Ontological Engineering: With Examples from the Areas of Knowledge Management, E-Commerce and the Semantic Web

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©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 1
Ontological Engineering
Asunción Gómez-Pérez
Mariano Fernández-López
Oscar Corcho
{asun, mfernandez, ocorcho}@fi.upm.es
Grupo de Ontologías
Laboratorio de Inteligencia Artificial
Facultad de Informática
Universidad Politécnica de Madrid
Campus de Montegancedo sn,
28660 Boadilla del Monte, Madrid, Spain

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 1
Ontological Engineering
Asunción Gómez-Pérez
Mariano Fernández-López
Oscar Corcho
{asun, mfernandez, ocorcho}@fi.upm.es
Grupo de Ontologías
Laboratorio de Inteligencia Artificial
Facultad de Informática
Universidad Politécnica de Madrid
Campus de Montegancedo sn,
28660 Boadilla del Monte, Madrid, Spain
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 2
Table of Contents
1. The Role of Ontologies in the Semantic Web
2. Theoretical Foundations of Ontologies
3. Methodologies and Tools for Building Ontologies
4. Ontology Languages
5. Ontology-based Applications

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 3
The Role of Ontologies in the Semantic Web
Asunción Gómez-Pérez
Mariano Fernández-López
Oscar Corcho
{asun, mfernandez, ocorcho}@fi.upm.es
Grupo de Ontologías
Laboratorio de Inteligencia Artificial
Facultad de Informática
Universidad Politécnica de Madrid
Campus de Montegancedo sn,
28660 Boadilla del Monte, Madrid, Spain
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 4
URI, HTML, HTTP
Static
WWW
500 millons of users
More than 3 billions of pages
The problem: Information overload on the WEb

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 5
The current Web is based on HTML
ر ﻮﻄﺘﻟا ﻢﻠﻋﻰﻓ ﺔﺳﺪﻨﻬﻟا <b>: ﻢﺳﻻا</b><BR>
زﺮﺒـﺰﻣﻮﻏ نﻮﻴﺴﻨﺳﺁ <b>: نﻮﻔّﻟﺆﻤﻟا</b><BR>
$74.95 <b>: ﺮﻌّﺴﻟا</b><BR>
ﺞﺘﻨﻤﻟا <b>: بﺎﺘﻜﻟا</b><BR>
ر ﻮﻄﺘﻟا ﻢﻠﻋﻰﻓ ﺔﺳﺪﻨﻬﻟا :ﻢﺳﻻا
زﺮﺒـﺰﻣﻮﻏ نﻮﻴﺴﻨﺳﺁ : نﻮﻔّﻟﺆﻤﻟا
$74.95 : ﺮﻌّﺴﻟا
بﺎﺘﻜﻟا : ﺞﺘﻨﻤﻟا
Arab
<b>Title:</b> Ontological Engineering <BR>
<b>Authors:</b> Asunción Gómez-Pérez... <BR>
<b>Price:</b> $74.95<BR>
<b>Product:</b> Book<BR>
Title: Ontological Engineering
Authors: Asunción Gómez-Pérez...
Price: $74.95
Product: Book
English
<b>Skjøte:</b> Ontological Ingeniørarbeid<BR>
<b>Forfatter:</b> Overtakelse Gómez-Pérez... <BR>
<b>Pris:</b> 74.95€<BR>
<b>Produkt:</b> Bok<BR>
Skjøte: Ontological Ingeniørarbeid
Forfatter: Overt akelse Gómez-Pérez...
Pris: 74.95€
Produkt: Bok
Norwegian
.- HTML is useful for browsing the information
.- Content is language-dependent
.- High cost for keeping the information up-to-date
Japanese
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 6
XML allows the creation of metada with “meaning”
¿What do the tags mean for the machine?
<Title>Ontological Engineering</Title>
<Author>Asunción Gómez-Pérez...</Author>
<Price>$74.95</Price>
<Product>Book</Product>
Title: Ontological Engineering
Authors: Asunción Gómez-Pérez...
Price: $74.95
Product: Book
English
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< نﻮﻔّﻟﺆﻤﻟا> زﺮﺒـﺰﻣﻮﻏ نﻮﻴﺴﻨﺳﺁ </ نﻮﻔّﻟﺆﻤﻟا>
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زﺮﺒـﺰﻣﻮﻏ نﻮﻴﺴﻨﺳﺁ : نﻮﻔّﻟﺆﻤﻟا
$74.95 : ﺮﻌّﺴﻟا
بﺎﺘﻜﻟا : ﺞﺘﻨﻤﻟا
Arab

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 7
The problem of choosing information
.- Find the information
.- Extract relevant information
.- Interpretation by human users
.- Sinthesis
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 8
The problem of content agregation:
From Madrid to Tokyo
.- Content in different languages (Spanish, English, Japanesse,...)
.- Find out relevant information from heterogeneous sources
.- Extract
.- Interpretation
.- Agregation
.- Consistency of the information

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 9
What was the Web intended to be?
“... a goal of the Web was that, if the interaction between
person and hypertext could be so intuitive that the
machine-readable information space gave an accurate
representation of the state of people's thoughts,
interactions, and work patterns, then machine analysis
could become a very powerful management tool, seeing
patterns in our work and facilitating our working together
through the typical problems which beset the management
of large organizations.”
[Berners-Lee 1996]
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 10
IBXX is a flight. Its
departure place is
Madrid and its arrival
place is Tokyo.
Madrid is an european
city. Tokyo is an
asian city.
Herzt is a
rental car
company with
luxury cars in
tokyo.
The new
national theater
is a theater
located in
Tokyo.It has
peformances
every Saturday.
Why not make the computers do the work?
Metadata
Integration
Knowledge
Inference
Xxx is a
hotel placed
in Tokyo

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 11
“The Semantic Web is an extension of the current Web in which
information is given well-defined meaning, better enabling computers
and people to work in cooperation. It is based on the idea of having data
on the Web defined and linked such that it can be used for more effective
discovery, automation, integration, and reuse across various
applications.”
Hendler, J., Berners-Lee, T., and Miller, E.
Integrating Applications on the Semantic Web, 2002,
http://www.w3.org/2002/07/swint.html
What is the Semantic Web?
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 12
Static URI, HTML, HTTP
WWW
Semantic Web Languages
RDF, RDFS, OWL
Semantic Web
Semantic richness
Dynamic

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 13
<rdf:Description rdf:about='Asunción Gómez-Pérez'>
<rdf:type rdf:resource=‘ Associate Prof'/>
<NS0:Full_Name>A. GomezPerez</NS0:Full_Name>
<NS0:Belongs_To>UPM</NS0: Belongs_To >
<NS0:e-mail>asun@fi.upm.es</NS0:e-mail>
Person Organization
Has_contact_Person
Belongs_To
Associate Prof. Partner
Subclass of
URL
Web Page
xmlns:rdf='http://www.w3.org/1999/02/22-rdf-syntax-ns#'
xmlns:NS0='http://www.esperonto.net/semanticportal/RDFS/Person_Ontology#'
xmlns:NS1='http://www.esperonto.net/semanticportal/RDFS/Organization_Ontology#'
<rdf:Description rdf:about='UPM'>
<rdf:type rdf:resource='Pa rtner'/>
<NS1:Acronym>UPM</NS1:Acronym>
<NS1:Has_Contact_Person>Asunción Gómez-Pérez
</NS1:Has_Contact_Person >
Instance of Instance of
Subclass of
Annotation
(RDF)
http://www.esperonto.net http://www.esperonto.net
Ontologies and Metadata
Ontologies
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 14
Static URI, HTML, HTTP
WWW
Web Services
Peer Web for information exchange between machines
RDF, RDFS, OWL
Semantic Web
UDDI, WSDL, SOAP
Web Services
Dynamic
Semantic richness
Declaratively described Program Access Interfaces
that are accessible through the Web
To register Services
Service Access Interfaz
Communication Protocol
To describe control flows
Terminological
problems

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 15
Static URI, HTML, HTTP
WWW
The Semantic Web and the Semantic Web Services
RDF, RDFS, OWL
Semantic Web
Semantic Web ServicesDynamic
Semantic richness
UDDI, WSDL, SOAP
Web Services
Web Services that describe their properties and capabilities using
the vocabulary of an ontology, and they are expressed in some semantic markup language
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 16
<process:CompositeProcess rdf:ID= “buyMovieTicket”>
<process:composedOf>
<process:Sequence>
<process:components rdf:parseType="Collection">
<process:AtomicProcess rd f:resource=“#findCinema" />
<process:AtomicProcess rd f:resource="#checkTimeTable" />
<process:AtomicProcess rd f:resource="#selectSeat” />
<process:AtomicProcess red :resource=“#buyTicket” /> ...
Process
<owl:Class rdf:ID="CompositePro cess">
<rdfs:subClassOf rdf:resource="#Pro cess"/>
<owl:disjointWith rdf:resource="#AtomicProcess"/>
<owl:disjointWith rdf:resource="#SimpleProcess"/> ... Composite
Process
Atomic
Process
OWL-S
instances
Knowledge
level
Simple
Process
Instance of
Instance of
Subclass of Subclass of Subclass of
Ontologies
Semantic Web Services

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 17
A Semantic Web Scenario
Emails
Documents
Static Web Pages
On-line DB
(Unknown schema)
Applicationss Web Services
Current Web
Agente
Semantic Web Services
Real World
Restrcited web sites
Agente Agente Agente
Intelligent Agents
Users Companies
Dinamyc Web pages
Ontologies Metadata:Annotation
Intelligent Agents
Web Services
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 18
Ontological Enginnering for the Semantic Web
Build Ontologies
Tools
Methodologies and
methods
Reasoners
Applications
Languages

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 1
Table of Contents
1. The Role of Ontologies in the Semantic Web
2. Theoretical Foundations of Ontologies
3. Methodologies and Tools for Building Ontologies
4. Ontology Languages
5. Ontology-based Applications
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 2
Theoretical Foundations of Ontologies
Asunción Gómez-Pérez
Mariano Fernández-López
Oscar Corcho
{asun, mfernandez, ocorcho}@fi.upm.es
Grupo de Ontologías
Laboratorio de Inteligencia Artificial
Facultad de Informática
Universidad Politécnica de Madrid
Campus de Montegancedo sn,
28660 Boadilla del Monte, Madrid, Spain

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 3
Main References
Gómez-Pérez, A.; Fernández-López, M.; Corcho, O. Ontological Engineering. Springer Verlag. 2003
http://www.ontoweb.org
Deliverables
•D1.1
•D1.2
•D1.3
•D1.4
•D1.5
Neches, R.; Fikes, R.; Finin, T.; Gruber, T.; Patil, R.; Senator, T.; Swartout, W.R. Enabling Technology for Knowledge Sharing.
AI Magazine. Winter 1991. 36-56.
Gruber, T. A translation Approach to portable ontology specifications. Knowledge Acquisition. Vol. 5. 1993. 199-220.
Uschold, M.; Grüninger , M. ONTOLOGIES: Principles, Methods and Applications. Knowledge Engineering Review. Vol. 11; N. 2; June 1996.
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 4
Outline
The Knowledge Sharing Initiative
Definitions of Ontologies
Modeling of Ontologies
Types of Ontologies
Libraries of Ontologies
Ontological Commitments

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 5
Reuse and Sharing
Reuse means to build new applications
assembling components already built
Advantages:
•Less money
•Less time
•Less resources
Sharing is when different
applications use the some resources
Areas:
•Software
•Knowledge
•Communications
•Interfaces
•---
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 6
The knowledge Sharing Initiative
“Building new Knowledge Based Systems today usually entails constructing new
knowledge bases from scratch. It could instead be done by assembling reusable components.
System developers would then only need to worry about creating the specialized knowledge and
reasoners new to the specific task of their systems. This new system would interoperate with
existing systems, using them to perform some of its reasoning. In this way,
declarative knowledge, problem-solving techniques, and reasoning services could all
be shared between systems. This approach would facilitate building bigger and better systems
cheaply. The infraestructure to support such sharing and reuse would lead to greater
ubiquity of these systems, potentially transforming the knowledge industry ...”
Neches, R.; Fikes, R.; Finin, T.; Gruber, T.; Patil, R.; Senator, T.; Swartout, W.R. Enabling Technology for Knowledge Sharing.
AI Magazine. Winter 1991. 36-56.

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 7
Reusable Knowledge Components
Problem Solving MethodsOntologies
Describe the reasoning process of a KBS in
an implementation and domain-independent manner
Describe domain knowledge in a generic way
and provide agreed understanding of a domain
Interaction Problem
Representing Knowledge for the purpose of solving some problem
is strongly affected by the nature of the problem
and the inference strategy to be applied to the problem [Bylander et al., 88
Bylander Chandrasekaran, B. Generic Tasks in knowledge-based reasoning.: the right level of abstraction for know ledge acquisition.
In B.R. Gaines and J. H. Boose, EDs Knowledge Acquisition for Knowledge Based systems, 65-77, London: Academic Press 1988.
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 8
Outline
The Knowledge Sharing Initiative
Definitions of Ontologies
Modeling of Ontologies
Types of Ontologies
Libraries of Ontologies
Ontological Commitments

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 9
Definitions of Ontologies (I)
1. “An ontology defines the basic terms and relations comprising the vocabulary of
a topic area, as well as the rules for combining terms and relations to define
extensions to the vocabulary”
Neches, R.; Fikes, R.; Finin, T.; Gruber, T.; Patil, R.; Senator, T.; Swartout, W.R. Enabling Technology for Knowledge Sharing.
AI Magazine. Winter 1991. 36-56.
2. “An ontology is an explicit specification of a conceptualization”
Gruber, T. A translation Approach to portable ontology specifications. Knowledge Acquisition. Vol. 5. 1993. 199-220.
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 10
Definitions of Ontologies (II)
3. An ontology is a hierarchically structured set of terms for describing a domain
that can be used as a skeletal foundation for a knowledge base.
B. Swartout; R. Patil; k. Knight; T. Russ. Toward Distributed Use of Large-Scale Ontologies
Ontological Engineering. AAAI-97 Spring Symposium Series. 1997. 138-148.
4. An ontology provides the means for describing explicitly the conceptualization
behind the knowledge represented in a knowledge base.
A. Bernaras;I. Laresgoiti; J. Correra. Building and Reusing Ontologies for Electrical Network Applications
ECAI96. 12th European conference on Artificial Intelligence. Ed. John Wiley & Sons, Ltd. 298-302.

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 11
Definitions of Ontologies (III)
5. “An ontology is a formal, explicit specification of a shared conceptualization”
Studer, Benjamins, Fensel. Knowledge Engineering: Principles and Methods. Data and Knowledge Engineering. 25 (1998) 161-197
Abstract model and
simplified view of some
phenomenon in the world
that we want to represent
Machine-readable
Concepts, properties
relations, functions,
constraints, axioms,
are explicitly defined
Consensual
Knowledge
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 12
Definitions of Ontologies (I)
1. “An ontology defines the basic terms and relations comprising the
vocabulary of a topic area, as well as the rules for combining terms and
relations to define extensions to the vocabulary”
Neches R, Fikes RE, Finin T, Gruber TR, Senator T, Swartout W R
(1991) Enabling technology for knowledge sharin g. AI Magazine
12(3):36–56
2. “An ontology is an explicit specification of a conceptualization” Gruber TR (1993a) A translation approach to portable
ontology specification. Knowledge Acquisition
5(2):199–220
3. “An ontology is a formal, explicit specification of a shared
conceptualization”
Studer R, Benjamins VR, Fensel D (1998) Knowledge E ngineering:
Principles and Methods.
IEEE Transactions on Data and Knowledge Engineering 25(1-
2):161–197
4. “A logical theory which gives on explicit, partial account of a
conceptualization”
Guarino N, Giaretta P (1995) Ontologies and Knowledge Bas es:
Towards a Terminological Clarification. In: Mars N (ed)
Towards Very Large Knowledge Bases: Knowledge Building
and Knowledge Sharing (KBKS’95). University of Twente,
Enschede, The Netherlands. IOS Press, Am sterdam, The
Netherlands, pp 25–32
5. “A set of logical axioms designed to account for the intended
meaning of a vocabulary”
Guarino N (1998) Formal Ontology in Information Systems. In:
Guarino N (ed) 1st International Conference on
Formal Ontology in Information Systems (FOIS’98). Trento,
Italy. IOS Press, Amsterdam, pp 3–15

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 13
Definitions of Ontologies (II)
Lightweight Ontologies :
•Include Concepts with properties and Taxonomies
•Do not include Axioms and constraints.
Heavyweight Ontologies :
•Include all the components
•Excellent!! If they have a lot of axioms.
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 14
Outline
The Knowledge Sharing Initiative
Definitions of Ontologies
Modeling of Ontologies
•Components
•Principles
•Approaches
Types of Ontologies
Libraries of Ontologies
Ontological Commitments

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 15
Components of an Ontology
Concepts are organized in
Relations
Functions
Axioms
Instances
R: C1 x C2x ... x Cn-1 x Cn
F: C1 x C2x ... x Cn-1 --> Cn
Elements
Sentences which are always true
Subclass-of: Concept 1 x Concept2
Connected to: Component1 x Component2
Mother-of: Person --> Women
Price of a used car: Model x Year x Kilometers --> Pric e
Gruber, T. A translation Approach to portable
ontology specifications. Knowledge Acquisition.
Vol. 5. 1993. 199-220.
taxonomies
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 16
Primitivas necesarias para modelizar
conocimientos disjuntos en taxonomías
class-Partition: Conjunto de clases que son disjuntas entre sí
Disjoint: un conjunto de clases que son disjuntas entre sí son subclase de una clase padre
Exhaustive-Disjoint: un conjunto de clases que son disjuntas entre sí son subclase de una clase padre
y el conjunto de clases definen completamente a la clase pad re.

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 17
Subclass-Of
Superclass-Of
Person Dog Cat
Subclass-Of
Pluto
Instance-Of
Instance-Of
Cartoon Dog
Mammal
How to build taxonomies (II)
Subclass-Of
Subclass-Of
Semantic Error
Pluto could be an instance of cat and dog
A. Gómez-Pérez. Evaluation ofOntologies.
International Journal of Intelligent Systems.
Vol. 16, Nº3. March 2001. PP391-410
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 18
Person Dog Cat
Subclass-Of
Pluto
Instance-Of
Cartoon Dog
Mammal
How to build taxonomies (III)
Subclass-Partition
Disjoint
Instance-Of Has-Instance
Pluto can not be simultaneously a class of Cat and
Dog because they are disjoint
A. Gómez-Pérez. Evaluation ofOntologies.
International Journal of Intelligent Systems.
Vol. 16, Nº3. March 2001. PP391-410

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 19
How to build taxonomies (IV)
Subclass-Partition
Number
Even Odd
Disjoint
4
Instance-Of Four is an instance of Par
A. Gómez-Pérez. Evaluation ofOntologies.International Journal of Intelligent Systems. Vol. 16, Nº3. March 2001. PP391-410
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 20
Subclass-Partition
Number
Odd Even
How to build taxonomies (V)
Exhaustive-Disjoint
4
Instance-Of
Four is an instance of something in the partition

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 21
Example of Domain Ontology
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 22

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 23
What does an Explicit Ontology look Like?
Highly informal:
Semi-informal:
Semi-formal:
Rigorously formal:
in natural language
in a restricted and structured form of natural language
in an artificial and formally defined language
in a language with formal semantics, theorems and proofs
of such properties as soundness and completeness
Uschold, M.; Grüninger , M. ONTOLOGIES: Principles, Methods and Applications.
Knowledge Engineering Review. Vol. 11; N. 2; June 1996.
Example
Example
An html ontology for linking documents
Example
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 24
Principles for the Design of Ontologies (I)
Clarity:
To communicate the intended meaning of defined terms
Coherence:
To sanction inferences that are consistent with definitions
Extendibility:
To anticipate the use of the shared vocabulary
Minimal Encoding Bias:
To be independent of the symbolic level
Minimal Ontological Commitments:
To make as few claims as possible about the world
• Gruber, T.; Towards Principles for the Design of Ontologies.
KSL-93-04. Knowledge Systems Laboratory.
Stanford University. 1993

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 25
Clarity
(define-class Travel (?travel)
"A journey from place to place"
:axiom-def
(and (Superclass-Of Travel Flight)
(Subclass-Of Travel Thing)
(Template-Facet-Value Cardinality
arrivalDate Travel 1)
(Template-Facet-Value Cardinality
departureDate Travel 1)
(Template-Facet-Value Maximum-Cardinality
singleFare Travel 1))
:def
(and (arrivalDate ?travel Date)
(departureDate ?travel Date)
(singleFare ?travel Number)
(companyName ?travel String)))
No Clarity
An ontology should communicate effectively the intended meaning of defined terms.
Definitions should be objective. Definitions can be stated on formal axioms, and a complete definition
(defined by necessary and sufficient conditions) is preferred over a partial definition
(defined by only necessary or sufficient conditions). . .
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 26
Clarity
(define-class Travel (?travel)
"A journey from place to place"
:axiom-def
(and (Superclass-Of Travel Flight)
(Subclass-Of Travel Thing)
(Template-Facet-Value Cardinality
arrivalDate Travel 1)
(Template-Facet-Value Cardinality
departureDate Travel 1)
(Template-Facet-Value Maximum-Cardinality
singleFare Travel 1))
:iff-def
(and (arrivalDate ?travel Date)
(departureDate ?travel Date))
:def
(and (singleFare ?travel Number)
(companyName ?travel String)))
Clarity

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 27
Minimal Encoding Bias
(define-class Travel (?travel)
"A journey from place to place"
:axiom-def
(and (Superclass-Of Travel Flight)
(Subclass-Of Travel Thing)
(Template-Facet-Value Cardinality
arrivalDate Travel 1)
(Template-Facet-Value Cardinality
departureDate Travel 1)
(Template-Facet-Value Maximum-Cardinality
singleFare Travel 1))
:iff-def
(and (arrivalDate ?travel Date)
(departureDate ?travel Date))
:def
(and (singleFare ?travel Number)
(companyName ?travel String)))
No minimal Encoding Bias
“The conceptualization should be specified at the knowledge level
without depending on a particular symbol-level encoding”.
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 28
Instance-of
Unit-of-Measure
Ampere
Amu
Angstrom
.
.
.
Volt
Watt
Year
Instance-of
Subclass-of
System-of-Units Si-Unit
Instance-of
Instance-of
Ampere
Candela
Degree-Kelvin
Identity-Unit
Kilogram
Meter
Mole
Second-of-Time
Instance-of
Standard-Units Ontology
Physical-Dimension
Physical-Quantities Ontology
....
Density-Dimension
....
Frequency-Dimension
....
Length-Dimension
Mass-Dimension
....
Pressure-Dimension
Resistance-Dimension
......
Work-Dimension
Standard-Dimensions Ontology
Instance-of
Instance-of
Currency Dimension
Euro
Minimal Encoding Bias

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 29
Minimal Encoding Bias
(singleFare ?travel Number)
should be substituted by:
(singleFare ?travel CurrencyQuantity)
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 30
Extensibility
“One should be able to define new terms
for special uses based on the existing vocabulary,
in a way that does not require the revision of the existing definitions”.
•Currency dimension
•Definition of currencies
•Relationship between currencies
(define-individual Euro (Unit-of-Measure)
"An Euro is the currency on the European Union"
:= (* 0,96 USDollar)
:axiom-def
(= (Quantity.dimension Euro) CurrencyDimension))

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 31
Coherence
“An ontology should be coherent: that is, it should sanction inferences
that are consistent with the definitions.[…]
If a sentence that can be inferred from the axioms contradicts a definition
or example given informally, then the ontology is incoherent”.
(define-axiom No-Train-between-USA-and-Europe
"It is not possible to travel by train between the USA and Europe"
:= (forall (?travel)
(forall (?city1)
(forall (?city2)
(=> (and (Travel ?travel)
(arrivalPlace ?travel ?city1)
(departurePlace ?travel ?city2)
(or (and (EuropeanLocation ?city1)
(USALocation ?city2))
(and (EuropeanLocation ?city2)
(USALocation ?city1) )))
(not (TrainTravel ?travel)))))))
(define-instance Madrid (EuropeanLocation))
(define-instance NewYork (USALocation))
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 32
Minimal Ontological Commitments
“Since ontological commitment is based on the consistent use of the vocabulary,
ontological commitment can be minimized by specifyingthe weakest theory
and defining only those terms that are essential to the communication of knowledge
consistent with the theory”.
(define-class Travel (?travel)
"A journey from place to place"
:axiom-def
( .... )
:iff-def
(and (arrivalDate ?travel Date)
(departureDate ?travel Date))
:def
(and (singleFare ?travel Number)
(companyName ?travel String)))
•What is a date?
•Absolute/relative date?
•could be an interval?
•date= month + year
•date= day + month +year
•date = month +day +year

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 33
Principles for the Design of Ontologies (IV)
Arpírez JC, Gómez-Pérez A, Lozano A, Pinto HS (1998) (ONTO)2Agent: An ontology-based WWW broker to select ontologies.
In: Gómez-Pérez A, Benjamins RV (eds) ECAI’98 Workshop on Applications of Ontologies and Problem-Solving Methods.
Brighton, United Kingdom, pp 16–24
•The representation of disjoint and exhaustive knowledge. If the set of
subclasses of a concept are disjoint, we can define a disjoint decomposition.
The decomposition is exhaustive if it defines the superconcept completely.
•To improve the understandability and reusability of the ontology, we should
implement the ontology trying to minimize the syntactic distance between
sibling concepts.
•The standardization of names. To ease the understanding of the ontology
the same naming conventions should be used to name related terms.
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 34
Approaches for Modeling Ontologies
•Using frames and first order logic
•Using description logic
•Using UML
•Using the entity relationship model

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 35
Using Frames and First Order Logic for Modeling Ontologies
(define-class Travel (?travel)
"A journey from place to place"
:axiom-def
(and (Superclass-Of Travel Flight)
(Template-Facet-Value Cardinality
arrivalDate Travel 1)
(Template-Facet-Value Cardinality
departureDate Travel 1)
(Template-Facet-Value Maximum-Cardinality
singleFare Travel 1))
:def
(and (arrivalDate ?travel Date)
(departureDate ?travel Date)
(singleFare ?travel Number)
(companyName ?travel String)))
(define-function Pays (?room ?discount) :-> ?finalPrice
"Price of the room after applying the discount"
:def (and (Room ?room) (Number ?discount)
(Number ?finalPrice)
(Price ?room ?price))
:lambda-body
(- ?price (/ (* ?price ?discount) 100)))
(define-relation connects (?edge ?source ?target)
"This relation links a source and a target by an edge.
The source and destination are considered as spatial
points. The relation has the following properties: symmetry
and irreflexivity."
:def (and (SpatialPoint ?source)
(SpatialPoint ?target)
(Edge ?edge))
:axiom-def
((=> (connects ?edge ?source ?target)
(connects ?edge ?target ?source)) ;symmetry
(=> (connects ?edge ?source ?target)
(not (or (part-of ?source ?target) ;irreflexivity
(part-of ?target ?source))))))
(define-instance AA7462-Feb-08-2002 (AA7462)
:def ((singleFare AA7462-Feb-08-2002 300)
(departureDate AA7462-Feb-08-2002 Feb8-2002)
(arrivalPlace AA7462-Feb-08-2002 Seattle)))
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 36
Using Description Logics for Modeling Ontologies
(defconcept Travel
"A journey from place to place"
:is-primitive
(:and
(:all arrivalDate Date)(:exactly 1 arrivalDate)
(:all departureDate Date)(:exactly 1
departureDate)
(:all companyName String)
(:all singleFare Number)(:at-most singleFare 1)))
(defrelation Pays
:is
(:function (?room ?Discount)
(- (Price ?room) (/(*(Price ?room) ?Discount) 100)))
:domains (Room Number)
:range Number)
(defrelation connects
"A road connects two different cities"
:arity 3
:domains (Location Location)
:range RoadSection
:predicate
((?city1 ?city2 ?road)
(:not (part-of ?city1 ?city2))
(:not (part-of ?city2 ?city1))
(:or (:and (start ?road ?city1)(end ?road ?city2))
(:and (start ?road ?city2)(end ?road ?city1)))))
(tellm (AA7462 AA7462-08-Feb-2002)
(singleFare AA7462-08-Feb-2002 300)
(departureDate AA7462-08-Feb-2002 Feb8-2002)
(arrivalPlace AA7462-08-Feb-2002 Seattle))

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 37
Using UML for Modeling Ontologies
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 38
Using the Entity Relationship Model for
Modeling Ontologies

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 39
Conclusions on the Different Approaches to Build
Ontologies
•The formalism and the language limit the kind of knowledge that can be
represented
•All the aforementioned formalisms allow representing: classes, organized in class
taxonomies, attributes, and binary relations
•Only AI formalisms are specially prepared to model formal axioms either as
independent components in the ontology or embedded in other components
•A domain model is not necessarily an ontology only because it is written in
Ontolingua or OWL, for the same reasons that we cannot say that a program is a
knowledge-based system because it is written in Prolog
•Although some languages are more appropriate than others to represent ontologies,
a model is an ontology only if it is agreed and machine readable
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 40
Outline
The Knowledge Sharing Initiative
Definitions of Ontologies
Modeling of Ontologies
Types of Ontologies
Libraries of Ontologies
Ontological Commitments

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 41
Catalog/ID
Thessauri
“narrower term”
relation
Formal
is-a
Frames
(properties)
General
Logical
constraints
Terms/
glossary
Informal
is-a
Formal
instance
Value
Restrs.
Disjointness,
Inverse, part-Of ...
Types of Ontologies
Lassila and McGuiness Classification
Lassila O, McGuiness D. The Role of Frame-Based Representation on the Semantic W eb.
Technical Report. Knowledge Systems Laboratory. Stanford University. KSL-01-02. 2001.
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 42
Types of Ontologies
Issue of the
Conceptualization
Application O.
• Non reusable
• Usable
Domain O.
• Reusable
Generic O.
• Reusable across D.
Representation O.
• Conceptualization
of KR formalisms
Van Heist, G.; Schreiber, T.; Wielinga, B.
Using Explicit Ontologies in KBS
International Journal of Human-Computer Studies.
Vol. 46. (2/3). 183-292. 1997
Content Ontologies
Task O.
General/Common O.
Domain O.
Scalpel, scanner
anesthetize, give birth
Mizoguchi, R. Vanwelkenhuysen, J.; Ikeda, M.
Task Ontology for Reuse of Problem Solving Knowledge.
Towards Very Large Knowledge Bases:
Knowledge Building & Knowledge Sharing.
IOS Press. 1995. 46-59.
goal, schedule
to assign, to classify
Things, Events, Time, Space
Causality, Behavior, Function

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 43
Knowledge Representation Ontologies
•Gruber TR (1993a) A translation approach to portable ontology
specification. Knowledge Acquisition 5(2):199– 220
•Chaudhri VK, Farquhar A, Fikes R, Karp PD, Rice JP (1998) Open
Knowledge Base Connectivity 2.0.3. Technical Report.
http://www.ai.sri.com/~okbc/okbc-2-0-3.pdf
Lassila O, Swick R (1999) Resource Desc ription Framework (RDF)
Model and Syntax Specification. W3C Recommendation.
http://www.w3.org/TR/REC-rdf-syntax/
Horrocks I, Fensel D, Harmelen F, Decker S, Erdmann M, Kl ein M
(2000) OIL in a Nutshell. In: Dieng R, Corby O (eds) 12th
International Conference in Knowledge Engine ering and Knowledge
Management (EKAW’00). Juan-L es-Pins, France. (Lecture Notes in
Artificial Intelligence LNAI 1937) Springer-Verlag, B erlin, Germany,
pp 1–16
Horrocks I, van Harmelen F (eds) (2001) Reference Descript ion of
the DAML+OIL (March 2001) Ontology Markup Language.
Technical report. http://www.daml.org/2001/03/reference.html
Dean M, Schreiber G (2003) OWL Web Ontology Language
Reference. W3C Working Draf t. http://www.w3.org/TR/owl-ref/
•The Frame Ontology and the OKBC Ontology
(http://ontolingua.stanford.edu)
•RDF and RDF Schema knowledge representation ontologies
(http://www.w3.org/1999/02/22-rdf-syntax-ns
http://www.w3.org/2000/01/rdf-schema)
•OIL knowledge representation ontology
(http://www.ontoknowledge.org/oil/rdf-schema/2000/11/10-oil-standard)
•DAML+OIL knowledge representation ontology
(http://www.daml.org/2001/03/daml+oil)
•OWL knowledge representation ontology
(http://www.w3.org/2002/07/owl)
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 44
Top-level Ontologies
•Top-level ontologies of universals and particulars (http://webode.dia.fi.upm.es/)
•Sowa’s top-level ontology (http://www.jfsowa.com/ontology/toplevel.htm)
•Cyc’s upper ontology
(http://www.cyc.com/cyc-2-1/cover.html)
•The Standard Upper Ontology (SUO)
(http://suo.ieee.org/)
•Guarino N, Welty C (2000) A Formal Ontology of Properties. In: DiengR, Corby O (eds) 12th International Conference in Knowledge Engineering and
Knowledge Management (EKAW’ 00). Juan-Les-Pins, France. (Lecture Notes in Artificial Intelligence LNAI 1937) Springer-Verlag, Berlin, Germany, pp
97–112
•Gangemi A, Guarino N, Oltramari A (2001) Conceptual an alysis of lexical taxonomies: the case of Wordnet top-level. In: Smith B, Welty C (eds)
International Conference on Formal Ontology in Inf ormation Systems (FOIS'01). Ogunquit, Maine. ACM Press, New York, pp 3–15
Lenat DB, Guha RV (1990) Building Large
Knowledge-based Systems: Representation an d
Inference in the Cyc Project. Addison-Wes ley,
Boston, Massachusetts
Pease RA, Niles I (2002) IEEE Standard Upper Ontology : A Progress Report. The Knowledge Engineering Review 17(1):65–7 0
Sowa JF (1999) Knowledge Representation: L ogical, Philosophical, and Computational Foundations. Brooks Cole Publis hing Co., Pacific Grove,
California

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 45
Linguistic Ontologies
•WordNet (http://www.hum.uva.nl/~ewn/gwa.htm)
•EuroWordNet (http://www.hum.uva.nl/~ewn/)
•The Generalized Upper Model
(http://www.darmstadt.gmd.de/publish/komet/gen-um/newUM.html)
•The Mikrokosmos ontology (http://crl.nmsu.edu/mikro [user and password are required])
•SENSUS (http://www.isi.edu/natural-language/projects/ONTOLOGIES.html)
Bateman JA, Fabris G, Magnini B (1995) The Generalized Upper Model Know ledge Base: Organization
and Use. In: Mars N (ed) Second International Conferenc e on Building and Sharing of Very Large-Scale
Knowledge Bases (KBKS '95). University of Twente, Enschede, The Netherlands. IOS Press,
Amsterdam, The Netherlands, pp 60–72
Swartout B, Ramesh P, Knight K, Russ T (1997) Toward Dis tributed Use of Large-Scale Ontologies. In:
Farquhar A, Gruninger M, Gómez-Pérez A, Uschold M, van der Vet P (eds ) AAAI’97 Spring Symposium
on Ontological Engineering. Stanford University, California, pp 138–148
•Miller GA (1995) WordNet: a lexical database for English. Comm unications of the ACM 38(11):39–41
•Miller GA, Beckwith R, Fellbaum C, Gross D, Miller K (1990) Introduction to WordNet: An on-l ine lexical database. International Journal of Lexicography 3(4):235–244
•Vossen P (ed) (1999) EuroWordNet General Document. Vers ion 3. http://www.hum.uva.nl/ewn/
•Vossen P (ed) (1998) EuroWordNet: A Multilingual Database w ith Lexical Semantic Networks. Kluwer
Academic Publishers, Dordrecht, The Netherlands
•Mahesh K (1996) Ontology development for machine trans lation: Ideology and Methodology. Technical
Report MCCS-96-292. Computing Research Laborat ory, New Mexico State University, Las Cruces, New
Mexico. http://citeseer.nj.nec.com/m ahesh96ontology.html
•Mahesh K, Nirenburg S (1995) Semantic classification for prac tical natural language processing. In:
Schwartz RP, Kwasnik BH, Beghtol C, Smith PJ , Jacob E (eds) 6th ASIS SIG/CR Classification Research
Workshop: An Interdisciplinary Meeting. Chicago, Illinois, pp 79–94
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 46
Domain Ontologies: e-Commerce Ontologies
•The United Nations Standard Products and
Services Codes (UNSPSC)
(http://www.unspsc.org/)
•NAICS (North American Industry Classification
System)
(http://www.census.gov/epcd/www/naics.html)
•SCTG (Standard Classification of Transported
Goods)
(http://www.statcan.ca/english/Subjects/Standard/sctg/sctg-menu.htm)
•E-cl@ss
(http://www.eclass.de/)
•RosettaNet
(http://www.rosettanet.org)

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 47
Domain Ontologies: Medical Ontologies
•GALEN (http://www.opengalen.org/)
•UMLS (Unified Medical Language System)
(http://www.nih.gov/research/umls/)
•ON9 (http://saussure.irmkant.rm.cnr.it/ON9/index.html)
Rector AL, Bechhofer S, Goble CA, Horrocks I, Nowlan W A,
Solomon WD (1997) The GRAIL concept modelling language for
medical terminology. Artificial Intelligence in Medicine 9:139–1 71
Gangemi A, Pisanelli DM, Steve G (1998) Some Requireme nts
and Experiences in Engineering Terminological Ontologies
over the WWW. In: Gaines BR, Musen MA (eds) 11th
International Workshop on Kno wledge Acquisition, Modeling
and Management (KAW'98). Ba nff, Canada, SHARE10:1–20
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 48
Domain Ontologies: Engineering Ontologies
•EngMath
•PhysSys
Gruber TR, Olsen G (1994) An ontology for Engineering Mathemati cs. In: Doyle J, TorassoP,
Sandewall E (eds) Fourth International Conference on P rinciples of Knowledge
Representation and Reasoning. Bonn, Germa ny. Morgan Kaufmann Publishers, San
Francisco, California, pp 258–269
Borst WN (1997) Construction of Engineeri ng Ontologies. Centre for Telematica and
Information Technology, University of Tweent y. Enschede, The Netherlands

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 49
Domain Ontologies: Enterprise Ontologies
•Enterprise Ontology (http://www.aiai.ed.ac.uk/~entprise/enterprise/ontology.html)
•TOVE (http://www.eil.utoronto.ca/tove/toveont.html)
Uschold M, King M, Moralee S, Zorgios Y (1998) The Enterprise Ontology. The Kno wledge
Engineering Review 13(1):31–89
Fox MS (1992) The TOVE Project: A Common-sense Model of the Enterprise. In: Belli
F, Radermacher FJ (eds) Industrial and Engineering Applicat ions of Artificial
Intelligence and Expert Systems. (Lecture Notes in Artificial Intelligence LNAI 604)
Springer-Verlag, Berlin, Germany, pp 25–34
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 50
Domain Ontologies: Knowledge Management
Ontologies
•(KA)2ontologies (http://ka2portal.aifb.uni-karlsruhe.de)
•R&D projects (http://www.esperonto.net/)
Decker S, Erdmann M, Fensel D, Studer R (1999) Ontobroker: Ontology Based Access to
Distributed and Semi-Structured Information. In: Meersm an R, Tari Z, Stevens S (eds)
Semantic Issues in Multimedia Systems (DS-8), Rot orua, New Zealand. Kluwer Academic
Publisher, Boston, Massachusetts. pp 351–369

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 51
Outline
The Knowledge Sharing Initiative
Definitions of Ontologies
Modeling of Ontologies
Types of Ontologies
Libraries of Ontologies
Ontological Commitments
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 52
DAML ontology library http://www.daml.org/ontologies/
Protege ontology library http://protege.stanford.edu/ontologies.html
Ontolingua ontology library http://www.cs.umd.edu/projects/plus/SHOE/onts/index.html
WebOnto ontology library http://webonto.open.ac.uk
SHOE ontology library http://www.cs.umd.edu/projects/plus/SHOE/onts/index.html
WebODE ontology library http://webode.dia.fi.upm.es/
(KA)2ontology library http://ka2portal.aifb.uni-karlsruhe.de/
Libraries of Ontologies (I)

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 53
Libraries of Ontologies (II)
Representation Ontology: Frame- Ontology
General/Common Ontologies: Time, Units, space, ...
Generic Domain O.: components
Domain O.: body
Generic Task O.: plan
Domain Task O.: plan-surgery
Application
Domain O. : heart-deseases
Application Domain
Task O.: surgery heart
-
+
Reusability
-
+
Usability
Example library
http://delicias.dia.fi.upm.es/mirror-server/ont-serv.html
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 54
Relationship between Ontologies in the Library
Kif-Numbers Frame-Ontology
Physical-Quatities
Standard-Dimensions
Standard-Units
Chemical-Elements
Monoatomic-Ions Poliatomic-ions
Environmental Pollutants

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 55
Outline
The Knowledge Sharing Initiative
Definitions of Ontologies
Modeling of Ontologies
Types of Ontologies
Libraries of Ontologies
Ontological Commitments
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 56
Ontological Commitments
Example: What is a pipe?
Agreements to use the vocabulary in a coherent and consistent manner (Gruber)
Connection between the ontology vocabulary and the meaning of the terms of such vocabulary
• Gruber, T.; Olsen, G. An Ontology for Engineering Mathematics.
Fourth International Conference on Principles of Knowledge Representation and Reasoning.
Ed by Doyle and Torasso. Morgan Kaufmann. 1994. Also as KSL-94-18.
• Guarino, N.; Carrara, M.; Giaretta, P. Formalizing Ontological Commitments.
12th National Conference on Artificial Intelligence. AAAI-94. 1994. 560-567
An agent commits (conforms) to an ontology if it “acts” consistently with the definitions
9 definitions of the term flight from wordnet
Identification of the o ntological commitment

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 57
Ontological Commitments
©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 58
flight
A formation of
aircraft in flight
An instanceof traveling by air
A set or steps betweenone floor or
landing for him
The act of escaping physically
OC1
OC2
OC3
OC4
A flock of flying birds
Thepathfollowedby a moving
object
Passing above and beyond ordinary bounds
A scheduled trip by plane between designated
airports
OC6
OC7
OC8
OC9
A unit of the US air force smaller
than a squadron
OC5
(define-class Flight (?X)
"A journey by plane"
:axiom-def
(and (Subclass-Of Flight Travel)
(Template-Facet-Value Cardinality
flightNumber Flight 1))
:class-slots ((transportMeans "plane")))
flight

©Asunción Gómez-Pérez, M. Fernández-López, O. Corcho 59
What is an Ontology?
Shared understanding of a domain
• Formal definitions
• Informal definitions
Repository of vocabulary

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Table of Contents
1. The Role of Ontologies in the Semantic Web
2. Theoretical Foundations of Ontologies
3. Methodologies and Tools for Building Ontologies
4. Ontology Languages
5. Ontology-based Applications
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Ontological Engineering:
Methodologies and Tools
Asunción Gómez-Pérez
Mariano Fernández-López
Oscar Corcho
{asun, mfernandez, ocorcho}@fi.upm.es
Grupo de Ontologías
Laboratorio de Inteligencia Artificial
Facultad de Informática
Universidad Politécnica de Madrid
Campus de Montegancedo sn,
28660 Boadilla del Monte, Madrid, Spain

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
The Ontology Development Process
Methodologies for building ontologies
Methods and tools for
Conceptualizing
Learning ontologies
Merging
Evaluating
Evolving
Outline
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
The Framework
The world of ontologies
•To set up a life cycle
•Development process
Tools
METHODOLOGY
Item 1: It is necessary…
…….
Item 2: Since …
Define-Ontology
(Imported ontologies....)
ONTOLOGY
Can bepublic
Gómez-Pérez, A.Knowledge Sharing and Reuse.In the Handbook of Applied Expert Systems. CRC Press. 1998.

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Building ontologies
Import
Evaluate
Prune
Merge
Alignment
Identificar Diferencias
Specialize
Extend
Evolution
Export
Conceptualize
Document
Integrate
Anotate
Reasoning
Specify
¿=?
+
O1O2
O3
...
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Scheduling
Control
Quality
assurance
Management
Configuration
management
Knowledge acquisition
Evaluation
Documentation
Support
Integration
Specification Conceptualization
Formalization Implementation
Maintenance
Development oriented
Pre-development
Development
Post-development
Merging
Environment study Feasibil ity study
Use Alignment
Ontology Development Process

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Specification Conceptualization Maintenance
Development activities
Support activities
Knowledge acquisition
Evaluation
Documentation
Configuration Management
Formalization
Integration
Implementation
Management activities
Scheduling Control
Quality assurance
Ontology Life Cycle
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Inter-dependencies
Inter-dependencies refer the relationship between activities carried out when building different ontologies
O1
O3
O2
Fernández-López, M.; Gómez-Pérez, A.; Rojas M.D.
Ontology’s Crossed Life Cycle.
Lectures Notes in Artificial Intelligence Nº 1937. October 2000

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Methodologies and methods for
building ontologies from scratch
Methods and Methodologies analysed (7):
•Cyc method
•Uschold and King’s method
•Grüninger and Fox’s methodology
•KACTUS method
•METHONTOLOGY
•SENSUS method
•On-To-Knowledge methodology
•Framework for comparing
methodologies
•Methodology/method description
•Comparison of the approaches
against the framework
•Conclusions
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
METHONTOLOGY Framework
Ontology Development Process (which activities)
–Management, Development, Support
Life Cycle (Order of activities)
- Evolving Prototype.
Methodology (how to carry out)
–Specification
–Knoweldge Acquisition
–Conceptualization
–Integration
–Implementation.
–Evaluation
–Documentation
Ontology
Building
Platforms
WebODE
METHODOLOGY
Item 1: It is necessary…
…….
Item 2: Since …
Gómez-Pérez, A.Knowledge Sharing and Reuse.
In the Handbook of Applied Expert Systems. CRC Press. 1998.

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
SENSUS as a basis for a domain-specific ontology (I)
Linking Domain Specific Terms to a broad Coverage Ontology
To identify the terms in SENSUS that are relevant to a particular domain and
then prune the skeletal ontology using heuristics
B. Swartout; R. Patil; k. Knight; T. Russ. Toward Distributed Use of Large-Scale Ontologies
Ontological Engineering. AAAI-97 Spring Symposium Series. 1997. 138-148.
SENSUS SENSUS
Skeletal Ontology
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
SENSUS as a basis for a domain-specific ontology (II)
Sensus Term
Seed
Path to root
Frequent Parent
Subtree Term
1. Identify “seed” terms
2. Link seed terms to SENSUS by hand
3. Include nodes on the path to root
4. Add entire subtrees using the heuristic:
If many nodes in a subtree are relevant,
the other nodes in the subtree are relevant
METHOD
B. Swartout; R. Patil; k. Knight; T. Russ. Toward Distributed Use of Large-Scale Ontologies
Ontological Engineering. AAAI-97 Spring Symposium Series. 1997. 138-148.

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Europe – Africa
flight
Europe – America
flight
London - Liverpool
flight
Madrid - Barcelo na
flight
seed term seed term seed term seed term
international flight domestic flight
SENSUS ontology
Is hyponym
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
PROCESS
MATERIAL PROCESS
NON – DIRECTED – ACTION
MOTION – PROCESS
change of location, move
travelling
journeying
trip < journey
flight trip
Node with
many paths
OB - THING
Europe – Africa
flight
Europe – America
flight
London - Liverpool
flight
Madrid - Barcelo na
flight
seed term seed term seed term seed term
international flight domestic flight
redeye nonstop flight
other terms of the
complete subtree
OBJECT
NON – CONSCIOUS - THIN
SPATIAL TEMPORAL
SPATIAL
SPACE INTERVAL
point < location
root < point goal < point
Is hyponym

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
• Identify
problem and
opportunity
areas
•Select most
promising
focus area
and target
solution
• Requirement
specification
• Analyze
input sources
• Develop
baseline
taxonomy
• Concept
elicitation with
domain experts
• Develop base-
line taxonomy
• Conceptualize
and formalize
• Add relations
and axioms
• Identify
problem and
opportunity
areas
•Select most
promising
focus area
and target
solution
• Manage
organizational
maintenance
process
Project setting Ontology development
On-To-Knowledge
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Document
Configuration Management
Control
Quality Assurance
Multilinguism
Prune
Extend
Specialize
RDF(S) DAML+OIL OWL
RDF(S) DAML+OIL OWL
Alignment
Merge
Evolution
Methontology
Specify
Conceptualize Evaluarte Implement
DAML+OIL
RDF(S)
OWL
Integrate Maintenance Use
Import
RDF(S) DAML+OIL OWL
Evaluate

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Evaluation framework for methodologies and methods
Construction Strategy
•Life Cycle Proposal
•Strategy with respect the application
•Use of core ontologies
•Strategy to identify concepts
Proposed Ontology development process
•Project Management processes:
•Ontology development-oridented processes
•Integral Processes:
Acceptation of the methodology by other groups
Technological support to the methodology
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Summary of the ontology development process
...

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Ontology Life Cycle
Specification
Acquisition
Integration
Conceptualization
Implementation
Formalization
EVOLVING
PROTOTYPES
Gómez-Pérez, A.Knowledge Sharing and Reuse.In the Handbook of Applied Expert Systems. CRC Press. 1998.
Evaluation
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Scheduling
Control
Quality
assurance
Management
Configuration
management
Knowledge acquisition
Evaluation
Documentation
Support
Integration
Specification Conceptualization
Formalization Implementation
Maintenance
Development oriented
Pre-development
Development
Post-development
Merging
Environment study Feasibil ity study
Use Alignment
To produce an Ontology Specification Document
Content:
•Purpose
•Scenarios of use
•Possible end users
•Level of formality of the ontology
•highly informal
•semi-informal
•semi-formal
•rigorously formal
•Scope
•Granularity
Language:
•Informal
•Semi-formal
•Competency Questions

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Getting terminology using Competency Questions
Identify intuitively possible
applications and solutions
Identify Queries:
•Answers: Axioms
Formal definitions
•Questions: Terminology
Motivating
Scenarios
Informal
Competency
Questions
Formal
Terminology
Classes
Relations
Attributes
Axioms
Instances
Uschold, M.; Grüninger , M.
ONTOLOGIES: Principles, Methods and Applications.
Knowledge Engineering Review.
Vol. 11; N. 2; June 1996.
Find stories which include Person P
Identify Queries:
•Questions: Story, Person, involved-in, includes
•Answers: Story S1 includes person P
Classes: Story, Person
Relations: Involved-in, includes
Attributes: ---
Axioms
Instances: P, S1
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Getting terminology using Competency Questions
Find all the events attended by participants working on semantic web projects
Identify Queries:
Questions: Event, Researcher, Project,
work-at, attend-at, type-of-Project
Answers: ISWC, EKAW, K-cap,....
Classes: Event, International Conference,
National Conference, Workshop,
Project Meetings,
Researcher, Person, Project,
Relations: Work-at, attend-at
Attributes: Type of Project
Axioms: For all...
Instances: ISWC, EKAW, K-cap,....
Each project has a
property storing its type
•Taxonomy of Topics
•There exist a relation that connects
projects and topics
Identify Queries:
Questions: Event, Researcher, Project,
work-at, attend-at,
Semantic Web Topics, main-topics
Answers: ISWC, EKAW, K-cap,....
Classes: Event, International Conference,
National Conference, Workshop,
Project Meetings, Researcher, Person, Project,
Topics, Ontologies, mark-up languages,
semantic web services, annotations, ...
Relations: Work-at, attend-at, main-topics, topic-of
Attributes: ---
Axioms: For all ........
Instances:ISWC, EKAW, K-cap,....

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Scheduling
Control
Quality
assurance
Management
Configuration
management
Knowledge acquisition
Evaluation
Documentation
Support
Integration
Specification Conceptualization
Formalization Implementation
Maintenance
Development oriented
Pre-development
Development
Post-development
Merging
Environment study Feasibil ity study
Use Alignment
Ontology Development Process
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
METHONTOLOGY: Conceptualization
Gómez-Pérez, A.Knowledge Sharing and Reuse.In the Handbook of Applied Expert Systems. CRC Press. 1998.
It organizes and structures the knowledge acquired during the knowledge acquisition activity
using external representations that are independent of the knowledge representation
paradigms and implementation languages in which the ontology will be
formalized and implemented.
•We can use Ontology Editors for conceptualizing the Ontology
•The ontology editors transforms the conceptualization into executable code using translators

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Task 1:
Build glossary of terms
Task 2:
Build concept taxonomies
Task 4:
Build concept dictionary
Task 3:
Build “ad-hoc” binary relation diagrams
Task 9:
Describe formal axioms
Task 6:
Describe instance
attributes
Task 7:
Describe class
attributes
Task 8:
Describe
constants
Task 5:
Describe “ad-hoc”
binary relations
Task 10:
Describe rules
Task 11:
Describe instances
Tasks of the
conceptualization
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Terms glossary

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Primitives for Modelling Taxonomies
Disjoint decomposition: a set of subclasses of C that do not have common instances and do not cover C
Exhaustive-Decomposition: a set subclasses of C that cover C and may have common instances or subclasses
Partition: a set subclasses of C that cover C and do not have common instances or subclasses
Subclass-of:
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Example of a Taxonomy (I)
Flight
Iberia FlightAmerican Airlines Flight British Airways Flight
AA7462 AA2010 AA0488 IB6274 BA0066 BA0069BA0068
Disjoint-DecompositionSubclass-ofSubclass-of
Subclass-of Subclass-of
Subclass-of
Subclass-of Subclass-ofSubclass-of

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Example of a Taxonomy (II)
Flight
Domestic FlightInternational Flight
Partition
Economy Trip
Exhaustive-Decomposition
Travel Package
Business Trip Luxury Trip
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Identify Ad-hoc relations
LocationTravel
arrival Place
is Arrival Place of
is Departure Place of
departure Place

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Define a Concept Dictionary
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Define in detail Instance Attributes

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Define Class Attributes
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Define formal axioms

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Define rules
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Define Instances

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Scheduling
Control
Quality
assurance
Management
Configuration
management
Knowledge acquisition
Evaluation
Documentation
Support
Integration
Specification Conceptualization
Formalization Implementation
Maintenance
Development oriented
Pre-development
Development
Post-development
Merging
Environment study Feasibil ity study
Use Alignment
Methods for
reenginering ontologies
A possible
Conceptual
Model
New
Conceptual
Model
Reestructuring:
Evaluation
Redesign
Configuration Mangement
Reverse
Engineering
Forward
Engineering
Ontology
Implementation
New Ontology
Implementation
Methods analysed (2):
•Method por reengineering integrated in METHONTOLOGY
•Onions proposes a method for reengineering ontologies
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Ontology Libraries
DAML ontology library http://www.daml.org/ontologies/
Protege ontology library http://protege.stanford.edu/ontologies.html
Ontolingua ontology library http://ontolingua.stanford.edu/
WebOnto ontology library http://webonto.open.ac.uk
SHOE ontology library http://www.cs.umd.edu/projects/plus/SHOE/onts/index.html
WebODE ontology library http://webode.dia.fi.upm.es/
(KA)2ontology library http://ka2portal.aifb.uni-karlsruhe.de/
AKT ontology http://www.aktors.org/ontology/

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
(def-class PUBLICATION-REFERENCE (abstract-information)
"we have decided that a publication reference is an intangible, abstract information"
((has-title :type string)
(has-author :type generic-agent)
(has-date :type calendar-date)
(has-place-of-publication :type location)))
(def-class ARTICLE-REFERENCE (Publication-Reference)
((has-page-numbers :type string)
(article-of-journal :type journal)
(issue-number :type integer)
(issue-volume :type integer)))
(def-instance DKE-0169-023X (Article-Reference)
(has-title “Methodologies, Tools and Languages
for building ontologies: where is the meeting poin t?”)
(has-author Corcho Fernández-López Gómez-Pérez)
(has-date July-2003)
(has-page-numbers 23)
(article-of-journal DKE)
(issue-volume 46))
Has-date
Generic-agent
Has-author
Calendar-date
Has-place-of-publication
Location
Journal
Article-of journal
Publication-Reference
Article-Reference
Subclass-of
Subclass-of
Abstract-information
.- has-title: string
.- has-page-numbers: string
.- issue-number:integer
.- issue-volumen:integer
Has-title: “Methodologies, Tools
and Languages for building
ontologies: where is the
meeting point?”)
has-page-numbers: 23
issue-volumen: 46
DKE
Instance-of
DKE-0169-023X
Instance-of
Corcho
Fernandez-Lopez
Gómez-Pérez
Instance-of
Instance-of
Instance-of
Article-of journal
Has-author
Has-author
Has-author
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Selecting a tool for building the ontology
I must develop an ontology.
What Tool do I use to conceptualize it???
•The one(s) I like the most?
•The one(s) I know the best?
•The one(s) that import/export an ontology
from/to a given ontology implementation
language?
•The one(s) that best fit(s) my needs?

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Main criteria for selecting an ontology editor
•Which activities of the ontology development process are supported by each tool?
•What is the expressiveness of the underlying knowledge model attached to the tool?
•What kinds of user interface does the tool provide to model ontology terms?
•Does the tool provide an advanced user interface to model formal axioms or complex expressions?
•Does the tool need to be installed locally or not?
•Can it be used with a Web browser?
•Where are the ontologies stored (in databases or files)?
•Does the tool have an inference engine and querying tools?
•Which ontology languages or formats does the tool generate?
•Is the tool able to import ontologies implemented in ontology languages or in other formats?
•Is it possible to export an ontology from one tool to another without losing knowledge?
•How can ontology-based applications use ontologies developed with a tool?
•What types of consistency checking and content evaluation does the tool perform?
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Ontology development Tools
KAON from AIFB and FZI at the University of Karlsruhe http://kaon.semanticweb.org/
OilEd from University of Manchester http://oiled.man.ac.uk/
Ontolingua from KSL (Stanford University) http://www-ksl.stanford.edu
OntoSaurus from ISI (USA) http://www.isi.edu/isd/ontosaurus.html
OntoEdit from Karlsrhue Univ. http://ontoserver.aifb.unikarlsruhe.de/ontoedit/
Protégé 2000 from SMI (Stanford University) http://protege.stanford.edu/
WebOnto from KMI (Open University) http://kmi.open.ac.uk/projects/webonto/
WebODE from UPM http://webode.dia.fi.upm.es/webODE/

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Ontology Development Tools
Ontology-Based Applications
Ontology Middleware
Ontology library
Ontologies
Metrics
services
Administration
services
Ontology selection
services
Query
services
Ontology access
services
...
Ontology
editor
Ontology
merge
Ontology
translation
Semantic
Portals
Knowledge
Management
Brokers ...
Ontology
Development
Suite
Component-based
Easy integration
RAD
...
Ontology
acquisition
Ontology
browser
Ontology
evaluation
Ontology
conf. man.
Ontology
docum.
Ontology
evolution alignment
Ontology
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Example of Domain Ontology
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Comparison of Ontology building tools
Criteria:
•General Description
•Tools’ architecture: architecture, extendibility, ontology storage, back-up
•Tools’ interoperability: with tools, export/import from/to languages
•KR paradigm supported by the tool
•Methodological Support
•Tools’ inference services
•Tools’ usability
•Framework for comparing tools
•Tool description
•Comparison of the tools
against the framework
•Conclusions
•Recommendations
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Ontology Development Tools.
General description

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Software architecture
Knowledge Representation Approach
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Main Features of the editor
and Inference Engine

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Interoperability
Why low interoperability?
SIG3
EON WS
Protégé-2000
RDF(S)
RDF(S)
Ad hoc
WEbODE
Knowledge Model
RDF(S)
Protégé-2000
Knowledge Model RDF(S)
Se pierde
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Standard-Units Reverse Engineering
Ontolingua
Instance-of
Unit-Of-
Measure
Ampere
Amu
Angstrom
.
.
.
Volt
Watt
Year
Instance-of
Subclass-of
System-of-
Units Si-Unit
Instance-of
Instance-of
Ampere
Candela
Degree-Kelvin
Identity-Unit
Kilogram
Meter
Mole
Second-Of-Time
Instance-of
Standard-Units
Physical-Quantities
Reverse
Engineering

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Restructuring Standard-Units Conceptual Model
Unit-Of-
Measure
Electrical-Charge-Unit
Electrical-Current-Unit
Mass-Unit
Length-Unit
Angular-Unit
Amount-Of-Substance-Unit
Number-Of-Bits-Unit
Energy-Unit
Luminous-Intensity-Unit
Thermodyna mic-Tempe rature-Unit
Work-Unit
Frequency-Unit
Time-Unit
Resistance-Unit
Pressure-Unit
Voltage-Unit
Force-Unit
Currency-Unit
Power-Unit
Ampere
Milli-Ampere
Nano-Ampere
Pico-Ampere
Amu
Gram
Kilogram
Pound-Mass
Slug
Instance-Of
Instance-Of
Instance-Of
Instance-Of
System-Of-
Units
Si-Unit
Subclass-Of
Meter
Kilogram
Second-Of-Time
Ampere
Degree-Kelvin
Mole
Candela
Identity-Unit
.
.
.
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Scheduling
Control
Quality
assurance
Management
Configuration
management
Knowledge acquisition
Evaluation
Documentation
Support
Integration
Specification Conceptualization
Formalization Implementation
Maintenance
Development oriented
Pre-development
Development
Post-development
Merging
Environment study Feasibil ity study
Use Alignment
Methods for Cooperative Construction
Co4: Collaborative construction of consensual knowledge bases,
(KA)2method

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Scheduling
Control
Quality
assurance
Management
Configuration
management
Knowledge acquisition
Evaluation
Documentation
Support
Integration
Specification Conceptualization
Formalization Implementation
Maintenance
Development oriented
Pre-development
Development
Post-development
Merging
Environment study Feasibil ity study
Use Alignment
Ontology Learning is the set of methods
and techniques used for building an ontology from scratch,
enriching, or adapting an existing ontology in
a semi-automatic fashion using several sources.
It aims to reduce the time and the effort necessary in
the knowledge acquisition process.
•Approaches:
•Ontology learning from text
•Ontology learning from dictionary
•Ontology learning from knowledge bases
•Ontology learning from semi-structured schemata
•Ontology learning from relational schemata
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Methods
Tools
Criteria
Approaches for Ontology Learning
Main techniques
Concept learning
Linguistic patterns
NLP techniques
Machine learning techniques
Ontological techniques
Reverse engineering
Statistical approach
Text-mining
Sources
Texts
Dictionaries
Knowledge bases
Semi-structured schema
Relational Schema

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Approaches for Ontology Learning
OL from text
•18 methods
•18 tools
OL from dictionary
•3 methods
•2 tools
OL from knowledge bases
•1 method and tool
OL from semi-structured schemata
•4 methods
•1 tool
OL from relational schemata
•4 methods
For each group of methods:
•Framework for comparing OL methods
•Method description
•Comparison of each Method
against the framework
•Conclusions
•Recommendations
For each group of tools:
•Framework for comparing OL Tools
•Tool description
•Comparison of each Tool
against the framework
•Conclusions
•Recommendations
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Techniques used in different OL approaches
OL from text
•Natural Language Techniques
•Clustering techniques
•Machine learning
•Statistical aproach
OL from dictionary
•Natural Language Processing
•Statistical aproach
OL from knowledge bases
•Rules
OL from semi-structured schemata
•Graph Theory
•Machine Learning
•Pattern Recognition
•Clustering
•Ontological Techniques
OL from relational schemata
•Mapping Techniques
•Reverse Engineering

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
OL from texts:methods and techniques
Aguirre and colleagues’ method
Alfonseca and Manandhar’s method
Aussenac-Gilles and colleagues’ approach
Bachimont’s method
Faatz and Steinmetz approach
Gupta and colleagues’ approach
Hahn and colleagues’ method
Hearst’s approach
Hwang’s method
Khan and Luo’s method
Kietz and colleagues’ method
Lonsdale and colleagues’ method
Missikoff and colleagues’ method
Moldovan and Girju’s method
Nobécourt approach
Roux and colleagues’ approach
Wagner approach
Xu and colleagues’ approach
URL: Not available
URL: http://www.ii.uam.es/~ealfon
URL: http://www-lipn.univ-paris13.fr/~szulman/TERMINAE.html
URL: http://opales.ina.fr/public/
URL: Not available
URL: Not available
URL: Not available
URL: http://www.ii.uam.es/~ealfon
URL: http://www.argreenhouse.com/InfoSleuth/index.shtml
URL: Not available
URL: http://ontoserver.aifb.uni-karlsruhe.d e/texttoonto/
URL: http://www.ttt.org/salt/index.html
URL: Not available
URL: Not available
URL: Not available
URL: Not available
URL: Not available
URL: Not available
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Hearst’s method
Rigau and colleagues’ method
Jannink and Wiederhold’s approach
URL: Not available
URL: http://www.lsi.upc.es/~rigau/
URL: Not available
OL from dictionary
OL from knowledge bases
OL from semi-structured schemata
OL from relational schemata
Deitel and colleagues’ approach
Doan and colleagues approach
Papatheodorou and colleagues’ method
Volz and colleagues’ approach
URL: http://mondeca-publishing.com/s/anonymous/title11884.html
URL: Not available
URL: http://www.educanext.org/
URL: http://www.aifb.uni-karlsruhe.de/WBS/rvo/raphael-
bib.html#wonderweb-D11
Johannesson’s method
Kashyap’s method
Rubin and colleagues’ approach
Stojanovic and colleagues’ approach
URL: Not available
URL: Not available
URL: http://www.nigms.nih.gov/funding/pharmacogenetics.html
URL: http://wonderweb.semanticweb.org/publications.shtml

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Criteria to descr ibe methods and techniques
•General Description, including its main goals and scope
•General steps used for learning
•Knowledge sources used for learning
•Main techniques applied in the process
•Possibility of reusing other ontologies
•Domains in which it has been tested
•Tools associated
•Most relevant ontologies built following it
•Bibliography
•URL
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Comparison of OL methods from texts
...

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Criteria followed to describe tools
•General Description including its main goals and scope
•Main techniques used by the tool
•Method followed
•Software architecture
•Interoperability with other tools
•Inport and export facilities
•Interface facilities
•URL
•Bibliography
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
OL from texts: tools
18 tools described
ASIUM
Caméléon
Corporum-Ontobuilder
DOE
KEA
LTG
MO’K Workbench
OntoLearn
Prométhée
SOAT
SubWordNet E.P.
SVETLAN’
TDIDF
TERMINAE
TextStorm and Clouds
TextToOnto
Welkin
WOLFIE
URL: http://www.lri.fr/~faure/Demonstration/Presentation_Demo.html
URL: Not available
URL: http://ontoserver.cognit.no
URL: http://opales.ina.fr/public/
URL: http://www.nzdl.org/Kea/
URL: http://www.ltg.ed.ac.uk/%7Emikheev/workbench.html
URL: Not available
URL: Not available
URL: http://www.sciences.univ-nantes.fr/info/perso/permanents/ morin/promethee/
URL: http://www.iis.sinica.edu.tw/IASL/en/index.htm
URL: http://www.aic.nrl.navy.mil/~aha/cbr/luikm.html
URL: http://www.limsi.fr/Individu/gael/ManuscritThese/
URL: Not available
URL: http://www-lipn.univ-paris13.fr/~szulman/TERMINAE.html
URL: Not available
URL: http://ontoserver.aifb.uni-karlsruhe.d e/texttoonto/
URL: http://www.ii.uam.es/~ealfon
URL: Not available

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
OL from dictionary
OL from knowledge bases
OL from semi-structured schemata
OL from relational schemata
SEID
DOODLE
URL: http://www.lsi.upc.es/~rigau/
URL: Not available
OntoBuilder URL: http://www.cs.msstate.edu/~gmodica/Education/OntoBuilder/
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
OL from texts. Tools
...

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Conclusions about Ontology learning
•Ontology learning is a suitable process:
–to accelerate the knowledge acquisition process necessary to build an ontology
from scratch,
–to reduce the time required to enrich an existing ontology,
–to speed up the construction of ontologies to be used for different purposes in
the Semantic Web.
•integrated methods and techniques are needed for achieving the goal.
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Ontology-based annotation tools
Ontology based annotation tools
•Used for Ontology population
•Main Features
•Language for storing the annotations
•Language for handling ontologies
•Automatization degree of the annotation process
•Static/dynamic page annotation
•Text/image annotation
AEroDAML
COHSE
MnM
OntoAnnotate
SHOE Knowledge Annotator

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Scheduling
Control
Quality
assurance
Management
Configuration
management
Knowledge acquisition
Evaluation
Documentation
Support
Integration
Specification Conceptualization
Formalization Implementation
Maintenance
Development oriented
Pre-development
Development
Post-development
Merging
Environment study Feasibil ity study
Use Alignment
Criteria:
Merging at run time or design time
Techniques used:
•Hierarchical clustering techniques
•FCA
•Terminological Analysis
Methods and Methodologies analysed (5):
•ONIONS,
•PROMPT,
•FCA-Merge,
•Information-Flow-based Ontology Mapping,
•The MOMIS methodology

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
FCA-Merge
Taxonomy 1
TAXONOMIES
Root
C1.1
C1.2
C1.3 C1.4
Root
C2.1
C2.2
C2.3 Taxonomy 2
Doc. 1 Doc. 2 Doc. 1...
DOCUMENTS
Root 1 C1.1C1.2 C1.3 C1.4
Doc. 1
Doc. 2
...
Doc. n
X
X
X
X
X
X
X
X
X
X
X
X
X
Root 2 C2.1 C2.2 C2.3
Doc. 1
Doc. 2
...
Doc. n
X
X
X
X
X
X
X
X
X
X
X
X
CONTEXTS
( {doc.1,.., doc.3},
{C1.2, C2.1} )
({doc.1,.., doc. n}, {Root})
({}, {Bottom})
PRUNED LATTICE
R
MERGED ONTOL.
C1.2
Root
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
The Prompt Method
Activity 1.
To make a list
of suggested
operations
Activity 5.
To update
the list of
operations
Merge
Ontology O1 Ontology O2 Ontology O1 Ontology O2
Merge
Merge
Merge
Ontology O1 Ontology O2
Merge
Merge
Resulting ontology Resulting ontology
Activities 2 & 3. To select and to
perform next operation
Conflict (e.g. data
type missing)
Activity 4.
To find
conflicts !
It is supposed that copy is
the operation proposed for
the classes that will not be
merged

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Scheduling
Control
Quality
assurance
Management
Configuration
management
Knowledge acquisition
Evaluation
Documentation
Support
Integration
Specification Conceptualization
Formalization Implementation
Maintenance
Development oriented
Pre-development
Development
Post-development
Merging
Environment study Feasibil ity study
Use Alignment
Ontology Evolution:
The ability to manage ontology changes and their effects by creating and maintaining
different variants of the ontology [Noy and Klein, 02].
Approaches
1. METHONTOLOGY,
¾Activity during the life cycle [Fernández-López et al., 97]
¾Identification of the elements to be controlled [Gómez- Pérez and Rojas, 99]
¾Control of changes
¾Generation of status reports.
2. Types of changes [Noy and Klein, 02].
3. Klein and Fensel [Klein and Fensel, 01]:
¾Identification
¾Change specification
¾Transparent evolution
4. Stojanovic’s Process [Stojanovic et al., 02]:
Disco ve r y
Representa ti on
Semantics
of change
Implemenatation
Validat i on
Propagati on
Knowledge
offic er
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Scheduling
Control
Quality
assurance
Management
Configuration
management
Knowledge acquisition
Evaluation
Documentation
Support
Integration
Specification Conceptualization
Formalization Implementation
Maintenance
Development oriented
Pre-development
Development
Post-development
Merging
Environment study Feasibil ity study
Use Alignment
Criteria:
•Content Evaluation on taxonomies
•Criteria: consistency, completeness
Methods analysed (3):
•Gómez-Pérez approach for taxonomy evaluation
•OntoClean Method
•Ontological Constrains Manager (OCM)

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Ontology’s crossed life cycles
Version 2
Version 3
Version 1
CHEMICAL-ELEMENTS
Development
ODE
Development
STANDARD UNITS
Ontolingua Server
Evaluation of v.1
Evaluation of v.2
Evaluation of v.3
Merge + Evaluation + Configuration
management
Reengineering + Configuration management
ODE
Maintenance of Stanford version
Evaluation
CONCEPTUALIZATION
•Conceptualization
•Acquisition
•Evaluation
•Documentation
•Integration
SPECIFICATION
Phases
Intra-
dependencies
•Specification
•Acquisition
•Evaluation
•Documentation
MONATOMIC IONS
ODE
IMPLEMENTATION
•Implementation
•Acquisition
•Evaluation
•Documentation
•Integration
Maintenance
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Conclusions
•There exist stable methodologies and tools for building ontologies, but
they do not cover all the process of the ontology development process.
–Methontology (the recommended methodology to ontology development by
FIPA )
–On-To-Knowledge
•There exist methods and tools for specific tasks
–Reengineering
–Collaborative construction
–Merging
–Evaluating
–Evolution
–Ontology Learning
•Integration of specific methods in methodologies are needed
•Technological support for the whole ontology development process

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Methodologies for building ontologies (I)
Methodologies for building ontologies from the scratch.
Cyc methodology URL: http://www.cyc.com
Uschold and King URL: Not available
Grüninger and Fox URL: Not available
KACTUS methodology URL: Not available
METHONTOLOGY URL: Not available
SENSUS methodology URL: Not available
On-To-Knowledge Methodology URL: http://www.ontoknowledge.org/
Methodologies for reengineering ontologies
Method for reengineering ontologies integrated in Methontology URL: Not available
Methodologies for cooperative construction of ontologies
CO4 methodology URL: Not available
(KA)2methodology URL: Not available
Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
Ontology learning methodologies
Aussenac-Gille's and colleagues methodology URL: http://www.biomath.jussieu.fr/TIA/
Maedche and colleagues' methodology URL: Not available
Ontology merge methodologies
FCA-merge URL: Not available
PROMPT URL: Not available
ONIONS URL: Not available
Ontology evaluation methods
OntoClean: Guarino's group methodology URL: Not available
Gómez Pérez's evaluation methodology URL: Not available
Methodologies for building ontologies (II)

Ontological Engineering ©Asunción Gómez-Pérez,, M. Fernández, O. Corcho
To know more about this topics
Ontoweb WP1: D1.1.1 http://www.ontoweb.org
WP1: D1.3 Survey on Tools
WP1: D1.4 Survey on methodologies
WP1: D1.5 Survey on ontology learning
OntoRoadMap
http://babage.dia.fi.upm.es/ontoweb/wp1/OntoRoadMap/index.html
Gómez-Pérez, A.; Fernández-López, M.; Corcho, O.
Ontological Engineering. Springer Verlag. 2003

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Table of Contents
1. The Role of Ontologies in the Semantic Web
2. Theoretical Foundations of Ontologies
3. Methodologies and Tools for Building Ontologies
4. Ontology Languages
5. Ontology-based Applications
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Ontology Languages
Asunción Gómez-Pérez
Mariano Fernández-López
Oscar Corcho
{asun, mfernandez, ocorcho}@fi.upm.es
Grupo de Ontologías
Laboratorio de Inteligencia Artificial
Facultad de Informática
Universidad Politécnica de Madrid
Campus de Montegancedo sn,
28660 Boadilla del Monte, Madrid, Spain

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
References
[Bray et al, 98] Bray, T., Paoli, J., Sperberg, C. Extensible Markup Language (XML) 1.0. W3C Recommendation.
Feb 1998. http://www.w3.org/TR/REC-xml.
[Brickley et al, 99] Brickley, D., Guha, R.V. Resource Description Framework (RDF) Schema Specification. W3C
Proposed Recommendation. March, 1999. http://www.w3.org/TR/PR-rdf-schema.
[Chaudhri et al, 97] Chaudhri, V., Farquhar, A, Fikes, R., Karp, P., Rice, J. The Generic Frame Protocol 2.0. July, 1997.
[Corcho et al, 00] Corcho, O., Gómez-Pérez, A. The Languages of the Semantic Web. Submitted to IEEE Intelligent
Systems & their applications. Special Issue on Semantic Web. 2000.
[Farquhar et al, 97] Farquhar, A., Fikes, R., Rice, J. The Ontolingua Server: A Tool for Collaborative Ontology
Construction. International Journal of Human Computer Studies. 46(6). pp: 707-728.
[Genesereth et al, 92] Genesereth, M., Fikes, R. Knowledge Interchange Format. Technical Report. Computer Science
Department. Stanford University. Logic-92-1. 1992.
[Gruber, 93] Gruber, R. A translation approach to portable ontology specification. Knowledge Acquisition. #5:
199-220. 1993.
[Harmelen et al, 99] Harmelen, F., Fensel, D. Surveying notati ons for machine-processable semantics of Web sources.
Proceedings of the IJCAI’99 Workshop on Ontologies & PSMs. 1999.
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
References
[Horrocks et al, 00] Horrocks, I., Fensel, D., Harmelen, F., Decker, S., Erdmann, M, Klein, M. OIL in a Nutshell.
Proceedings of the ECAI’00 Workshop on Application of Ontologies and PSMs. Berlin. Germany.
August, 2000.
[Karp et al, 99] Karp, R., Chaudhri, V., Thomere, J. XOL: An XML-Based Ontology Exchange Language. July,
1999.
[Kent, 98] Kent, R. Conceptual Knowledge Markup Language (version 0.2). 1998. .
[Kifer et al, 95] Kifer, M., Lausen, G., Wu, J. Logical Foundations of Object-Oriented and Frame-Based Languages.
Journal of the ACM. 1995.
[Lassila et al, 99] Lassila, O., Swick, R. Resource Description Framework (RDF) Model and Syntax Specification. W3C
Recommendation. January, 99. .
[Lenat et al, 90] Lenat, D.B., Guha, R.V. Building Large Knowledge-based systems. Representation and Inference in
the Cyc Project. Addison-Wesley. Reading. Massachusetts. 1990.
[Luke et al, 00] Luke S., Heflin J. SHOE 1.01. Proposed Specification. SHOE Project. February, 2000.
[MacGregor, 91] MacGregor, R. Inside the LOOM clasifier. SIGART bulletin. #2(3):70-76. June, 1991.

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
References
[Motta, 99] Motta, E. Reusable Components for Knowledge Modelling. IOS Press. Amsterdam. 1999.
[Van Harmelen et al, 01] van Harmelen, F., Patel-Schneider, P., Horrocks, I. Reference description of the DAML+OIL
(March 2001) ontology markup language. Technical Report. March, 2001.
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Language
Ontolingua/KIF
OKBC
OCML
LOOM
FLogic
SHOE
XOL
OIL
DAML+OIL
OML/CKML
RDF(S)
OWL
KR Formalisms
Formalism
Frames
Description Logic
Semantic Nets
Conceptual Graphs
First order Logic

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Index
1. Evaluation Framework
2. Ontology Languages
2.1 Traditional languages
2.2 Ontology markup languages
3. Comparison between languages
4. Examples
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Evaluation Framework
KR
(Expressiveness)
Classes: Metaclasses
Attributes
Facets
Taxonomies
Procedures
Relations/Functions
Instances/Individuals/
Facts/Claims
Axioms
Production Rules
Inference mechanisms
(Reasoning)
Exceptions
Automatic Classifications
Inheritance
Monotonic, non-monotonic
Simple, Multiple
Execution of procedures
Constraint Checking
Reasoning with rules

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Classes and attributes (I)
Primitive
class
Non-primitive
class
OKBC, LOOM, OIL
Class
Others
Used for
classification
Different types of classes
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Classes and attributes (II)
Ontolingua
Cardinality constraints
Class Desk
Attributes (Cardinality)
Price (0,2)
Number of legs (1,1)
Made of (2,N)
FLogic
Class Desk
Attributes (Cardinality)
Price (0,N)
Number of legs (0,1)
Made of (0,N)

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Class taxonomies (I)
Taxonomies
Subclass of / Not subclass of
Partition
Disjoint Decomposition
Exhaustive Decomposition
Instance of
Has Instance
Subclass of
Mickey
Disjoint
Decomposition
Instance of
Subclass of
Superclass of
Human Mouse Cat
Cartoon
Mouse
Mammal
Partition
Partition
Number
Even Odd
Exhaustive Decomposition
Not subclass of
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Class taxonomies (II)
Disjoint Decompositions
Partitions
AmericanAirlinesFlight
AA2010AA7462
Disjoint-Decomposition
Subclass-Of
AmericanAirlinesFlight
In-Partition
Partition
AmericanAirlinesFlight
AA0488
AA2010AA7462 AA0488
AA2010AA7462 AA0488
Subclass-Of
Subclass-Of
In-Partition
In-Partition
Disjoint
a) In Ontolingua b) In LOOM
d) In OIL
FORALL flight flight:AA7462 <-> NOT flight:AA2010.
AmericanAirlinesFlight
AA2010AA7462 AA0488
Subclass-Of Subclass-Of
Subclass-Of
c) In FLogic
FORALL flight flight:AA2010 <-> NOT flight:AA0488.
FORALL flight flight:AA7462 <-> NOT flight:AA0488.

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Relations and functions (I)
Ontolingua OCML
FLogic
(def-function Pays (?room ?discount) -> ?finalPrice
"Price of the room after applying the discount"
:def (and (Room ?room)(Number ?discount))
:body
(- (Price ?room) (/ (* (Price ?room) ?discount) 100)))
Buyer[pays@Room,Number => Number].
B[pays@Prod,D -> F] ß
B:Buyer AND Prod:Room AND D:Number AND F:Number
AND Prod[price->P] AND F = P – (P * D / 100).
Not executable Executable
Executable
(define-function Pays (?room ?discount) :-> ?finalPrice
"Price of the room after applying the discount"
:def (and (Room ?room)
(Number ?discount)
(Number ?finalPrice)
(Price ?room ?price))
:lambda-body
(- ?price (/ (* ?price ?discount) 100)))
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Formal axioms (I)
Axioms
First order logic
Second order logic
Named axioms
Ontolingua LOOM FLogic
Named axiom 1
Class Dog
Embedded axiom1
Embedded axiom2
Class Dog
Embedded axiom1
Embedded axiom2
Named axiom 1
Class Dog
Embedded axiom1
Embedded axiom2
Named axiom 1
Unnamed axiom 1

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Instances (I)
<AA7462 rdf:ID="AA7462Feb082002">
<singleFare>300 US Dollars</singleFare>
<departureDate rdf:datatype=" &xsd;date">
2002-02-08
</departureDate>
<arrivalPlace rdf:resource="#Seattle"/>
</AA7462>
<INSTANCE KEY="AA7462-Feb08-2002">
<USE-ONTOLOGY ID="Travel-Ontology"
URL="http://delicias.dia.fi.upm.es/SHOE/travel.html"
VERSION="1.0" PREFIX="travel">
<CATEGORY NAME="travel.AA7462">
<RELATION NAME="travel.singleFare">
<ARG POS=1 VALUE="me">
<ARG POS=2 VALUE="300USDollars">
</RELATION>
<RELATION NAME="travel.departureDate">
<ARG POS=1 VALUE="me">
<ARG POS=2 VALUE="Feb8-2002">
</RELATION>
<RELATION NAME="travel.arrivalPlace">
<ARG POS=1 VALUE="me">
<ARG POS=2 VALUE="Seattle">
</RELATION>
</INSTANCE>
RDF(S)
SHOE
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Inference mechanisms (I)
Several definitions depending on the existence of an inference engine for the language
(define-Axiom NoTrainfromUSAtoEurope
"It is not possible to travel from the USA to Europe by train"
:= (forall (?travel)
(forall (?city1)
(forall (?city2)
(=> (and (Travel ?travel)
(arrivalPlace ?travel ?city1)
(departurePlace ?travel ?city2)
(EuropeanLocation ?city1)
(USALocation ?city2))
(not (TrainTravel ?travel))))))) (defconcept Train-Travel
:is (:and Travel
(:satisfies ?x (:for-all ?y (:for-all ?z
(:not (:and (arrivalPlace ?x ?y)
(EuropeanLocation ?y)
(departurePlace ?x ?z)
(USALocation ?z))))))))
(Valente et al, 99) Valente, Russ, MacGregor, Swartout. Building and (Re)Using a Ontology of Air
Campaign Planning. IEEE Intelligent Systems. 14. #1 (1999) 27-36
Ontolingua (no inference engine)
LOOM (with inference engine)

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Inference mechanisms (II)
Automatic classifications performed by the inference engine of a language
RDF(S)
No automatic classification
LOOM
Automatic classification
Subclass of
Furniture
ChairDesk
Subclass of
Wardrobe
Subclass of
3.leg
Chair
4-leg
Chair
Subclass of Subclass of
FurnitureChair
Desk
Wardrobe
3.leg
Chair
4-leg
Chair
Automatic
classification
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Ontology Languages (I)
Traditional ontology languages
Ontolingua/KIF
OKBC
OCML
LOOM
FLogic

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Ontology Languages (II)
Ontology markup languages
Standards & Recommendations of W3C
XML RDF(S)
Ontology specification languages
SHOE XOL
OIL
DAML+OIL
OWL
XML
RDF
OIL DAML+OIL
XOL
SHOE
(XML)
HTML
SHOE
(HTML)
RDFS
OWL
RDF(S)
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
OWL
Web Ontology Language
Built on top of RDF(S) and renaming DAML+OIL primitives
3 layers:
-OWL Lite: a small subset, easier for frame-based tools to transition to, easier reasoning
-OWL DL: description logic, decidable reasoning
-OWL Full: RDF extension, allows metaclasses
Several syntaxes:
-Abstract syntax: easier to read and write manually, closely corresponds to DL
-RDF/XML: OWL can be parsed as an RDF document, more verbose
Dean M, Schreiber G. OWL Web Ontology Language 1.0 Reference. December 2003.
XML
RDF(S)
OIL DAML+OIL
XOLSHOE
OWL

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Class taxonomy of the OWL KR ontology
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Property list of the OWL KR ontology

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
DC ⊆
R
SR ⊆

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
CR.
∀
CR.
∃
nR
≤
nR≥
nR=
DC
∩
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
DC ≡
SR ≡
Abox
1−
R
⊥
Τ
R
)(+

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
DC ∪
C
¬
}{x
⊆⊥
∩
DC
}.{xR
∃
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
OWL Example
Develop a sample ontology in the domain of people, pets, vehicles, and newspapers
- Practice with DL syntax, OWL abstract syntax and OWL RDF/XML syntax
- Understand the basic primitives of OWL Lite and OWL DL
- Understand the basic reasoning mechanisms of OWL DL
Subsumption
Automatic classification: an ontology built collaboratively
Instance classification
Detecting redundancy
Consistency checking: unsatisfiable restrictions in a Tbox (are the classes coherent?)

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Chunk 1. Formalize in DL, and then in OWL DL
1. Concept definitions:
Grass and trees must be plants. Leaves are parts of a tree but there are other parts of a tree
that are not leaves. A dog must eat bones, at least. A sheep is an animal that must only eat
grass. A giraffe is an animal that must only eat leaves. A mad cow is a cow that eats brains
that can be part of a sheep.
2. Restrictions:
Animals or part of animals are disjoint with plants or parts of plants.
3. Properties:
Eats is applied to animals. Its inverse is eaten_by.
4. Individuals:
Tom.
Flossie is a cow.
Rex is a dog and is a pet of Mick.
Fido is a dog.
Tibbs is a cat.
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Chunk 2. Formalize in DL, and then in OWL DL
1. Concept definitions:
Bicycles, buses, cars, lorries, trucks and vans are vehicles. There are several types of
companies: bus companies and haulage companies.
An elderly person must be adult. A kid is (exactly) a person who is young. A man is a person
who is male and is adult. A woman is a person who is female and is adult. A grown up is a
person who is an adult. And old lady is a person who is elderly and female. Old ladies
must have some animal as pets and all their pets are cats.
2. Restrictions:
Youngs are not adults, and adults are not youngs.
3. Properties:
Has mother and has father are subproperties of has parent.
4. Individuals:
Kevin is a person.
Fred is a person who has a pet called Tibbs.
Joe is a person who has at most one pet. He has a pet called Fido.
Minnie is a female, elderly, who has a pet called Tom.

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Chunk 3. Formalize in DL, and then in OWL DL
1. Concept definitions:
A magazine is a publication. Broadsheets and tabloids are newspapers. A quality broadsheet
is a type of broadsheet. A red top is a type of tabloid. A newspaper is a publication that must
be either a broadsheet or a tabloid.
White van mans must read only tabloids.
2. Restrictions:
Tabloids are not broadsheets, and broadsheets are not tabloids.
3. Properties:
The only things that can be read are publications.
4. Individuals:
Daily Mirror
The Guardian and The Times are broadsheets
The Sun is a tabloid
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Chunk 4. Formalize in DL, and then in OWL DL
1. Concept definitions:
A pet is a pet of something. An animal must eat something. A vegetarian is an animal
that does not eat animals nor parts of animals. Ducks, cats and tigers are animals.
An animal lover is a person who has at least three pets. A pet owner is a person who
has animal pets. A cat liker is a person who likes cats. A cat owner is a person who has
cat pets. A dog liker is a person who likes dogs. A dog owner is a person who has dog pets.
2. Restrictions:
Dogs are not cats, and cats are not dogs.
3. Properties:
Has pet is defined between persons and animals. Its inverse is is_pet_of.
4. Individuals:
Dewey, Huey, and Louie are ducks.
Fluffy is a tiger.
Walt is a person who has pets called Huey, Louie and Dewey.

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Chunk 5. Formalize in DL, and then in OWL DL
1. Concept definitions
A driver must be adult. A driver is a person who drives vehicles. A lorry driver is a person who
drives lorries. A haulage worker is who works for a haulage company or for part of
a haulage company. A haulage truck driver is a person who drives trucks ans works for part of
a haulage company. A van driver is a person who drives vans. A bus driver is a person who
drives buses. A white van man is a man who drives white things and vans.
2. Restrictions:
--
3. Properties:
The service number is an integer property with no restricted domain
4. Individuals:
Q123ABC is a van and a white thing.
The42 is a bus whose service number is 42.
Mick is a male who read Daily Mirror and drives Q123ABC.
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Chunk 1. Formalisation in DL
⊆⊥∃∪∩∃∪
∃∩∃∩≡
∀∩⊆
∀∩⊆
∃⊆
∃⊆
⊆
⊆
).().(
)..(
.
.
.
.
plantpartOfplantanimalpartOfanimal
sheeppartOfbraineatscowmadCow
leafeatsanimalgiraffe
grasseatsanimalsheep
boneeatsdog
treepartOfleaf
planttree
plantgrass

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Chunk 2. Formalisation in DL
hasParenthasFather
hasParenthasMother
adultyoung
cathasPetanimalhasPetoldLady
elderlyfemalepersonoldLady
adultpersongrownUp
adultfemalepersonwoman
adultmalepersonman
youngpersonkid
adultpersonelderly
companypanyhaulageComcompanybusCompany
vehicletruckvehiclelorryvehiclecarvehiclebusvehiclebicycle
⊆
⊆
⊆⊥∩
∀∩∃⊆
∩∩≡
∩≡
∩∩≡
∩∩≡
∩≡
∩⊆
⊆⊆
⊆⊆⊆⊆⊆
..
;
;;;;
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Chunk 3. Formalisation in DL
⊆⊥∩
∀⊆
∪∩⊆
⊆
⊆
⊆
⊆
⊆
broadsheettabloid
tabloidreadsnwhiteVanMa
tabloidbroadsheetnpublicationewspaper
tabloidredTop
broadsheetadsheetqualityBro
newspapertabloid
newspaperbroadsheet
npublicatiomagazine
.
)(

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Chunk 4. Formalisation in DL
⊆⊥∩
∃∩≡∃∩≡
∃∩≡∃∩≡
∃∩≡
≥∩≡
⊆⊆⊆
∃¬∀∩¬∀∩≡
Τ∃⊆
Τ
∃
≡
catdog
doghasPetpersondogOwnerdoglikespersondogLike
cathasPetpersoncatOwnercatlikespersoncatLike
animalhasPetpersonpetOwner
hasPetpersonranimalLove
animaltigeranimalcatanimalduck
animalpartOfeatsanimaleatsanimalvegetarian
eatsanimal
isPetOfpet
.;.
.;.
.
)3(
;;
).(..
.
.
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Chunk 5. Formalisation in DL
).(
.
.
)..(
.
)..(
.
.
vanwhiteThingdrivesmannwhiteVanMa
busdrivespersonbusDriver
vandrivespersonvanDriver
panyhaulageCompartOfworksFor
truckdrivespersonckDriverhaulageTru
panyhaulageCompartOfpanyhaulageComworksForkehaulageWor
lorrydrivespersonrlorryDrive
vehicledrivespersondriver
adultdriver
∩∃∩≡
∃∩≡
∃∩≡
∃∃
∩∃∩≡
∃∪∃≡
∃∩≡
∃∩≡
⊆

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Formalisation in OWL DL. Initial concept taxonomy
OWL Abstract syntax people+pets.abs.txt
OWL RDF/XML syntax people+pets.owl
Initial concept taxonomy Æinferencing log Æfinal concept taxonomy
4_ConceptTaxonomies.doc
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Interesting results (I). Automatic classification
And old lady is a person who is elderly and female.
Old ladies must have some animal as pets and all their pets are cats.
cathasPetanimalhasPetoldLady
elderlyfemalepersonoldLady
cathasPetpersoncatOwner
adultfemalepersonwoman
adultpersonelderly
..
.
∀∩∃⊆
∩∩≡
∃∩≡
∩∩≡
∩⊆
We obtain:
Old ladies must be women.
Every old lady must have a pet cat
Hence, every old lady must be a cat owner
catOwnerelderlywomanoldLady
∩
∩
⊆

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Interesting results (II). Instance classification
A pet owner is a person who has animal pets
Old ladies must have some animal as pets and all their pets are cats.
Has pet has domain person and range animal
Minnie is a female, elderly, who has a pet called Tom.
),(
),(
..
.
TomMinniehasPet
elderlyfemaleMinnie
animalpersonhasPet
cathasPetanimalhasPetoldLady
animalhasPetpersonpetOwner
∩∈
⊆
∀∩∃⊆
∃∩≡
We obtain:
Minnie is a person
Hence, Minnie is an old lady
Hence, Tom is a cat
catTom
oldLadyMinnie
petOwnerMinnie
animalTompersonMinnie
∈
∈
∈
∈
∈
;
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Interestin
g
results (III). Instance classification and
redundancy detection
An animal lover is a person who has at least three pets
Walt is a person who has pets called Huey, Louie and Dewey.
),(
),(
),(
)3(
DeweyWalthasPet
LouieWalthasPet
HueyWalthasPet
personWalt
hasPetpersonranimalLove
∈
≥∩
≡
We obtain:
Walt is an animal lover
Walt is a person is redundant
ranimalLoveWalt
∈

© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Interesting results (IV). Instance classification
A van is a type of vehicle
A driver must be adult
A driver is a person who drives vehicles
A white van man is a man who drives vans and white things
White van mans must read only tabloids
Q123ABC is a white thing and a van
Mick is a male who reads Daily Mirror and drives Q123ABC
)123,(
),(
123
.
).(
.
ABCQMickdrives
rDailyMirroMickreads
maleMick
vanwhiteThingABCQ
tabloidreadsnwhiteVanMa
whiteThingvandrivesmannwhiteVanMa
vehicledrivespersondriver
adultdriver
vehiclevan
∈
∩∈
∀⊆
∩∃∩≡
∃∩≡
⊆
⊆
We obtain:
Mick is an adult
Mick is a white van man
Daily Mirror is a tabloid
tabloidrDailyMirro
nwhiteVanMaMick
adultMick
∈
∈
∈
© Oscar Corcho, Mariano Fernánde-López, Asunción Gómez-Pérez
Interesting results (V). Consistency checking
Cows are vegetarian.
A vegetarian is an animal that does not eat animals nor parts of animals.
A mad cow is a cow that eats brains that can be part of a sheep
⊆⊥∃∪∩∃∪
∃∪∃∩≡
∃¬∀
∩¬∀∩≡
⊆
).().(
)..(
)).(.
.
plantpartOfplantanimalpartOfanimal
sheeppartOfbraineatscowmadCow
animalpartOfeats
animaleatsanimalvegetarian
vegetariancow
We obtain:
Mad cow is unsatisfiable

1
© Asunción Gómez-Pérez 1
Table of Contents
1. The Role of Ontologies in the Semantic Web
2. Theoretical Foundations of Ontologies
3. Methodologies and Tools for Building Ontologies
4. Ontology Languages
5. Ontology-based Applications
© Asunción Gómez-Pérez 2
Ontological Engineering:
Semantic Web Portals
Asunción Gómez-Pérez
Mariano Fernández-López
Oscar Corcho
Angel López Cima
{asun, mfernandez, ocorcho, alopez}@fi.upm.es
Grupo de Ontologías
Laboratorio de Inteligencia Artificial
Facultad de Informática
Universidad Politécnica de Madrid
Campus de Montegancedo sn,
28660 Boadilla del Monte, Madrid, Spain

2
© Asunción Gómez-Pérez 3
ODESeW
Ontology-based application that automatically generates and manages
Knowledge portals for intranets and extranets
IST-2001-34373
http://www.esperonto.net
2. Permission-based
1. Semantic Driven
3. User Oriented
4. Interoperate
5. Sincronization
ODESeW portal is one of the two main front-end applications of the WebODE workbench
ODESeW is used for building the EsperOnto Web site
© Asunción Gómez-Pérez 4
O1
O2
Oi
Oj
Portal Administrators
Different users = Different perspectives
Extranet Users
Agents
Intranet Users
Permission-based
Semantic Driven
User Oriented

3
© Asunción Gómez-Pérez 5
Ontology Workbench Status
Inference
engine
Export services
OWL
XML
Import services
OWL
XML
DAML+OIL
XCARIN
RDF(S)
Other languages OKBC
Prolog
Ontology languages
OIL
FLogic
JavaJess
XCARIN
Other languages
Ontology languages
ODE API
Cache Consistency Axiom
ODESearch
Permissions
SeW
Ontology Editor
WebODE-DB
Application Server
ODEEval
DAML+OIL
RDF(S)
WebPicker
EuroWordNet
API
Linguistic
Learning
OntoTag
ODE-Mapster
ODE Evolution Manager
Instance
learning
ODE-Mapster
© Asunción Gómez-Pérez 6
Portal Generation Process
1. Build the Ontologi es
2. Deploy ontologies into ODESeW
3. Create and Update typologies of users and users
4. Define permissions at the concept and instance level
5. Define the attribute visualization ordering
6. Select and compose the attributes for summarization purposes

4
© Asunción Gómez-Pérez 7
Ontology Modelling
RDF(S)
DAML+OIL
OWL
RDF(S)
DAML+OIL
OWL
Ontologists
© Asunción Gómez-Pérez 8
Ontology Modelling

5
© Asunción Gómez-Pérez 9
Deploy ontologies into ODESeW
Select the ontologies that will be made available on the portal for browsing
© Asunción Gómez-Pérez 10
Published
Ontologies
Personalized Browsing
Concept
Ontology
Hierarchy
Ontology implementations
(conceptual model)
Instances
Implementation
List of
Instances

6
© Asunción Gómez-Pérez 11
Semantics driven visualization (guest)
Permission Service
Workpackage
Deliverable
has associated
© Asunción Gómez-Pérez 12
Workpackage
Deliverable
has associated
Semantics driven visualization (intranet)

7
© Asunción Gómez-Pérez 13
Workpackage
Deliverable
has associated
has Q.A. partneris generated by
Organization
Semantics driven visualization