From Information Society to Knowledge Society:The Ontology Issue

Christophe Roche

University of Savoy - LGIS - Campus Scientifique73 3 76 Le Bourget du Lac cedex - France

roche@univ-savoie.frhttp://ontology, univ-savoie.fr

Abstract. Information society, virtual enterprise, e-business rely more and more on communication and knowledge sharingbetween heterogeneous actors. But, no communication is possible, and all the more so no co-operation or collaboration, ifthose actors do not share the same or at least a compatible meaning for the terms they use. Ontology7, understood as anagreed vocabulary of common terms and meanings, is a solution to that problem. Nevertheless, although there is quite a lotof experience in using ontologies, several barriers remain which stand against a real use of ontology. As a matter of fact, itis very difficult to build, reuse and share ontologies. We claim that the ontology problem requires a multidisciplinaryapproach based on sound epistemological, logical and linguistic principles. This article presents the Ontological KnowledgeStation (OK Station®), a software environment for building and using ontologies which relies on such principles. The OKStation is currently being used in several industrial applications.

Keywords: Communication and Knowledge Sharing, Ontology.

1 INTRODUCTION: FROM INFORMATION TO KNOWLEDGE

The increasingly global economy, the explosive growth of the "world" in the "world wide web", the constantlymoving market characterised by short product life cycles and increased demand for flexibility as well as the extensiveuse of information, have led to a new vision of the society : the Information Society. A new socio-economic systemwhich relies more and more on circulation, sharing and exchanging information whose repercussions modify daily life,culture, economy and industry.

Concurrent Engineering based on the co-operation and collaboration of multi-disciplinary people, is a goodexample [1]. Collaborators, from design to manufacturing, have to share and exchange information: clientrequirements, business information, simulation results, workshop loads, supplier delays... as they have to co-ordinatetheir decisions in order to react as quickly as possible to changes: "concurrent engineering is a knowledge- andcommunication-intensive process" [2], [3].

The Information Society (virtual enterprise, e-business, etc.) relies on communication between interacting andheterogeneous actors : people, organisations and even software systems (let us notice that software systems oftenaggravate the problem of communication by isolating information and using their own protocols [4]. But everybodyspeaks his own language with his own terms and meanings and no communication is possible, and all the more so noco-operation or collaboration, if one can not understand each other: the Information Society is the new Tower ofBabel.

Communication between people, organisations and software systems is difficult due to the fact that each of theseactors speaks a different language. To address this problem, we need a common communication language that agentscan read and understand. Using a single, normalised language like KQML (Knowledge Query ManipulationLanguage) [5] or ACL (Agent Communication Language by FIPA [6]), can reduce the gap of misunderstanding byusing a same syntax. But, although such languages give some useful indications about the pragmatic content of themessage, the semantic problem has still to be addressed. As a matter of fact, two entities can communicate only if

CP627, Computing Anticipatory Systems: CASYS 2001 —Fifth International Conference, edited by D. M. Dubois© 2002 American Institute of Physics 0-7354-0081-4/02/$ 19.00

575

they agree upon on the meaning of the terms they use, and the problem becomes more complex when one takes intoaccount multi-linguality. Let us notice that communication cannot be reduced to only exchanging data but must takeinto account the exchange of knowledge. Co-workers in an enterprise work at their own levels, using their ownknowledge and engineering models. Furthermore, the software tools extensively used in information societies,requiring specific and dedicated representations, are more concurrent than collaborative.

Communication, knowledge sharing and exchanging, are the new economic stakes of the Information Societywhich must move up to the Knowledge Society. The way to address this problem is to define a shared understanding.Agreement must be achieved about the shared knowledge used as a communication medium among people andsoftware tools. Ontology, understood as an agreed vocabulary of common terms and meanings shared by a group ofpeople, is a solution to that problem.

2 ONTOLOGY: WHAT IS IT ? WHAT IS IT FOR ?

When the main goal of an ontology is to normalise the meaning of terms, the term "ontology" itself is not clearlydefined: "although ontology is currently a fashionable term, no agreement exists on the exact meaning of the term"[7], [8] and "seems to generate a lot of controversy in discussion about AT' [9], In fact, ontologies found applicabilityin many domains of application in knowledge and software engineering, and each of them gives its own definition. Letus see some examples from a general, and famous, definition from Gruber: "An ontology is a specification of aconceptualisation" [9] to a more dedicated one: "The main purpose of an ontology is to enable communicationbetween computer systems in a way that is independent of the individual system technologies, informationarchitectures and application domain." [10]. Nevertheless, although an ontology may take a variety of forms, it willinclude a vocabulary of terms and some specification of their meaning [10], [11], [12], [13]. So, in the following, wewill consider that: "an ontology is a collection of agreements upon a vocabulary of common terms and meanings insome domains. The term's meanings are structured into a system whose properties must be guarantees of ontologycommitment, reuse and sharing".

But, what is important is what an ontology is for: terminology, communication, inter-operability, systemsengineering, etc. [11]. According to the objectives, the required properties will be different as well as therepresentation language.

3 THE OK MODEL: A MULTI-DISCIPLINARY APPROACH

Our objective is to build consensual and coherent corporate ontologies which can be shared and reused. Such anobjective is difficult to reach, even if the application domain and the representation language are the same. Forexample, how can we combine the definitions coming from the two enterprise ontologies: TOVE [14] and EnterpriseOntology [15] ?

We claim that such a problem requires clear and sound principles based on a multidisciplinary approach from:- linguistics, as we use words to communicate, and more especially from lexical semantics and structuralism,- epistemology, since we want to represent conceptual knowledge, and- logic in order to guarantee some coherence and to allow inference mechanisms.

The specific-difference theory fulfils all these criteria.note: in the following, we shall focus on the definition of the meaning of terms (words) which refer to conceptualknowledge (e.g. concepts used in a corporate knowledge as 'turning', 'milling', 'stamping'... in a 'mechanicalmachining' ontology).

3.1 Concept

The concept is the meaning of term. It is defined by 'specific differentiation'. It means that a concept is definedfrom a previously existing concept adding a new difference which is then called the 'specific difference' of the newlycreated concept. Such a recursive definition tightly links concepts and introduces an important new notion: thedifference. The "specific difference" relationship between two concepts is more than the classical "is-a" relationshipas it introduces constraints between the sibling concepts and a logical formalisation. Let us notice that the meaning ofa concept can also be defined by the set of its differences.

576

3.2 Difference

Differences are the elementary units from which the meaning of a concept is built. This means that the differenceshave no meaning in themselves. Unlike an attribute it cannot be removed from the definition of an object withoutchanging its nature; nor can it be valued. For example, for the 'Turning5 concept, 'piece rotation' is a differencewhereas 'rotation speed' is an attribute.

A difference is an unit that builds meanings and divides concepts into two different sets. In fact, adding adifference to an existing concept creates two new ones, the first to which it belongs and the second which will neverbe able to own it. That difference is called the "specific difference" of the former new concept. The fact that adifference cannot belong to a concept is itself a specific difference which can be named. This is the reason whydifferences are defined by couples of opposite differences, like 'metal preservation' and 'no metal preservation' or'material removal' and 'material deposit' (the language is differential). Thus, owning a difference for a conceptimplies it will never contain the opposite difference, nor the concepts it could subsume. Such a property will be veryuseful for building and using ontologies. It is a guarantee of the coherence of the ontology .

3.3 Properties

The definition of concepts by specific differentiation offers several good properties which explain such a choice:- consensual definitions;- the agreement problem is reduced to the sole problem of agreement on the difference names and not on the

concept names (n couples of differences allow to define 2n concept names);- no multiple hierarchy and therefore no problem of inheritance;- sound logical properties.

4 THE OK STATION

The OK Station is a software environment dedicated to building and using knowledge bases. It provides to declaredor anonymous users a set of features gathered into dedicated modules (see figure 1). Let us see the two main modulesdedicated to building ontologies: the linguistic module and the ontology module.

'< flits flrittt iieat^ OlCi 1

[•'''•^^^f.^i^H&ys^''^^^^.':'-

•^:lwi»^^^^ :

' • • ' ' : llliHBiiil • • • • • lliiiSliBll!- • . ' :

• Itocl^ - JM y^f v

li

-.upas!A

FIGURE 1. The login window and the user launcher.

577

4.1 The Linguistic Module

The linguistic module provides the user with several tools in order to automatically extract from texts differentlexicons, e.g. noun lexicon, unknown-name lexicon and expression lexicon. This module is a means to producepotential terms for the ontology, especially the unknown-names, which do not belong to the English dictionary, andthe expressions which are in general linked to a technical skill.

4.2 The Ontology Module

The ontology module is the core of the system. It allows a user to manage his own ontologies based with the helpof an ontology launcher created and associated to him when he is logged (see figure 2 below).

Ontology Launcher for user: Roche

DangerousThings.ontentiles.ontInteqriteCT.ont

metaOntology.ontPrecedes d'elaboration.rjPsanofi.ontusinages.ont

ontology H translations

| manager

define query

inspect lexic

l-'^LQK B-'

FIGURE 2. The ontology launcher.

An ontology launcher provides two kinds of tools. The first one (see the menus 'ontology' and 'translations'under the 5OK Ontology List' pane of the previous figure) allows an user to handle his ontologies as files: creation,editing, printing, deleting. He can also translate his ontologies into an interchange format. As a matter of fact, one ofthe goals of ontologies is to provide knowledge sharing and exchange, so it is necessary to produce ontologieswritten in a more common formalism than LOK language. It is the reason why a LOK file (see the next paragraph)can be translated into a KIF file, for Knowledge Interchange Format [16], or into a conceptual graph format file.These files are bigger and less comprehensive than the LOK one due to the fact that these formalisms are moregeneral than LOK and so it is necessary to translate the LOK semantics into them.

But the main goal of the launcher is to manage the ontologies themselves, i.e. to manage the terms and theirmeanings. This is done through the managers associated with ontologies when they are opened (see the 'OK ManagerList' pane of figure 6). Opening an ontology means to run the LOK instruction File in order to obtain a computationalmodel of the ontology handled by a manager. From his launcher, the user can apply to the selected manager a set oftools: graphical editor of concepts, LOK interpreter, definition browsers, inspectors, query interfaces, etc.

4.3 The LOK Language

The LOK language (Language for Ontological Knowledge) is a dedicated ontology-oriented language composedof more than 150 instructions, with a 'a la Lisp' syntax. Let us take the simple following example extracted from theontology 'Machining' (see figure 3).

The first thing to do is to define the elementary units of meaning as couples of opposite differences:( defineDifference 'metal preservation' 'no metal preservation'),( defineDifference 'piece rotation' 'tool rotation' ),

Then, to create a root concept: ( defineRootConcept 'Mechanical Machining' ),

578

After that, new concepts can be added:( defineConceptFrom 'Mechanical Machining1 ( rightConcept 'Stamping'

( specificDifference 'metal preservation1) ) )

OK Grapher interface. User: Roche. Ontology: machining.i

.shonymoGs5•—^ 1 • • - • : ' : • Bectro-erosion —-' 1 •;.'.'•.:'.•::EUeeiro-platirig —j i ;.••::: ;anonymous6

FIGURE 3. An ontology viewed as a Porphyry tree.

5 THE ACQUISITION METHODOLOGY

Ontology capturing (Uschold 1995) is a difficult and crucial problem; and although some useful guidelines havebeen defined the problem remains complex [17], [18], [19]: "Ontologies are becoming increasingly popular inpractice, but a principled methodology for building them is still lacking." [20], Building ontologies is an acquisitionknowledge problem that can be split into interlaced and incremental processes: extracting potential terms, findingobjects, concepts and relationships, producing definitions... It is important to notice that thought and language andstrongly linked. As a matter of fact, one does not define in a same way a concept in natural language, in calculuspredicate or in a frame system. The OK model gives strong guidelines for building ontologies. The first stage isextracting potential terms, especially nouns, using the linguistic module. The second one identifies the kind of terms:concept, set (a set is not a concept), difference, attribute, relationship. Some practical rules help the knowledgemanager to do that, e.g. a difference is never valued whereas an attribute is. Finally, the 'specific difference'relationships between concepts are defined with the help of the difference-grid tool, a specific tool of OK model. Itsprinciple is to define an array with the concept terms as columns and the difference terms as rows (see figure 4below). This array is filled with appropriate values according to whether the difference belongs to the concept or not,or if it is no relevant for the concept. The 'specific difference' relationships are the result of processing the array.

piece rotationtool rotationno metal preservationmetal preservationmechanical deformationthermal deformation

Millingnoyesyesnono relevantno relevant

Stampingno relevantno relevantnoyesyesno

Turningyesnoyesnono relevantno relevant

Electro-platingno relevantno relevantyesnono relevantno relevant

FIGURE 4. The Difference Grid.

579

6 CONCLUSION

The Information Society relies more and more on communication between interacting and heterogeneous actors :people, organisations and even software systems. But no communication is possible, and all the more so no co-operation or collaboration, between those actors if they do not agree upon the meaning of the terms they use: theInformation Society is the new Tower of Babel.

Ontology, understood as an agreed vocabulary of common terms and meanings, is a solution to that problem.Nevertheless, several barriers remain which stand against a real use of ontology. We claim that a multidisciplinaryapproach based on sound epistemological, logical and linguistic principles is needed in order to reach a real ontologycommitment. We presented a model for ontological knowledge called OK (Ontological Knowledge) based on the"specific difference" theory. This model provides many advantages: consensual definitions and logical propertieswhich are guarantees of ontology commitment, reuse and sharing. The OK Station0 is an implementation of the OKmodel. It is a software environment dedicated to building, defining and exploiting ontologies.

REFERENCES

1. G.R. Olsen, M. Cutkosky, J.M. Tenenbaum, T.R. Gruber (1994). "Collaborative Engineering based onKnowledge Sharing Agreements", ASME Database Symposium, Minneapolis.

2. T.R. Gruber, J.M. Tenenbaum, J.C. Weber (1992). "Toward a Knowledge Medium for Collaborative ProductDevelopment", Artificial Intelligence in Design Conference, Pittsburgh, USA.

3. Cutkosky, Engelmore, Fikes, Gruber, Genesereth, Mark, Tenenbaum and Weber (1993). PACT: An experiment inintegrating concurrent engineering systems, in IEEE Computer, vol. 26, n°l, January 1993.

4. McGuire, Kuokka, Weber, Tenenbaum, Gruber and Olsen (1993). "SHADE: Technology for Knowledge-BasedCollaborative Engineering", Concurrent Engineering: Research & Applications, Volumel, number 3, September1993.

5. Y. Labrou, T. Finin (1997). "A proposal for a new KQML Specification", Internal Report TR CS-97-03,Computer Science and Electrical Engineering Department (CSEE), University of Maryland Baltimore County(UMBC), February 1997.

6. FIPA: Foundation for Intelligent Physical Agents: http://www.fipa.org/7. KACTUS Esprit Project 8145. "Framework and Formalism for Expressing Ontologies"8. Nicola Guarino (1995). "Ontologies and Knowledge Bases. Towards a Terminological Clarification" Towards

Very Large Knowledge Bases, IOS Press, Amsterdam, 1995.9. T. R. Gruber (1993). A translation approach to portable ontologies. Knowledge Acquisition, 5(2): 199-220, 1993

(http://www-ksl.stanford.edu/kst/what-is-an-ontology.html).10. Ontology.org. http://www.ontology.org11.M. Uschold & M. Gruninger (1996). "Ontologies: Principles, Methods and Applications" Knowledge

Engineering Review, Vol. 11, n° 2, June 1996.12. Ontology Inference Layer OIL : http://www.ontoknowledge.org/oil/13. FIPA (1998). Specification - Part 12 : Ontology Service : http://www.fipa.org14. Fox M.S (1992)., The TOVE Project: Towards a Common Sense Model of the Enterprise, in Enterprise

Integration, C. Petrie (Ed.), Cambridge MA: MIT Press.15.M. Uschold, M. King, S. Moralee, Y. Zorgios (1997). "The Enterprise Ontology" AIM, The University of

Edinburgh.16. Genesereth M.R. and Fikes R.E. (1992). Knowledge Interchange Format Version 3.0, Reference Manual, Report

Logic 92-1, Computer Science Department, Stanford University, June 1992.17. Mike Uschold and Martin King (1995). "Towards a Methodology for Building Ontologies" internal report AIAI-

TR-183, July 1995.18. M. Uschold, M. Gruninger (1996). "Ontologies: Principles, Methods and Applications" AIAI-TR-191.19. T. Gruber (1995). "Towards principles for the design of ontologies used for knowledge sharing" International

Journal of Human Computer Studies, 43: 907-928.20. Nicola Guarino and Christopher Welty. "A Formal Ontology of Properties". Proceedings of 12th Int. Conf. on

Knowledge Engineering and Knowledge Management, Lecture Notes in Computer Science, Springer Verlag

580