Intelligent Systems

1

• Intelligent Systems
• Lecture 24
• Ontologies. Semantic WEB
• (based on presentation of Forschungszentrum
  Informatik at the University of Karlsruhe,
  Germany)

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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
13.12.2005

• Introduction Motivation
• Introduction - Semantic Web
• Semantic Web Applications
• Semantic Web Technology
• Next Steps

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Application fields and technologies
Application Fields
Basic 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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On the Way to a Global Information Structure
Arpanet
Internet/WWW
Semantic Web
...
Concepts
Objects
Packets
1965
1985
2000
1975
1995
2005
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Agenda
13.12.2005

• Introduction Motivation
• Introduction - Semantic Web
• Semantic Web Applications
• Semantic Web Technology
• Next Steps

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The Origin of the WWW
Information Management A Proposal, Tim
Berners-Lee, CERN, 1989
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Semantic Web Bringing the Web to its Full
Potential
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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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Relational Metadata

• 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)

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Agenda
13.12.2005

• 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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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
- Search relevant Web resources

• Cooperatively add
• further information
• in the form of
• metadata!
• Semantic Portals
• for HR strategy

DEMO
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Virtual Museum (I)
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Virtual Museum (II)
DEMO
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News Services - Content Syndication with RSS (I)
13.12.2005
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

http//www.ontoweb.org
Participating Siten
Content Syndication Service
...

Participating Site2

AnnotatedWeb Pages
Participating Site1
OntologyBrowse QueryFront End
Generated Content Objects
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General Web Services
13.12.2005

• 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!
• gt 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
13.12.2005

• 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.
• gt 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 Data Model for the Semantic Web

• 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

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KAON A RDF-based Software Infrastructure

• Not the subatomic particle ...KArlsruhe Ontology
• 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

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KAON Architecture
Web Application Framework
OntoMat App Framework
HTMLBrowser
KAON Portal Portal Maker
Legacy Portals
Reverse Engineering
Applications Services
Ontology and Metadata Editing
Focused Crawler
SYNDICATION
Evolution
Text Mining
KAON-API
NLP-API
NLP-API
DOC-API
QEL- Wrapper
KAON-Server
Middleware
K-Edutella Wrapper
J2EE
RDF-API
Doc-Manag. Service
Data And Remote Services
NLP Service
Relational Database
RDFFiles
Reasoning Service
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Ontology Engineering Plugin - SOEP

DEMO
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Database Reverse Engineering Plugin - REVERSE

DEMO
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Text Extraction Plugin

DEMO
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Focused Document/Metadata Crawling Plugin

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Further Plugins
13.12.2005

• 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
13.12.2005

• 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 User Rapid Prototyp Frontend
KAON Engineering Frontend
KAON Server
KAON Backend
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Finally What is behind ? KAON Server!

• Middleware connects applications with data and
  network services
• Generic APIs for
• Access to ontologies and metadata
• Access to documents
• Access to language processing tools
• P2P Access
• APIs are implemented, e.g. by Stanfords RDF-API,
  by J2EE complient implementation,etc.

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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
13.12.2005

• 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
  its 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!