepage
OntologyOntology
RDF Semantic Web over Web Resources
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Resources
All things being described by RDF
expressions are called resources:
entire Web page;
a specific XML element; whole collection of pages;
an object that is not directly accessible via the
Web.
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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 resourcesvia a representation of their primary access mechanism (e.g., their network "location"), rather than
identifying the resource by name or by some other attribute(s) of that resource.
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Subjectof an RDF statement is aresource
Predicate of an RDF statement is aproperty of a resource
Objectof an RDF statement is the value
of a property of a resource
RDF Statement
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Example of RDF Statement
Subject (resource) http://www.w3.org/Home/Lassila
Predicate (property) Creator
Object (literal) Ora Lassila
Ora Lassila is the creator of the resource
http://www.w3.org/Home/Lassila.
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RDF Example (serialization syntax)
Ora Lassila is the creator of the resource
http://www.w3.org/Home/Lassila.
Ora Lassila
's' is a specific namespace prefix, e.g.
xmlns:s="http://description.org/schema/"
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RDF Example (abbreviated syntax)
Ora Lassila is the creator of the resource
http://www.w3.org/Home/Lassila.
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Statements about Statements (1)
An unnamed node is the source of
all five arcs. The first arc is labelled
rdf:type and points to the node
identified as rdf:Statement. The
second arc is labelled rdf:predicate
and points to the node identified as
s:Creator. The third arc is labelled
rdf:subject and points to a node
labelled
http://www.w3.org/Home/Lassila .
The fourth arc is labelled rdf:objectand points to a node containing the
string value "Ora Lassila". The fifth
and final arc is labelled
a:attributedTo and points to a node
containing the string value "Ralph
Swick".
Ralph Swick says that Ora Lassila is the creator of the
resource http://www.w3.org/Home/Lassila
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Statements about Statements (2)
Ralph Swick says that Ora Lassila is the creator of the
resource http://www.w3.org/Home/Lassila
Ora Lassila
Ralph Swick
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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)
Capability to explicitly declare semantic relationsbetween vocabulary terms
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RDF Schema
Semantic network on the Web
Nodes are identified by URIs
rdfs:Class
rdfs:Property
rdfs:subClassOf
Cl Hi h f th RDFS
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Class Hierarchy of the RDFS
Class hierarchy is shown
using a "nodes and arcs"
graph representation of
the RDF data model. If
one class is a subset ofanother, then there is an
rdfs:subClassOfarc from
the node representing the
first class to the node
representing the second.
If a resource is an instance of a class, then there is an rdf:type arc
from the resource to the node representing the class.
E l (1)
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Example (1)
Example expresses the following class hierarchy. We first define a class
MotorVehicle.We then define three subclasses ofMotorVehicle,
namely PassengerVehicle, Truckand Van.We then define a class
Minivan which is a subclass of both Van and PassengerVehicle.
E l (2)
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Example (2)
...
E l (3)
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Example (3)
...
E l (4)
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Example (4)
D bli C
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53
Dublin Core
A set of fifteen basic properties for
describing generalised Web resources
ISO Standard
15836
-2003 (February2003):
http://www.niso.org/international/SC4/n515.pdf
http://dublincore.org/
The Dublin Core Metadata Initiative is an open forum engaged in the development of interoperable
online metadata standards that support a broad range of purposes and business models .
D bli C (15 b i ti )
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54
Dublin Core (15 basic properties):
Title
Creator
Subject Description
Publisher
Contributor Date
Type
Format
Identifier
Source
Language
Relation
Coverage
Rights
D bli C E l
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Guidance on expressing the Dublin Core within the Resource
Description Framework (RDF)
Eric Miller Paul Miller
Dan Brickley
Dublin Core; Resource Description Framework; RDF; eXtensible
Markup Language; XML
Dublin Core Metadata Initiative
Dublin Core Data ModelWorking Group
1999-07-01
text/html
en
Dublin Core Example
Where to look next
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56
Where to look next
RDF:
http://www.w3.org/RDF/
RDF Schema:
http://www.w3.org/TR/rdf-schema/
O t l i l Vi i f S ti W b
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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 ofclasses within the domain, semantic
relations among terms and inference rules
Use of ontologies:
Sharing semantics of your data across
distributed applications
O l i h f d i f S i W bO l i h f d i f S i W b
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Ontologies: the foundation of SemanticWebOntologies: the foundation of SemanticWeb
Document
Location
Subject
name
is-a
uri
comment __Thing__
is-a
Report
Web-page
Access Rights
Author
http://www.ontogroup.net
is-a
\\AgServ\vagan\InBCT_1.doc
V. Terziyan
Author
O. Kononenko
Author
uriLocation
draft
comment
public
Home page
comment
3.1: analysis
Subject
Instance-of Instance-of
Query 1: get all documents from location X, but not web-pages
Query 2: get documents related to Y, with more then one author, one of which is Terziyan
Query 3: are there web-pages of Z with private access related to documents with subjectS?
Related to
Related to
Access rights
#doc1 #doc2
Ontologies are keyenabling technology for
the SemanticWeb
..explicit specification of
conceptualization..
Ontology is formal and rich
way to provide shared and
common understanding of
a domain, that can be used
by people and machines
Semantic Webname
public
private
S ti W b I t bilitS ti W b I t bilit
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SemanticWeb: InteroperabilitySemanticWeb: InteroperabilityOntology A: Documents Ontology B: Research
A commitment to a common
ontology is a guarantee of a
consistency and thus possibility
of data (and knowledge) sharing
Common
(sh
ared)ontology
Ontology C: Services
System 1System 2
\\AgServ\vagan\InBCT_1.doc
V. Terziyan
A:Report
A:Location3.1: analysis
A:Subject
A:Author
Instance-ofSemanticWeb
A:name
Query Today
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Query Today
The answer may besomewhere in this
list of URLs
WWW Hotbot
What is Al Qaeda?
Semantic Query
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What is Al Qaeda?
Membership
Locations
Structure
Finances Tactics
Other terrorist organizations
Semantic Query
A terrorist organization
Would you like additional information on?
Example Ontology
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Example Ontology
These ontologies accessed
at remote locations
RDF Based Inference
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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
What is an ontology?
Benefits
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Benefits
Building an ontology is not a goal in itself.
Communication between people
Interoperability between software agents
Reuse of domain knowledge
Make domain knowledge explicit
Analyze domain knowledge
Ontology Elements
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Ontology Elements
Concepts(classes) + their hierarchy
Concept properties (slots/attributes)
Property restrictions (type, cardinality, domain)
Relations between concepts (disjoint, equality)
Instances
How to build an ontology?
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How to build an ontology?
Steps:
determine domain and scope
enumerate important terms
define classes and class hierarchies
define slots
define slot restrictions (cardinality, value-type)
Step 1: Determine Domain and Scope
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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?How many borders are crossed?
Step 2: Enumerate Important Terms
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Step 2: Enumerate Important Terms
country
city capital
border
connection
Connection_on_land
Connection_in_air
Connection_on_water
road
railway
currency
Step 3: Define Classes and Class Hierarchy
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Step 3: Define Classes and Class Hierarchy
Step 4: Define Slots of Classes
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Step 4: Define Slots of Classes
Step 5: Define slot constraints
Slot-cardinalityEx: Borders_with multiple, Start_pointsingle
Slot-value typeEx: Borders_with- Country
Geographic_entity
Country CityHas_capital
Capital_ofBorders_with
ConnectionStart_point
End_point
Capital_city
OWL became standard
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OWL became standard
10 February 2004 the World Wide Web
Consortium announced final approval of two
key Semantic Web technologies, the revisedResource Description Framework (RDF) and
the Web Ontology Language (OWL).
Read more in:http://www.w3.org/2004/01/sws-pressrelease.html.en
OWL IntroductionOWL Introduction
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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 IntroductionOWL Introduction
Example
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Example
There are two types of animals, Male and Female.
The subClassOfelement asserts that its subject
-Male
-is asubclass of its object -- the resource identified by #Animal.
Some animals are Female, too, but nothing can be both
Male and Female (in this ontology) because these two
classes are disjoint (using the disjointWith tag).
OWL Example in Protg (1)
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OWL Example in Protg (1)
Class Person superclass
Man, Woman subclasses
Properties
isWifeOf, isHusbandOf
Property characteristics, restrictions inverseOf
domain
range
Cardinality
Class expressions
disjointWith
OWL Example in Protg (2)
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OWL Example in Protg (2)
OWL Example in Protg (3)
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OWL Example in Protg (3)
Web of Trust
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Web ofTrust
Claims can be verified if there is supporting evidence
from another (trusted) source
We only believe that someone is a professor at a
university if the university also claims that personis a professor, and the university is on a list I trust.
believe(c1) :- claims(x, c1) predicate(c1, professorAt) arg1(c1, x) ^ arg2(c1, y) ^ claims(c2, y) ^
predicate(c2, professorAt) ^ arg1(c2, x) ^arg2(c2, y) ^ AccreditedUniversity(y)AcknowledgedUniversity(u) :- link-from( http://www.cs.umd.edu/university-list ,u)
Notice this one
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Six Challenges for the Semantic Web
Richard Benjamins, Jesus Contreras,
Oscar Corcho, Asuncion Gomez-Perez
April 2002
Challenge 1:Availability of ContentChallenge 1:Availability of Content
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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 includemultimedia, and web services.
Challenge 1:Availability of ContentChallenge 1:Availability of Content
Challenge 2: OntologyAvailability,Challenge 2: OntologyAvailability,
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Constructing ofkernel ontologies to be used by all
the domains.
Managing evolution of ontologies and their relation
to already annotated data.
g gy y,g gy y,
Development and EvolutionDevelopment and Evolution
Challenge 3: Scalability of SemanticChallenge 3: Scalability of Semantic
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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 itand how to find the right content.
g yg y
Web ContentWeb Content
Challenge 4: MultilingualityChallenge 4: Multilinguality
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Multilinguality plays an increasing role at the level of
ontologies, of annotations and of user interface.
g g yg g y
Challenge 5: VisualizationChallenge 5: Visualization
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With the increasing amount of information overload,
intuitive visualization of content will become more
and more important.
gg
Challenge 6: SemanticWebChallenge 6: SemanticWeb
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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 thecommunity.
Language StandardizationLanguage Standardization
Summary
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y
The semantic web is based on machine-
processable semantics of data.
Its backbone technology are Ontologies. It is based on new web languages such as
XML, RDF, and OWL, and tools that make
use of these languages.
SemanticWeb Activities in Finland
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The first Semantic Web Kick-Off Meeting in Finland was in
Helsinki 2 November 2001;
Later Finnish portal on Semantic web activities was
launched in
http://www.cs.helsinki.fi/u/eahyvone/stes/semanticweb.
Semantic Computing (SeCo) research group was formally
established in the spring 2002. The group belongs to the
University of Helsinki, Department of Computer Science and
Helsinki Institute for Information Technology (HIIT). Group
leader is Prof. Eero Hyvonen
The first projects focus on Semantic Web and Web Service
applications and representation of cultural content on the
Web.
SemanticWeb Activities in Finland
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The conference Towards the Semantic Web and Web
Services was organized in October 21-22, 2002 in Helsinki
by the XML Finland Association and others, and was
supported by several patrons, such as OntoWeb. The goal of
the event was to stimulate interest in the synergy between
the Semantic Web and Web Services.
Established in 2002 the W3C Office in Finland is situated at
the Tampere University ofTechnology, Digital Media Institute
(The manager of the Finnish Office is Ossi Nyknen).
Main Finnish industrial players are involved: Nokia,
TeliaSonera, TietoEnator, Metso,
Company Benefits from the SemanticWebCompany Benefits from the SemanticWeb
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Developing ontology languages, ontologies, annotationsupport tools will give you an advance of several yearsbefore others can develop the same. Important is that thestandards and the applications will depend on you.
Developing Semantic Web service platforms, agents,applications, based on widespread standards allows toautomatically explore rich Web content providing services formillions of customers.
Annotate your own products and services. This makesyour products and services reachable by new generation ofsemantic search engines and automatically accessed by Web
applications, agents and services.
p yp y
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ConclusionConclusion
Semantic Web is not only a technologytechnology as manyused to name it;
Semantic Web is not only an environmentenvironment asmany naming it now;
Semantic WebSemantic Web it is a newcontextcontextwithin whichone should rethink and re-interpret his existingbusinesses, resources, services, technologies,
processes, environments, products etc. to raisethem to totally new level of performance
------------------------------------------
Contact: Vagan Terziyan [email protected]
http://www.cs.jyu.fi/ai/vagan (tel. +35814 2604618)
Lecture Notes and Textbook
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Dave McComb, Semantics in BusinessSystems, Morgan Kaufmann, 2004.
Main recommended textbook
Lecture Notes (available online)
Follow link:
http://www.cs.jyu.fi/ai/vagan/courses
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Where to find out more: Web-Sites
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OWL, OWL-S http://www.w3.org/2004/01/sws-pressrelease
http://www.w3.org/2004/01/sws-testimonial
Semantic Web
http://www.w3.org/2001/sw/ http://www.semwebcentral.org/
Semantic Web Services http://www.daml.org/services/
http://www.swsi.org/
http://www.wsmo.org
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Ask not what the Semantic
Web Can do for you, ask what
you can do for the Semantic
Web
Hans-Georg Stork, European Union
http://lsdis.cs.uga.edu/SemNSF
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