CARTOGRAPHIES OF ONTOLOGY CONCEPTS

Hatem Ben Sta

1, 2

, Lamjed Ben Said

, Khaled Ghédira

, Michel Bigand

, Jean Pierre Bourey

Unité de Recherche en Stratégies d'Optimisation des Informations et de la connaissancE (SOIE), ISG de Tunis, Université

de Tunis, 41 avenue de la Liberté, cité Bouchoucha 2000 Tunis, Tunisia

Équipe de Recherche en Génie Industriel

Ecole Centrale de Lille, BP 48, 59651 Villeneuve d’Ascq Cedex, France

Keywords: Ontology, Conceptualization, Semantic Web, Systems of knowledge Management, Ontological engineering.

Abstract: We are interested to study the state of the art of ontologies and to synthesize it. This paper makes a synthesis

of definitions, languages, ontology classifications, ontological engineering, ontological platforms and

application fields of ontologies. The objective of this study is to cover and synthesize the ontological

concepts through the proposition of a whole of cartographies related to these concepts.

1 INTRODUCTION

Historically, the ontological engineering emerged

the engineering of knowledge. This latter was for a

long time has been considered as the domain of

appraisal development in the conception of systems

for the basis of knowledge.

In spite of the fact that the engineering of

nowledge contributed to increase this appraisal

while organizing the engineer in an automated

perspective, some members of the community of the

artificial intelligence felt the need to spend to one

engineering leaning more solidly on the theoretical

and methodological foundations to improve the

conception of the intelligent systems: the ontological

engineering (OE) permits to specify the

conceptualization of a system, providing him with a

formal representation of knowledge that he must

acquire, under the shape of exploitable declarative

knowledge by an agent. Thus, the exploitation by a

mechanism of inference, of a declarative type

representation as the ontology, while following rules

of definite inference in this ontology, is the source of

the intelligence of the system.

The engineering of knowledge gave birth thus to

he ontological engineering where the ontology is

the key object on which it is necessary to bend. The

necessity of ontology and an ontological engineering

of systems to basis of knowledge have begun to be

understood and accepted by the community.

To found the ontological engineering requires

that one

define its object of it and defend the

specificity of it’s methodological. However, if no

one contests that the object of the ontological

engineering is the ontology, the explicit definition

and the precise cutoff of this concept raises some

questions all at the same time: philosophical order,

epistemological, cognitive and technique.

There are several domains of application of

ont

ologies: (1) medical domain (MENELAS), (2)

agriculture domain (AOS), (3) modeling enterprise

domain (TOVE), (4) management of a shared

enterprise knowledge memory domain (CoMMA),

etc. The most retained definition of ontology

throughout these domains was proposed by Gruber

(Gruber, 1993): “Ontology is an explicit and formal

specification of a shared conceptualization“. The

construction of ontology poses real problems

relative to knowledge engineering, conception,

maintenance and reuse. In spite of the existence of

interesting results, problems raised by the ontology

theme remain numerous and complex.

The second section of this paper presents

cartog

raphy of definitions met in the literature. The

third section introduces cartography of ontology

languages. The fourth section presents the

ontological engineering. The fifth section introduces

the classification of ontologies and cartography of

relative classification approaches. In sixth section,

we present the most relevant application domains of

ontologies. Finally, we describe some platforms

used to construct ontologies.

486

Ben Sta H., Ben Said L., Ghédira K., Bigand M. and Pierre Bourey J. (2005).

CARTOGRAPHIES OF ONTOLOGY CONCEPTS.

In Proceedings of the Seventh International Conference on Enterprise Information Systems, pages 486-494

DOI: 10.5220/0002529904860494

 SciTePress

2 CARTOGRAPHY OF

DEFINITIONS

A large number of definitions exist in the literature.

Divergences of these definitions are:

1) Whether an ontology must be formal (Noy,

2004) or no (Sowa, 2004).

2) Whether an ontology is a conceptualization

(Roche, 2004) or a specification of a

conceptualization (Gruber, 1993).

The cartography of these definitions permits,

firstly, to extract the main considered concepts and,

secondly, to position our definition in relation to

those in the literature. We extract and describe the

following main terms present in ontology definitions

overhauled in this paper:

- Conceptualization refers to an abstract model of a

phenomenon in the world, identifying the suitable

concepts relative to this phenomenon.

- Explicit means that the used concepts and their

relations are defined explicitly.

- Formal means that the ontology should be

expressed formally in order to facilitate its

translation into an interpretable language by a

machine.

- Shared means that ontology captures the

consensual knowledge which is not reserved to some

individuals, but shared by a group or a community.

In this paper we propose the following definition:

“Ontology is an explicit and formal shared abstract

view of a part of the real world. This view is

described by a whole of tools as a vocabulary

formed of concepts, relations, axioms and rules of

inference”.

Our definition is at the intersection of definitions

whose concepts are presented in the Figure 1. This

definition is inspired from terms explicitly invoked

(full arrows) or implicitly invoked (dashed line

arrows) in the corresponding references.

3 ONTOLOGY LANGUAGES

According to the approach of Corcho and Gómez-

Pérez (Corcho, 2000), languages of ontology

development are classified into three categories

(Figure 2):

- Traditional ontology languages are divided into

four categories: (1) languages relative to the logic of

the first order predicate as CycL, (2) frame based

languages as Ontolingua, F-Logic, CML and

OCML, (3) languages based on description logic as

Loom and (4) others such as Telos.

- Standard languages of the Web as XML, RDF

-Web ontology languages as OIL, DAML+OIL,

OWL, SHOE and XOL.

CARTOGRAPHIES OF ONTOLOGY CONCEPTS

487

4 ONTOLOGICAL ENGINEERING

4.1 Ontology Components

Ontology components have been identified in

(Gómez-Pérez, 1999) as:

- Concepts: called also ontology terms or ontology

classes. They correspond to the applicable

abstractions of a part of the reality (problem domain)

that have been chosen according to the ontology

objectives. According to (Gómez-Pérez, 1999) these

concepts can be classified according to several

dimensions: (1) abstraction level (concrete or

abstract), (2) atomicity (elementary or composed),

(3) reality level (real or fictitious).

- Relations: are the relevant associations existing

between the concepts present in the analyzed part of

reality. These relations include for example

associations such as sub-class-of (generalization-

specification), part-of (aggregation or composition),

associated-with, etc. These relations enable us to

analyse interrelationship of the considered concepts.

- Axioms: are the true assertions relative to the

ontology domain.

4.2 Ontology Construction

The construction process of ontology is complex.

Managing this complexity requires precise

management rules in order to control costs and risks,

and to insure the quality throughout the construction

process. Till now, there is no consensus about the

best practices to adopt during the ontology

construction process or even about technical

standards governing the process of ontology

development. However, several methodological

contributions were introduced to help ontology

construction (Bernaras, 1996), (Grüninger, 1995),

(Lenat, 1990), (Mizoguchi, 1998), (Staab, 2001),

(Uschold, 1995).

A recent survey in (Mendes, 2003) shows that

there are about thirty-three proposed methodologies

for ontologies construction. These methodological

approaches can be divided into five categories: (1)

constructing from the beginning, (2) integration or

fusion with other ontologies, (3) re-engineering, (4)

collaborative constructing (5) evaluation of built

ontologies. (Psyché, 2003) proposed a referential

frame that allows a comparative analysis of these

construction methodologies and their interactions.

Methodological construction approaches have been

in many cases associated with the evaluation process

of ontology (Friedman, 1997). Among these

approaches we can mention studies relative to the

following projects: Cyc (Mizoguchi, 1998),

Enterprise (Uschold, 1995), TOVE (Uschold, 1996),

CommonKADS and KACTUS (KACTUS Web),

METHONTOLOGY (Fernández, 1997) and

Ontolingua (Mendes, 2003).

Besides the above mentioned methodological

construction approaches, there are other domain-

specific studies that lead to some interesting

experience-based construction methodologies. It is

the case in (Uschold, 1995) and (Fox, 1997).

Moreover, part of the methodological research is

focussing particularly on a specific ontology

construction phase such as the Knowledge

representation or the conceptualization (Guarino,

1997) (Kassel, 2002).

5 ONTOLOGY

CLASSIFICATIONS

5.1 Classification Approaches

The main contributions of ontology classifications

are the following (Figure 3):

- In (Uschold, 1996) ontologies are classified

according to three criteria: 1) Formality (very casual:

expressed in a natural language; semi-casual:

expressed in a reduced form and structured of a

natural language; semi-formal: expressed positively

in a definite artificial language) expressed in natural

language; 2) Objective (communication, inter-

Ontolingua

OCML

OKBC

protocol

Figure 2: Cartography of ontology languages.

Languages concepts

F-Logic

RDFs

DAML+OIL

OIL

SHOE

DAML

OWL

XOL

Traditional

Languages

Web

Lan

Standard of

the Web

Languages

Ontologies

ICEIS 2005 - INFORMATION SYSTEMS ANALYSIS AND SPECIFICATION

488

operability, advantages of the systems engineering

(reutilisability, acquirement of knowledge,

specification)); and the 3)Topic “subject matter”

(subject like the domain (ontology domain), subject

of problem solving (tasks, methods or ontology of

problem solving), topic of languages of knowledge

representation ontology of representation or mat-

ontology).

- In (Guarino, 1995) ontologies are classified

according to two criteria: 1) detail level: for example

ontology meta-level, ontologies of reference, shared

ontologies, domain ontologies and 2) dependence

level: for example ontologies of high-level,

ontologies of tasks and ontologies of applications.

- In (Gomez-Perez, 1999) ontologies are essentially

classified according to the following criteria: 1)

ontologies of knowledge representation (formal

ontologies); 2) common/general ontologies; 3) top-

level ontologies,4) meta/generic ontologies; 5)

domain ontologies; 6) linguistic ontologies; 7) tasks

ontologies (ontology task-domain, methods

ontology, application ontology).

- In (Psyché, 2003) ontologies are classified

according to the following criteria: object of

conceptualization, detail level, completeness level,

representation formalism level.

1) According to the object of conceptualisation,

ontologies are classified by (Gómez-Perez, 1999),

(Guarino, 1997), (Mizoguchi, 1998),

(Mizoguchi,1996), (VanHeijst, 1997),

(Vanwelkenhuysen, 1994), (Vanwelkenhuysen,

1995), (Wieliinga, 1993) in the following way: a)

representation of the knowledge; b) superior / High

level; c) generic; d) domain; e) task; f) application.

2) Detail level: In relation to the level of detail used

at the time of the conceptualization of the ontology

according to the operational objective considered for

the ontology, two categories at least can be

identified: fine granularity, large granularity.

3) Completeness level: has been landed by

(Mizoguchi, 1998) and (Bachimont, 2000). As an

example, let us describe the typology of (Bachimont,

2000). This latter proposes the classification at

following three levels (semantic level, reference

level, operational level).

4) Representation formalism level: In relation to the

level of the formalism of representation of the

language used to give back the ontology operational,

(Uschold, 1996) propose a classification

understanding four categories: casual, semi-

informal, semi-formal, formal (Gómez-Pérez, 1999).

5.2 Ontology Domains

Besides the above ontology classification

approaches, it is possible to categorize ontologies

according to their application domains. Figure 4

presents a cartography existing projects concerning

different ontology application domains. There are

several important ontologies developed by the

artificial intelligence and the language engineering

communities. These ontologies cover several

domains whose features have been defined in

(Friedman, 1997) as:

- General : (1) The objective for which the ontology

was created (general or specific), (2) the size

expressed by the number of used concepts, rules and

linkers, (3) the formalism, (3) the used language and

platform of implementation (4) scientific

communications, etc. - Conception Process : How

has the ontology has been constructed? Is there any

evaluation formalism? What is the general taxonomy

of the ontology organization? - Taxonomy: What is it

the general taxonomy of ontology organization? Are

there several taxonomies or only one? What is the

composition of this taxonomy?

- Internal Structure of concepts and their relations:

Do concepts have specific internal structures? Are

there roles and properties? Are there other types of

relation between concepts? How are part-whole

relations represented?

- Axioms: Are there any explicit axioms? How are

axioms expressed?

- Mechanism of inference: How is the reasoning

made (if any)? What are some processes of going

beyond first-order logic?

- Applications: research mechanisms, user-interface,

the application in which the ontology has been used?

- Contributions: Major strengths and contributions,

weakness and araised problems.

Figure 3: Cartography of ontology classification

approaches.

Ontology

Classification

Objective

Detail Level

Formality Subjec

(Uschold, 1996)

Object

Conceptualization

(Psyché, 2003)

Detail level

(Guarino, 1997)

Completeness

Level

Representation

Formalism Level

Dependence

level

Meta/generic

Domain Tasks

Knowledge representation

(Gomez-Perez, 1999)

CARTOGRAPHIES OF ONTOLOGY CONCEPTS

489

KACTUS

(Electrical

ineerin

6 APPLICATION FIELDS OF

ONTOLOGIES

Far to be only a laboratory object, ontologies are

used today in many real application fields where

knowledge conceptualization and representation is

needed. The object of this section is to present some

applications (Figure 5) integrating ontologies and,

more precisely, the role of ontologies in knowledge

based systems and in the semantic Web.

6.1 Knowledge Based Systems

The main application of ontologies is data

management for knowledge based systems. Many

operational projects exist in different domains. We

can mention the MENELAS project (Gandon, 2002),

led in the computer services of the PUBLIC

HOSPITALS OF PARIS. Its role consists in helping

the management of medical reports and their

analysis by a system using the conceptual graph

model. Graphs are used here to represent the

inclusive medical knowledge in reports. They are

generated from texts and then stocked. The use of

adapted reasoning mechanisms permits the

interactive consultation of the knowledge. Other

projects, dedicated to the management of enterprise,

are currently in progress. The TOVE project

(Gandon, 2002) (Fox, 1997) has for goal to create a

model of enterprise expressed through an ontology,

allowing a system using this ontology to manage

knowledge related to the organization and activities

of enterprises. The CoMMA project (Gandon, 2002),

realised in the INRIA of Sophia-Antipolis, aims at

permitting the management of a shared knowledge

memory inside an enterprise. The use of ontologies

within systems offering real possibilities of

reasoning is not well developed till now. This can be

explained by the inadequate existing representation

of languages.

6.2 Semantic Web

The Web constitutes an ideal land of application of

ontologies. Without coming back to the different

definitions presented of ontologies in engineering of

knowledge, it is clear that researches on these are

essential for the realization of the semantic Web.

Indeed, on the one hand, once constructed once and

accepted by a particular community, ontology must

translate a certain explicit consensus and a certain

level of sharing that are essential to permit the

exploitation of resources of the Web by different

applications or software agents. On the other, the

formalisation, other facet of ontologies, is necessary

so that these tools can be provided of capacities of

reasoning permitting to unload the different users of

a part of their task of exploitation and combination

of resources of the Web.

Of the point of ontology view, will be crucial for

the semantic Web methods and tools contributing to:

Application domains

of ontologies

TOVE

(Enterprise

Modeling)

GUM

(Natural language

processing)

MENELAS

(Processing of hospital

documents)

GALEN

(Clinical terminology

model)

EngMath

(Engineering

mathematics)

ProPer

(Skills and

competencies of

)

CHEMICALS

(Chemical elements

and crystalline

structures

)

UMDL

(University of

Michigan

ital

Entreprise Ontology

(Entreprise

projects)

WfMC

(Workflow

Management)

Gene

(Molecular function,

biological process and

cellula

com

onent

)

Figure 4: Cartography of ontology application domains.

AOS

(Agricultural domain)

ICEIS 2005 - INFORMATION SYSTEMS ANALYSIS AND SPECIFICATION

490

- To construct ontologies, that is from primary

sources, particularly the textual corpora, or while

searching for a certain reusability. The construction

of ontologies from the textual corpus analysis is a

domain in strong evolution where a certain number

of methodologies and tools are tested by a very

active community. The question of the reusability

that caused long proceedings in the community

Engineering of knowledge permitted to progress

toward the research of some genericity but remains a

major stake for the semantic Web;

- To manage the access to ontologies, their

evolution, with management of versions, and their

fusion. Ontologies are often rich of several thousand

of concepts and remain then directly accessible by

their inventor. Their access by users, same

professionals, requires the management of the tie

between concepts of ontologies and terms of the

natural language that it is for a simple understanding

or for the indexing and the intended request

construction to tasks of research of information.

Solution implementations until now pass by

methodologies separating explicitly terms and

concepts of a domain and tools of visualization and

navigation searching for the conceptual proximities

in terms of a domain and permitting to fear the

complexity of this domain intuitively;

- To insure the interoperability of ontologies while

managing the heterogeneities of representation and

the semantic heterogeneities. These latter are the

hardest to manage and they will require some

conjoined reflections to the problematic of the

ontology accessibility.

Some projects have been achieved or under

realization using concepts of the Semantic Web.

Among these projects: PICSEL (LRI), Xyléme

(INRIA-Xyleme, 2000), CoMMA (Gandon, 2002),

ACACIA (INRIA, 2000), ESCRIRE (INRIALPES),

COMMONV (Trichet, 2002), GEMO (INRIA-

GEMO).

Web Semantic

GEMO (INRIA-GEMO)

CoMMA Project

(Gandon, 2002)

PICSEL (LRI)

MENELAS Project Xyléme (INRIA-Xyleme,

2000)

(Gandon, 2002) IA (INIRA, 2000) ACAC

CoMMA (Gandon, 2002)

TOVE Project ESCRIRE

(Fox, 1997), (Gandon, 2002) (INRIALPES

COMMONCV

(Trichet, 2002)

Knowledge Based Systems

Applications

Fields Of

Ontologies

Figure 5: Cartography of some Applications Fields of

Ontologies

7 SOME PLATFORMS FOR

ONTOLOGY CONSTRUCTION

In this section we describe some platforms used for

ontology construction.

There exist numerous ontological platforms using

varied formalisms and offering different

functionalities. These platforms offer supports for

the construction process of ontology. However they

do not offer a great help concerning the

conceptualization. We describe here some of the

most important ontological platforms:

- Ontolingua: Ontolingua is a set of developed tools

written in Common Lisp. It is used to analyze and to

transform ontologies that have been developed in the

beginning of 20th century at the Knowledge Systems

Laboratory of the Stanford University of (Farquhar,

1997). Ontolingua is composed of a server and a

representation language. The server memorizes a set

of constructed ontologies in order to assist the

development of new ontologies (Duineveld, 1999).

- WebOnto: WebOnto has been developed by the

Knowledge Media Institute of the Open University

(Onto Web). WebOnto has been conceived in order

to support collaborative research, creation and

display of ontologies. WebOnto provides a user

interface that displays ontological expressions. It

CARTOGRAPHIES OF ONTOLOGY CONCEPTS

491

provides also an ontological tool called Tadzebao

which is able to support the synchronous and

asynchronous communication between ontologies. -

Enterprise Toolsets: It is an agent based platform

that integrates several plug-and-play tools. The main

components of Enterprise Toolset are: a procedure

onstructor used to capture models of a process,

agent's Toolkit used to support the development of

agents, administrator of tasks used for the

integration and the visualization of a process, and a

communication tool (Uschold, 1998).

- KACTUS / VOID Toolkit: KACTUS is an

interactive environment to search, publish and

manage ontologies. The VOID tool offers an

experimental framework for examining and

analysing theoretical ontology concepts. It permits

also the organisation of developed ontology libraries

and the transformation of different ontology

formalisms. The KAKTUS toolkit allows also

executing a set practical operation such as searching,

publishing and interrogating ontologies developed

using different formalisms. In order to support the

reuse of ontologies, the toolkit can manipulate

several formalisms of ontologies (CML, EXPRESS

and Ontolingua) and can manipulate transformations

between these formalisms. Other platforms are

mentioned in (Duineveld, 1999).

8 CONCLUSION

The notion of ontology stems from the discipline of

Philosophy. It has evolved to its current meaning in

the context of Computer and Information Science

where it refers to a designed artefact which formally

represents agreed semantics in a computer resource.

Ontologies are becoming increasingly important in

various fields. They are used to describe diverse

domains in order to treat information automatically.

In this paper we tried to present some concepts

bound to ontologies but from a new approach: the

cartography. It will allow readers to situate their

ontological needs while referring to the suitable

concepts.

This paper has permitted to browse in a rather

exhaustive way the state of the art relative to

ontologies. Thus, we introduced several

cartographies relative to definitions, languages,

classification approaches and application domains.

This ontological survey was supported by a

progressing study that we are leading. In fact, we

have finished the conceptualization of an ontology

dedicated to the management of a project memory

(Bigand, 2004). For the following of our researches,

the development of this ontology is in progress and

we intend to experiment it the case of French and

Tunisian companies.

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