practical difficulties in the construction of ontologies and different

Practical difficulties in the construction of ontologies and different kinds of knowledge representation in the Semantic Web

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What is a knowledge representation in the digital world?

• It is a surrogatesurrogate, a substitute for the thing itself, used to enable an entity to determine consequences by thinking rather than acting

• It is a set of ontological commitmentsontological commitments, to answer in what terms in what terms should we think about a domain should we think about a domain

• It is a fragmentary theory of intelligent reasoningfragmentary theory of intelligent reasoning, expressed in terms of three components: a. the representation's fundamental conception of intelligent reasoning; b. the set of inferences the representation sanctions; c. the set of inferences it recommends

• It is a medium of human expression human expression, a language in which we say things about the world

• It is a medium for pragmatically efficient computation efficient computation Ref: Davis, R., Shrobe, H., and Szolovits, P. What is a Knowledge Representation? AI Magazine, 14(1):17-33, 1993.

http://groups.csail.mit.edu/medg/ftp/psz/k-rep.html

What is a knowledge representation in the Semantic Web ?

•Description of content and formal aspects of web resourcesweb resources

•This description is expressed by a metadata structure in a markup language: RDF, Resource Description Format

• In a way understandable by machines

There is not only one structure of knowledge representation. There are different structures and elements that belong to different languages

So Semantic Web knowledge representation formalisms consist of different kinds of logics in different kinds of

representation formats

1. Resourcedescription:

data andmetadata

2. Form andContent:human

classificationand

catalogation

3. computersinteractivity:middleware

CDU, ISBD,Dewey,Thesauri

© Mela Bosch2006

RDF - SKOS

Controlledlanguages andcatalogationstandards

Artificial languagesOWL(Ontologies)

HTML, XML. RDF,DC

Descriptionlogic

Indexinglogic

Objectoriented

logic

Levels Conceptual toolsApplication tools Logic tools

Web resourcesmarkup lenguages

Declarative

Knowledge

representation

Semantic web: logics, tools and levels of KnowledgeRepresentation

Domain experts: know-how in the field to beontologically modeled


data andmetadata

Semantic web: logics, tools and levels of Knowledge Representation

HTML, XML. RDF,DC

Descriptionlogic

Declarative

Knowledge

representation



Level 1

© Mela Bosch2006

First level of knowledge representation

Methodologies for intelligent systems

Procedural knowledge integrated in the program. AdvantagesAdvantages : a great specificity: algorithms for each case.

DisadvantagesDisadvantages : lack of versatility, difficulty to modify.

Declarative knowledge representation is independent of the computational processes.

AdvantagesAdvantages: flexible and with hard logical base. DisadvantagesDisadvantages: great level of abstraction, difficulty to maintain a

consistent logic.

Semantic web: Semantic web: declarative knowledge declarative knowledge representationrepresentation using metadata using metadata

The metadata is expressed in

•controlled language in which the syntax is independentsyntax is independent of system procedures and the terminologyterminology is adequate to application domainapplication domain

•well defined semantics, very expressive

Description logic also known as terminological logicDescription logic also known as terminological logic

Markup languageMarkup language: : procedimental procedimental specifity and declarative abstraction specifity and declarative abstraction

Markup language: <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"</rdf:RDF>


data andmetadata


classificationand

catalogation


Semantic web: logics, tools and levels of Knowledge Representation

© Mela Bosch2006


HTML, XML. RDF,DC

Descriptionlogic

Indexinglogic



Declarative

Knowledge

representation

Second level of knowledge representation: well known well known

for library science for library science professionals professionals

Second level of knowledge representation: another type of logic

TThe logic of indexation for cataloguing and he logic of indexation for cataloguing and classifyclassifyinging

But it is not the same to index But it is not the same to index an an object object and to index something and to index something

which is the which is the reference to that reference to that objectobject

Semantic web indexes resources web

Reference items of the digital objects: authoring, date, etc. Objects are described through aObjects are described through ann ontologyontology

That is to say, objectsobjects, not material objects, but digital digital

objects.objects.

Similar description to library science classification systems

Others aspects of the digital objects such as: attributes, behavior, relationships and cardinality are expressed by another logicanother logic


data andmetadata


classificationand

catalogation

3. computersinteractivity:middleware


© Mela Bosch2006

RDF - SKOS


Artificial languagesOWL(Ontologies)

HTML, XML. RDF,DC

Descriptionlogic

Indexinglogic

Objectoriented

logic



Declarative

Knowledge

representation

Semantic web: logics, tools and levels of KnowledgeRepresentation

has become the mainstream has become the mainstream technique in the technique in the software software

industryindustry

Opposed to a traditional Opposed to a traditional viewview in which a program

may be seen as a collection of functionsfunctions,, or

a list oflist of instructions instructions given to the computer.

OObject-oriented point of view:bject-oriented point of view: Computer program: a set Computer program: a set of interacting individual of interacting individual

units, or units, or objectsobjects, , that manage their own that manage their own state and operationsstate and operations

Third level of knowledge representation: Object oriented modeling paradigm

AdvantagesAdvantages Intuitive: direct mapping from the Intuitive: direct mapping from the real-world real-world

Third level of knowledge representation: Object oriented logic to:

DisadvantagesDisadvantages Difficult to build large coherent and complete Difficult to build large coherent and complete representationrepresentation Hand crafting Hand crafting

object hierarchyobject hierarchy

•make domain assumptions explicitmake domain assumptions explicit

•separate domain knowledge from the separate domain knowledge from the operational knowledgeoperational knowledge

•uusing terms for representing concepts that are sing terms for representing concepts that are an abstraction of objects’ main propertiesan abstraction of objects’ main properties

Object oriented logic: Fundamental concepts

ClassClass — the unit of definition of data and behavior — the unit of definition of data and behavior for some kind-of-thing. for some kind-of-thing. Object Object — an instance of a class, an object — an instance of a class, an object Encapsulation Encapsulation — a type of privacy applied to the — a type of privacy applied to the data, ensures that an object can be changed only data, ensures that an object can be changed only through established channels through established channels Inheritance Inheritance — provides a way to define a (sub)class — provides a way to define a (sub)class as a specialization or subtype or extension of a as a specialization or subtype or extension of a more general class more general class Abstraction Abstraction — the ability to ignore the details of an — the ability to ignore the details of an object's (sub)class and work at a more generic object's (sub)class and work at a more generic level when appropriatelevel when appropriatePolymorphism Polymorphism — polymorphism is behavior that — polymorphism is behavior that varies depending on the class in which the varies depending on the class in which the behavior is invoked, that is, two or more classes behavior is invoked, that is, two or more classes can react can react differentlydifferently to the to the same messagesame message. . Ref: wikipedia.orgRef: wikipedia.org

Object-Oriented Modeling and Ontology Engineering

There are There are stepssteps in commonin common::•an iterative an iterative processprocess•Defining concepts Defining concepts in the domain in the domain (classes)(classes)•Arranging the Arranging the concepts in a concepts in a hierarchy (subclass-hierarchy (subclass-superclass hierarchy)superclass hierarchy)•Defining which Defining which attributes and attributes and properties classes properties classes can have and can have and constraints on their constraints on their valuesvalues•Defining Defining individuals and filling individuals and filling in slot valuesin slot values

“Jaguar“

Concept

Abstract Class: Car

Subclass:Jaguar, luxe

Abstract Class: animal

subclass:Jaguar, spots

Class: feline

Different: attributes, properties and values

Object-Oriented Modeling and Ontology Engineering

TThe same logic but:he same logic but:An ontologyAn ontology•reflects the structure of the reflects the structure of the worldworld•is often about structure of is often about structure of conceptsconcepts•actual actual physical representationphysical representation is is not an issuenot an issue An OAn Object bject OOrientedriented class structure class structure•reflects the structure of the reflects the structure of the datadata•is usually about is usually about behaviorbehavior •describes the describes the physical representationphysical representation of dataof data (long int, char, etc.) (long int, char, etc.) ((RefRef: http://protege.stanford.edu): http://protege.stanford.edu)

.

TTop-down: define the most general concepts first and op-down: define the most general concepts first and then then specialize themspecialize them

BBottom-up: define the most specific concepts and ottom-up: define the most specific concepts and then organize then organize them in more general classesthem in more general classes

CCombination: define the more salient concepts first ombination: define the more salient concepts first and then and then generalize and specialize themgeneralize and specialize them

DDocument classification ocument classification ssystemsystems •ConceptsConcepts

•parts of the conceptsparts of the concepts

•How they relate to other How they relate to other conceptsconcepts

Ref: http://www.ncess.ac.uk/insight/tutorials/datagrids/data_sh/ontologies/

Object Oriented logic for construction of ontologies

and Object Oriented software: the same the same methodological premises as document methodological premises as document

classification systemsclassification systems

Object Oriented logic and document classification

• conceptsconcepts• parts of the conceptsparts of the concepts• How they relate to other How they relate to other

conceptsconcepts• properties (attributes): properties (attributes):

contain primitive values contain primitive values (strings, numbers)(strings, numbers)

• complex properties: contain complex properties: contain (or point to) other objects(or point to) other objects


Hybrid knowledge representation :supports a rich

knowledge model with different kinds of

representation at the same time

http://www.ncess.ac.uk/insight/tutorials/datagrids/data_sh/ontologies/

. Class structure usually constitute a taxonomic

hierarchy:

Class Subclass

:

Examples from: Protégé: a graphical ontology- development tool, open-source and freely available: (http://protege.stanford.edu)

Hierarchy: French wines

Hierarchy: Pizza

Slots in a class definition describe attributes of instances of the class and relations to other instances: Each wine will have color, sugar content, producer, etc. Types of properties•“intrinsic” properties: flavor and color of wine•“extrinsic” properties: name and price of wine•parts: ingredients in a dish•relations to other objects: producer of wine (winery)

TerminologyClass=conceptInstance= objectSlot= property Facet=valuesSlot cardinality = the number of values a slot has (common facet)Slot value type = the type of values a slot has (common facet): string, num, booleanMinimum and maximum value = a range of values for a numeric slot (common facet)Default value = the value a slot has unless explicitly specified otherwise(common facet)

Class instance creation

Examples from: http://protege.stanford.edu/publications/ontology_development/ontology101.html

Superclass Wine

Subclass French wine

A subclass inheritsinherits all the slots from the superclass, but with a list of own allowed values


Common problems: Is a Margherita Pizza a Vegetarian Pizza?

A class can have more than one superclassA subclass inherits slots and facet restrictions from all the parentsDifferent systems resolve conflicts differently

Ref: http://www.co-ode.org

Errors in understanding common logical constructs

Ref: http://www.co-ode.org

Common problems: Is a Margherita Pizza a Vegetarian Pizza?

Different subclasses

Closure Axiom: onlyClosure Axiom: only

Correct hierarchy

Conclusion•Semantic Web knowledge representation formalisms consist of different kinds of logics in different kinds of representation formats•there are many aspects involved such as description logic, classification systems, object oriented data structure and markup languages

“Every ontology is a treaty – a social agreement – among people with some common motive in sharing”

Gruber says:

Ref: http://www.sigsemis.org/newsletter/october2004/tom_gruber_interview_sigsemis

CCollaborative ollaborative approachapproach to construction of to construction of ontologiesontologies

•Communication between collaborators from different disciplines is difficult

•Ontology Building, maintenance and reuse: time consuming activities, cost analysis is complex

Domain experts: know-how in the field to beontologically modeled

Web developers:markup language:RDF, OWL, SKOS

Library Science andTerminology:

controlled languagesand classification

schemes

Software Engineering:Object Oriented Design

Collaborativeapproach to

construction ofontologies

Conclusion

•Methodologies for collaboratively creating and managing shared information: Modeling semantically heterogeneous data sources and services, Representing and reasoning with ontologies and mappings between ontologies•Semantic community support systems and collaboration applications: Groupware tools for supporting collaborative ontology design, Semantic Wikis, semantic blogging, •Case studies and experience reports on semantics-aware collaborative applications •Cost Estimation Models for Ontology Engineering

References

•Hodgson, Ralph; Keller, Paul. Collaborative Ontology-Based Systems. Innovator Perspectives and Demonstrations of New Open Standards and Technologies in Support of Ontology Engineered Solutions. TopQuadrant and NASA Ames. Collaborative Expedition Workshop #38. February 22, 2005 at NSF Semantic Conflict, Mapping, and Enablement: Making Commitments Together. http://www.topquadrant.com/documents/talks/TQ%20Ontology-Based%20Collaborative%20Environments%20(v4).pdfBased%20Collaborative%20Environments%20(v4).pdf • Díaz, Alicia, Baldo, G. CO-Protégé: A Groupware Tool for Supporting Collaborative Ontology Design with Divergence. Lifia, Fac. Informática- UNLP, La Plata, Argentina- Loria, Campus Scientifique, Vandœuvre-lès-Nancy cedex, France. http://protege.stanford.edu/conference/2005/slides/6.2_A.Diaz_Co-Protege_slices_and_flyer.pdf; http://protege.stanford.edu/conference/2005/submissions/abstracts/accepted-abstract-diaz.pdf •Gamper, Johann, Nejdl, Wolfgang; Wolpers, Martin. Combining Ontologies and Terminologies in Information Systems. European Academy Bolzano/Bozen, Scientific Area ``Language and Law''Bozen, Italy - Institut für Rechnergestützte Wissensverarbeitung University of Hannover, Germany. http://www.kbs.uni-hannover.de/Arbeiten/Publikationen/1999/tke99/

•W3C Working Draft 07 March 2002, Requirements for a Web Ontology Language. Latest version:http://www.w3.org/TR/webont-req/

•Institut für Informatik, Freie Universität Berlin. Ontology Engineering Cost Estimation with ONTOCOM. http://ontocom.ag-nbi.de//index.html

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Examples of ontologies:ProtegeOntologiesLibraryhttp://protege.cim3.net/cgi-bin/wiki.pl?ProtegeOntologiesLibrary

practical difficulties in the construction of ontologies and different

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