The Relation between a Framework forCollaborative Ontology Engineering andNicola Guarino’s Terminology and Ideas in“Formal Ontology and Information Systems”

Christophe Debruyne2013-05-01

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Table of contents

Introduction

Formal Ontology and Information Systems

Open vs. Closed Information Systems

Developing Ontology Guided Methods and Applications

Relation between the two Formalisms

Conclusion

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Introduction

Ontology by [Gru93]An ontology is commonly defined as: “a [formal,] explicit specificationof a [shared] conceptualization”.

I Gruber’s definition was based on the definition of Geneserethand Nilsson’s notion of a conceptualization [GN87] that used anextensional notion for describing one particular state of affairs.

I Guarino and Gieretta in [GG95] argued that a differentintensional account of the notion of conceptualization has to beintroduced

I Guarino then wrote his – currently – most influential work“Formal Ontology and Information Systems” in which he provideddefinitions for conceptualization, ontological commitment andontology.

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Introduction

I The problem is not only what ontologies in computer science are,but how they also come to be shared artifacts in a network ofhumans and computerized systems.

I Over the past years, quite a few (collaborative)ontology-engineering methods have been developed, each withtheir own characteristics; e.g., the formalism adopted, approachof agreement processes, application domain, etc.

I The goal of this presentation are:I Relate the two different formalisms and terminologies;I Provide a reference for disambiguation (e.g., the slightly different

notion of ontological commitment in the two frameworks.

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Formal Ontology and Information Systems

Figure : “The intended models of a logical language reflect its commitment toa conceptualization. An ontology indirectly reflects this commitment (and theunderlying conceptualization) by approximating this set of intended models.”(Figure from [Gua98])

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Open vs. Closed Information Systems

I [Gua98] provided a definition for ontologies;I Ontologies are key for semantic interoperability between

autonomously developed and maintained information systems;I Open vs. Closed Information Systems;I Are similar in “exercise”.

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Open vs. Closed Information Systems

Information System

AGREEMENT(N.L.)

End users

Designer

Business Domain Expert

Conceptual Schema

Design Tool

"Real world"Business Domain

Abstraction from instances

Communicate at instance level

Observe/Interact => Test by instances

Observe/Abstract

DB Schema

DBMS

DB

Apps

ENTERPRISE CONTEXT - DEFINED BY REQUIREMENTS

Figure : Information Systems in an enterprise context.

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Open vs. Closed Information Systems

Shared World

Community

Observe/Interact

Enterprise IS 1 Enterprise IS 2

Agreement

Interaction

ONTOLOGY

leads to

results in

Replacing

SemanticInteroperability

Enables

Figure : Agreements leading to ontology for enabling semantic interoperability

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DOGMA

Developing Ontology Guided Methods and Applications.

Definition (DOGMA Ontology Descriptions)

DOGMA Ontology Descriptions Ω = 〈Λ, ci ,K〉I Λ a lexon base, a finite set of plausible binary fact types called

lexons 〈γ, t1, r1, r2, t2〉, with γ ∈ Γ context-identifiers.I ci a function mapping context-identifiers and terms to conceptsI K a finite set of ontological commitments containing

I A selection of lexonsI A mapping from application symbols to ontology termsI Predicates over those terms and roles to express constraints

Note: fact orientation, double articulation

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DOGMA

The hybrid aspect of ontologiesI Ontologies are resources shared among humans working in a

community, and (networked) systemsI Mapping of terms to a concept is the result of a community

agreementI Capture those agreements, turn communities into first class

citizens of the ontology, resulting notion called hybrid ontologyI Fundamental technology: formalized glossaries, special

linguistic resources to support the agreement process

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DOGMA

Definition (Hybrid Ontology Description )

Hybrid Ontology Description HΩ = 〈Ω,G〉I Ω a DOGMA Ontology DescriptionI The contexts in Γ are referring/called communitiesI G is a glossary, a quadruple with components

I Gloss, a set of linguistic, human-interpretable glossesI g1, mapping community-term pairs to glossesI g2, mapping lexons to glossesI Pairs of glosses agreed to be referring to the same concept

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DOGMA

I Community commitments contains a selection of lexons +constraints to ensure proper semantic interoperability within acommunity

I Application commitments refer to one or more communitycommitments, possibly extended with application-specificknowledge (lexons + constraints) and mappings from applicationsymbols to concepts and relations in the ontology.

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DOGMA

I Without agreement on synonymy, all following lexons aredifferent:

I 〈Person Context, Person, with, of, Name〉I 〈Person Context, Dog, with, of, Name〉I 〈Person Context, Person, with, of, Age〉I 〈Project Context, Person, with, of, Name〉

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Relation between the two Formalisms

Previous work

I DOGMA follows the intensional notion of a conceptualization ofGuarino, but arrived at it from a database-inspired perspective[Mee99a, JM09].

I DOGMA, however, also pursues this idea to arrive at concretesoftware architectural and engineering conclusions [JM09].

I Other than this statement in [JM09], there is no existingpublication on the relationship between the work of Guarino andDOGMA.

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Relation between the two Formalisms

Analyzing lexons (I)

I The sets T and R for term- and role-labels in lexons correspondto the predicate symbols in V .

I The context-identifier γ provides an interpretation from terms toconcepts.

I The context-identifier γ actually corresponds to Guarino’sinterpretation function I. In other words, if one selects in thelexon base all lexons holding in a particular context withcontext-identifier γ, one is able to reconstruct Guarino’sinterpretation function I: all concepts x referred to by ci(γ, t) (foreach term t in those lexons) will refer to the interpretation of aunary predicate.

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Relation between the two Formalisms

Analyzing lexons (II)

I DOGMA’s is based on ORM and NIAM, which are fact-orientedmodelling language.

I Because of DOGMA’s fact-orientation, the use of the predicatesdenoted by the term- and role-labels are already constrained[Hal89]. A binary fact type 〈A,R,S,B〉 is actually translated intothe following first order logic statements [Hal89]:

I ∀x∀y(R(x , y) → (A(x) ∧ B(y))I ∀x∀y(R(x , y) ↔ S(y , x))

I These constraints already reduce the set of possible models withlanguage L.

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Relation between the two Formalisms

Analyzing commitments (I)

I A commitment k ∈ K of the DOGMA Ontology Descriptioncorresponds with one ontology from Guarino’s framework.

I It is a selection of lexon from the lexon base that is constrainedsuch that it approximates as good as possible the domain it aimsto describe. Those constraints correspond with the notion ofaxioms and typically include notions such as: type- and rolehierarchies, totality constraints, uniqueness constraints, valueconstraints, etc.

I Value constraints are interesting to note that they limit domainelements for the interpretation of concept referred to by a term.The only place in DOGMA where we have a notion of labelsreferring to individuals.

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Relation between the two Formalisms

Analyzing commitments (II)

I A community commitment further restrains all possible models ofthe lexons committed to.

I An application commitment will even further restrain those byproviding additional lexons, constraints, and narrowing down allpossible models by providing additional constants via themappings.

I However mapping from database to ontology, and databaseassumed to be replacing the conceptualization. (!) Thusconstant symbols for referring to individuals are done so viamappings, returning the constant symbols of the application.

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Relation between the two Formalisms

Analyzing commitments (III)

I It follows that one needs to break down the commitments andcombine pieces with the lexon base (cfr. ci function) toreconstruct Guarino’s ontological commitment. In other words,there is a high cohesion between ontological commitments andontologies in the DOGMA ontology engineering framework.

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In Conclusion

I The goal was to provide a point of reference for understandingsome aspects of the DOGMA framework.

I We presented the terminology used by Guarino.I We presented the DOGMA frameworkI We related the two frameworks and terminologies.

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References I

C. Debruyne, T. K. Tran, and R. Meersman, Grounding ontologies with social processes andnatural language (to appear)., Journal of Data Semantics (2013).

N. Guarino and P. Giaretta, Ontologies and Knowledge Bases: Towards a TerminologicalClarification, Towards Very Large Knowledge Bases: Knowledge Building and KnowledgeSharing (1995), 25–32.

M. Genesereth and N. Nilsson, Logical foundations of artificial intelligence, MorganKaufmann, San Mateo, CA, 1987.

T. Gruber, Toward principles for the design of ontologies used for knowledge sharing,International Journal of Human-Computer Studies 43 (1993), 907–928.

N. Guarino, Formal ontology and information systems, International Conference On FormalOntology In Information Systems FOIS’98 (Trento, Italy), Amsterdam, IOS Press, June 1998,pp. 3–15.

T. A. Halpin, A logical analysis of information systems: static aspects of the data-orientedperspective, Ph.D. thesis, University of Queensland, 1989.

M. Jarrar and R. Meersman, Ontology engineering – the DOGMA approach, Advances inWeb Semantics I (T. S. Dillon, E. Chang, R. Meersman, and K. Sycara, eds.), LNCS, vol.4891, Springer Berlin Heidelberg, 2009, pp. 7–34.

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References II

R. Meersman, Semantic ontology tools in IS design, ISMIS (Z. W. Ras and A. Skowron, eds.),LNCS, vol. 1609, Springer, 1999, pp. 30–45.

R. Meersman, The use of lexicons and other computer-linguistic tools in semantics, designand cooperation of database systems, The Proceedings of the Second InternationalSymposium on Cooperative Database Systems for Advanced Applications (CODAS99)(Y. Zhang, M. Rusinkiewicz, and Y. Kambayashi, eds.), Springer, 1999, pp. 1–14.

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