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13.12.2005

13.12.2005

1

Intelligent Systems


Lecture 24

Ontologies. Semantic WEB

(based on presentation of
Forschungszentrum Informatik at the
University of Karlsruhe, Germany)



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2

Definitions


An ontology is a specification of a
conceptualization


An ontology is a description (like a formal
specification of a program) of the concepts and
relationships that can exist for an agent or a
community of agents.


Purpose of enabling knowledge sharing and
reuse. In that context, an ontology is a
specification used for making ontological
commitments.

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Definitions (2)


The subject of
ontology

is the study of the
categories

of
things that exist or may exist in some domain.


The product of such a study, called
an ontology
, is a
catalog of the types of things that are assumed to exist in
a domain of interest
D

from the perspective of a person
who uses a language
L

for the purpose of talking about
D
.


The types in the ontology represent the
predicates
,
word
senses
, or
concept and relation types

of the language
L

when used to discuss topics in the domain
D
. An
uninterpreted logic, such as predicate calculus, conceptual
graphs, or KIF, is
ontologically neutral
. It imposes no
constraints on the subject matter or the way the subject
may be characterized. By itself, logic says nothing about
anything, but the combination of logic with an ontology
provides a language that can express relationships about
the entities in the domain of interest.

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Definitions (2)


An informal ontology may be specified by a catalog of
types that are either undefined or defined only by
statements in a natural language. A formal ontology is
specified by a collection of names for concept and
relation types organized in a partial ordering by the type
-
subtype relation. Formal ontologies are further
distinguished by the way the subtypes are distinguished
from their supertypes: an
axiomatized ontology

distinguishes subtypes by axioms and definitions stated
in a formal language, such as logic or some computer
-
oriented notation that can be translated to logic; a
prototype
-
based ontology

distinguishes subtypes by a
comparison with a typical member or
prototype

for each
subtype. Large ontologies often use a mixture of
definitional methods: formal axioms and definitions are
used for the terms in mathematics, physics, and
engineering; and prototypes are used for plants, animals,
and common household items

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Agenda

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Introduction & Motivation


Introduction
-

Semantic Web


Semantic Web Applications


Semantic Web Technology


Next Steps

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Knowledge

Management

Ontologies and

Metadata

Machine

Learning

Web
Technologies
and

Standards

E
-
Learning

Data, Text

Web Mining

Information

Extraction

Web Portals

Search engines

Metadata
-
driven

Applications

Basic

Technologies

Application

Fields

Application fields and technologies

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Motivation


WWW is a
success,

measured in


the number of users


the number of available documents


Goal
-
driven
access

to information is problematic, because
Web content has to be interpreted, combined and processed
by
humans
.


We are currently on the way to a next generation Web, building
on the existing WWW
-

the
Semantic Web
which will make
contents also for
machines
accessible and interpretable !


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Arpanet

Internet/WWW

Semantic Web

1965

1985

2000

1975

1995

Packets

Objects

Concepts

2005

...

On the Way to a Global Information Structure

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Agenda

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Introduction & Motivation


Introduction
-

Semantic Web


Semantic Web Applications


Semantic Web Technology


Next Steps

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“Information
Management:
A Proposal“,

Tim Berners
-
Lee, CERN,
1989



The Origin of the WWW

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Semantic Web


Bringing the Web to its Full Potential

HTML mit Hyperlinks

Relational

Metadata

URI
-
SHA

URI
-
STEFAND

URI
-
DAMLPROJ

WORKS
-
IN

COOPERATES
-

WITH

WORKS
-
IN

„ Darpa Agent


Markup Language“

PROJECT

RESEARCHER

PERSON

subClassOf

range

domain

Ontology

TOP

COOPERATES

WITH

WORKS
-
IN

NAME

domain

domain

range

NAME

subClassOf

subClassOf

SYMMETRIC

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Ontologies


In its classical sense ontology is a philosophical discipline.


In Computer Science: Formal
specification

of a domain of interest in
the form of a concept system


Targets
:


Shared understanding of a domain of interest


Formal description of the meaning of terms and relations


Machine executable (e.g. query for all relations of the concept
„HOTEL“)


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Metadata are
„data about data“
, e.g.


Library classification systems


The Yahoo! Categorization


Microsoft Office Document Properties



Metadata in the Semantic Web is complex structured (based on
predefined ontologies):

Relational Metadata

http://www.w3c.org/

http://www.w3c.org

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

Lassila

http://www.w3.org/

Lassila

Ora Lassila

Ora Lassila

s:Name

s.

Organization

s.

s:Person

rdf

:type

rdf

:type

s:email

lassila@w3.org

s:

worksAt

s:email

s:Name

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Agenda

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Introduction & Motivation


Introduction
-

Semantic Web


Semantic Web Applications


Skills & Human Resources


Semantic Intranet Portals


Interoperability in Tourism


Web Services


Virtual Museum


Semantic Web Technology


Next Steps

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Ontologies/Metadata in Human
Resources


Usage of
skill ontologies:


Automatic
extraction

of skills
(from applications)



Semantic
Ranking



Competency Analysis via



Data Mining



Relation to
E
-
Learning

with


skills

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2. Digitalization &

Text Generation

via OCR

3. Automatic Skill


Extraction using Shallow Parsing

3. Intranet



Employee

Marketplace

1.
Paper
-
based


Application

Ontologies/Metadata in Human
Resources

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Automatic Generation of Metadata

Via OCR from written documents

extracted

Predefined skill ontology

with metadata and lexicon

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Semantic
-
Driven Intranet Portal (I)


Requirements:


Develop
domain
-
specific terminology

for topics


Automatically generate Yahoo
-
like structure
for this
terminology


Allow to add
further, complex structured information

to the terminology


Techniques:


Ontology

Engineering


Discovering of Web Documents

via Focused Crawling


Automatic Classification

of Documents into Ontology


Cooperative
Metadata

Engineering


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Semantic
-
Driven Intranet
Portal (II)

Human Resource

Strategy:





-

Define relevant


topics in the form


of an ontology

-

Cooperatively add


further information


in the form of


metadata!




Semantic Portals


for HR strategy


-

Search relevant


Web resources




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Virtual Museum (I)


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Virtual Museum (II)


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News Services
-

Content Syndication with
RSS (I)

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NEWS

ARE FREE!

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News Services
-

RDF Site
Summary RSS (II)




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Content Services
-

OntoWeb
Community Portal


















OntoWeb Community

Annotated

Web Pages

Generated

Content Objects

Participating Site
2

{ }

Participating Site
n

{ }

Participating Site
1

{ }

...

Ontology

Browse & Query

Front End

Content

Syndication

Service

http://www.ontoweb.org

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General Web Services

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Web services


perform functions, which
can be anything from
simple requests to
complicated business
processes!


will transform the Web
from a collection of
information to a
distributed device of
computation


Web services clearly require


a semantic
-
driven description!


=> Semantic Web Enabled



Web Services

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HARMONISE


Interoperability in
Tourism



The tourism industry is
essentially an information
business where data
interoperability

is
necessary to create
dynamic markets and
cooperation.


Build bridges between
different tourism
marketplaces via Semantic
Web technologies


MAPPING
DISCOVERY!


An ontology will
mediate

between the different
underlying representations.

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Agenda

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Introduction & Motivation


Introduction
-

Semantic Web


Semantic Web Applications


Semantic Web Technology


A Layered Approach


RDF(S)


KAON Open Source Infrastructure


Next Steps

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The Semantic Web As By its
Inventor

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XML
and its relation to the
Semantic Web


„XML only provides an alphabet, not a vocabulary“.






[Forrester Report, December 2001]



The languages french and english use the same
alphabet
.


=> Can all french people communicate with english people?



Adopted to the WWW:


XML provides an alphabet and further important means for


validation and modularization!


XML does not offer any possibilities to transport conceptual
content!

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RDF: Standard for
metadata representation


Basis for interoperability in applications


Cost effective development of tools and
applications


Basis for very different users: Digital libraries,
content rating, B2B, etc.



RDF
-
Schema
: Definition of simple ontologies
in the WWW.



W3C Recommendation RDF is used by
different software companies and
standardization organisations



RDF


Data Model for the
Semantic Web

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Not the subatomic particle ...
KA
rlsruhe
On
tology



Based on RDF(S), with several extensions, e.g. for
typed, multilingual lexical expressions



Component
-
based, easily extendable application
framework



Open
-
Source Tool Suite, supporting




KAON


A RDF
-
based Software
Infrastructure

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KAON Architecture


RDF

Files

P2P

Relational

Database

Relational

Database

NLP Service

Applications

& Services

Web Application Framework

HTMLBrowser

Ontology and

Metadata Editing

Reverse Engineering

SYNDICATION

KAON Portal

Portal Maker

OntoMat App Framework

Focused Crawler

Text Mining

Evolution

Legacy Portals

KAON
-
API

RDF
-
API

K
-
Edutella

Wrapper

KAON
-
Server

J2EE

Middleware

NLP
-
API

QEL
-

Wrapper

NLP
-
API

Reasoning Service

DOC
-
API

Doc
-
Manag. Service

Data

And

Remote

Services

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Ontology Engineering Plugin
-

SOEP





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Database Reverse Engineering
Plugin
-

REVERSE





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Text Extraction Plugin





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Focused Document/Metadata Crawling Plugin







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Further Plugins


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Automatic Ontology Extraction Component
-

TextToOnto


Ontology
-
based Document Clustering


Hierarchical Text classification


Automatic Yahoo
generation


View definition component


Peer
-
2
-
Peer
-
based document annotation and authoring


(for HTML, PDF, JPEG, GIF)


Graphical Query Interface based on QEL


SVG
-
based visualization


Versioning component

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KAON Portal

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KAON Portal is a set of tools supporting
ontology
-
based web site management


It supports web
-
based presentation of
information for users (generated and extracted
by other components)


It also provides means for defining information
(cooperatively!)

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Rapid Prototyping a Semantic
Portal

KAON

Engineering

Frontend

KAON

User Rapid

Prototyp

Frontend

KAON

Backend

KAON Server

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Finally: What is behind ? KAON
Server!


Middleware

connects

applications

with

data

and

network

services


Generic

API’s

for


Access

to

ontologies

and

metadata


Access

to

documents


Access

to

language

processing

tools


P
2
P

Access


API‘s

are

implemented,

e
.
g
.

by

Stanfords

RDF
-
API,

by

J
2
EE

complient

implementation,etc
.


Connectors

JXTA


HTTP, IIOP



WebDAV


Java API





Security

Authorization

Authentication

Encryption



Auditing



Management

Transaction

Replication

Naming Services Storage



Data Access

Query


Update

Validatation

Inferencing



External Services

TP Monitors

Databases

Inference Engines





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Summarization KAON


KAON is basis for approx. 10
research and industry projects. It
is also used by external projects
all over the world.


Open Source Community is
growing, currently 35 persons.


KAON is basis for building
knowledge
-
intensive and
semantics
-
based applications.

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Agenda

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Introduction & Motivation


Introduction
-

Semantic Web


Semantic Web Applications


Semantic Web Technology


Next Steps

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Conclusion


We are on the way to a global information structure, being
based on the World Wide Web and it‘s successor Semantic Web



The main vision is: Support machine
-
processable and
interpretable data to provide a higher degree of automatization
(e.g. Web Services, Query Answering, etc.)



Standards and tools for ontologies and metadata are ready to
use!

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Next Steps


Semantic Web technology should be the basis for the
Agricultural Ontology Service (AOS)



KAON already provides ready
-
to
-
run, open
-
source tools on
which the specific AOS functionalities may be built!



Rapid prototyping approach is promising:


Convert AGROVOC in RDF(S), connect it with existing data
sources and present the information in the Web browser!