The Relation between a Framework for Collaborative Ontology Engineering and Nicola Guarino's Terminology and Ideas in ``Formal Ontology and Information Systems''
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The Relation between a Framework for Collaborative Ontology Engineering and Nicola Guarino's Terminology and Ideas in ``Formal Ontology and Information Systems''

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Presented at the IFIP WG 12.7 VASCO 2013 Workshop ...

Presented at the IFIP WG 12.7 VASCO 2013 Workshop

In this paper, we investigate the relation between Guarino's seminal paper ``Formal Ontology and Information Systems'' and the DOGMA ontology-engineering framework. As DOGMA is geared towards the development of ontologies for semantic interoperation between autonomously developed and maintained information systems, it follows that the stakeholders in this project form a community and adds a social dimension to the ontology project. The goal of this exercise is to examine how the different terminologies and ideas relate to one and another, thus providing a reference for clarifying DOGMA's ideas and notation inside Guarino's framework.

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The Relation between a Framework for Collaborative Ontology Engineering and Nicola Guarino's Terminology and Ideas in ``Formal Ontology and Information Systems'' The Relation between a Framework for Collaborative Ontology Engineering and Nicola Guarino's Terminology and Ideas in ``Formal Ontology and Information Systems'' Presentation Transcript

  • The Relation between a Framework forCollaborative Ontology Engineering andNicola Guarino’s Terminology and Ideas in“Formal Ontology and Information Systems”Christophe Debruyne2013-05-012013-05-01| page 1
  • Table of contentsIntroductionFormal Ontology and Information SystemsOpen vs. Closed Information SystemsDeveloping Ontology Guided Methods and ApplicationsRelation between the two FormalismsConclusion2013-05-01| page 2
  • IntroductionOntology by [Gru93]An ontology is commonly defined as: “a [formal,] explicit specificationof a [shared] conceptualization”.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.Guarino and Gieretta in [GG95] argued that a differentintensional account of the notion of conceptualization has to beintroducedGuarino then wrote his – currently – most influential work“Formal Ontology and Information Systems” in which he provideddefinitions for conceptualization, ontological commitment andontology.2013-05-01| page 3
  • IntroductionThe 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.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.The goal of this presentation are:Relate the two different formalisms and terminologies;Provide a reference for disambiguation (e.g., the slightly differentnotion of ontological commitment in the two frameworks.2013-05-01| page 4
  • Formal Ontology and Information SystemsFigure : “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])2013-05-01| page 5
  • Open vs. Closed Information Systems[Gua98] provided a definition for ontologies;Ontologies are key for semantic interoperability betweenautonomously developed and maintained information systems;Open vs. Closed Information Systems;Are similar in “exercise”.2013-05-01| page 6
  • Open vs. Closed Information SystemsInformation SystemAGREEMENT(N.L.)End usersDesignerBusinessDomain ExpertConceptualSchemaDesignTool"Real world"Business DomainAbstractionfrom instancesCommunicate atinstance levelObserve/Interact => Test byinstancesObserve/AbstractDBSchemaDBMSDBAppsENTERPRISE CONTEXT - DEFINED BY REQUIREMENTSFigure : Information Systems in an enterprise context.2013-05-01| page 7
  • Open vs. Closed Information SystemsShared WorldCommunityObserve/InteractEnterprise IS 1 Enterprise IS 2AgreementInteractionONTOLOGYleads toresults inReplacingSemanticInteroperabilityEnablesFigure : Agreements leading to ontology for enabling semantic interoperability2013-05-01| page 8
  • DOGMADeveloping Ontology Guided Methods and Applications.Definition (DOGMA Ontology Descriptions)DOGMA Ontology Descriptions Ω = Λ, ci, KΛ a lexon base, a finite set of plausible binary fact types calledlexons γ, t1, r1, r2, t2 , with γ ∈ Γ context-identifiers.ci a function mapping context-identifiers and terms to conceptsK a finite set of ontological commitments containingA selection of lexonsA mapping from application symbols to ontology termsPredicates over those terms and roles to express constraintsNote: fact orientation, double articulation2013-05-01| page 9
  • DOGMAThe hybrid aspect of ontologiesOntologies are resources shared among humans working in acommunity, and (networked) systemsMapping of terms to a concept is the result of a communityagreementCapture those agreements, turn communities into first classcitizens of the ontology, resulting notion called hybrid ontologyFundamental technology: formalized glossaries, speciallinguistic resources to support the agreement process2013-05-01| page 10
  • DOGMADefinition (Hybrid Ontology Description )Hybrid Ontology Description HΩ = Ω, GΩ a DOGMA Ontology DescriptionThe contexts in Γ are referring/called communitiesG is a glossary, a quadruple with componentsGloss, a set of linguistic, human-interpretable glossesg1, mapping community-term pairs to glossesg2, mapping lexons to glossesPairs of glosses agreed to be referring to the same concept2013-05-01| page 11
  • DOGMACommunity commitments contains a selection of lexons +constraints to ensure proper semantic interoperability within acommunityApplication 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.2013-05-01| page 12
  • DOGMAWithout agreement on synonymy, all following lexons aredifferent:Person Context, Person, with, of, NamePerson Context, Dog, with, of, NamePerson Context, Person, with, of, AgeProject Context, Person, with, of, Name2013-05-01| page 13
  • Relation between the two FormalismsPrevious workDOGMA follows the intensional notion of a conceptualization ofGuarino, but arrived at it from a database-inspired perspective[Mee99a, JM09].DOGMA, however, also pursues this idea to arrive at concretesoftware architectural and engineering conclusions [JM09].Other than this statement in [JM09], there is no existingpublication on the relationship between the work of Guarino andDOGMA.2013-05-01| page 14
  • Relation between the two FormalismsAnalyzing lexons (I)The sets T and R for term- and role-labels in lexons correspondto the predicate symbols in V.The context-identifier γ provides an interpretation from terms toconcepts.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.2013-05-01| page 15
  • Relation between the two FormalismsAnalyzing lexons (II)DOGMA’s is based on ORM and NIAM, which are fact-orientedmodelling language.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]:∀x∀y(R(x, y) → (A(x) ∧ B(y))∀x∀y(R(x, y) ↔ S(y, x))These constraints already reduce the set of possible models withlanguage L.2013-05-01| page 16
  • Relation between the two FormalismsAnalyzing commitments (I)A commitment k ∈ K of the DOGMA Ontology Descriptioncorresponds with one ontology from Guarino’s framework.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.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.2013-05-01| page 17
  • Relation between the two FormalismsAnalyzing commitments (II)A community commitment further restrains all possible models ofthe lexons committed to.An application commitment will even further restrain those byproviding additional lexons, constraints, and narrowing down allpossible models by providing additional constants via themappings.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.2013-05-01| page 18
  • Relation between the two FormalismsAnalyzing commitments (III)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.2013-05-01| page 19
  • In ConclusionThe goal was to provide a point of reference for understandingsome aspects of the DOGMA framework.We presented the terminology used by Guarino.We presented the DOGMA frameworkWe related the two frameworks and terminologies.2013-05-01| page 20
  • References IC. 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. 7–34.2013-05-01| page 21
  • References IIR. 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. 1–14.2013-05-01| page 22