CARTOGRAPHIES OF ONTOLOGY CONCEPTS
Hatem Ben Sta
1, 2
, Lamjed Ben Said
1
, Khaled Ghédira
1
, Michel Bigand
2
, Jean Pierre Bourey
2
1
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
2
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
k
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
t
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
Copyright
c
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
g
ua
g
es
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
t
(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
En
g
ineerin
g)
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
p
eo
p
le
)
CHEMICALS
(Chemical elements
and crystalline
structures
UMDL
(University of
Michigan
Di
g
ital
Entreprise Ontology
(Entreprise
projects)
WfMC
(Workflow
Management)
Gene
(Molecular function,
biological process and
cellula
r
com
p
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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