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.

1. The Relation between a Framework for
Collaborative Ontology Engineering and
Nicola Guarino’s Terminology and Ideas in
“Formal Ontology and Information Systems”
Christophe Debruyne
2013-05-01
2013-05-01| page 1

2. 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
2013-05-01| page 2

3. Introduction
Ontology by [Gru93]
An ontology is commonly defined as: “a [formal,] explicit specification
of a [shared] conceptualization”.
Gruber’s definition was based on the definition of Genesereth
and Nilsson’s notion of a conceptualization [GN87] that used an
extensional notion for describing one particular state of affairs.
Guarino and Gieretta in [GG95] argued that a different
intensional account of the notion of conceptualization has to be
introduced
Guarino then wrote his – currently – most influential work
“Formal Ontology and Information Systems” in which he provided
definitions for conceptualization, ontological commitment and
ontology.
2013-05-01| page 3

4. Introduction
The problem is not only what ontologies in computer science are,
but how they also come to be shared artifacts in a network of
humans and computerized systems.
Over the past years, quite a few (collaborative)
ontology-engineering methods have been developed, each with
their own characteristics; e.g., the formalism adopted, approach
of 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 different
notion of ontological commitment in the two frameworks.
2013-05-01| page 4

5. Formal Ontology and Information Systems
Figure : “The intended models of a logical language reflect its commitment to
a conceptualization. An ontology indirectly reflects this commitment (and the
underlying conceptualization) by approximating this set of intended models.”
(Figure from [Gua98])
2013-05-01| page 5

6. Open vs. Closed Information Systems
[Gua98] provided a definition for ontologies;
Ontologies are key for semantic interoperability between
autonomously developed and maintained information systems;
Open vs. Closed Information Systems;
Are similar in “exercise”.
2013-05-01| page 6

7. 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.
2013-05-01| page 7

8. Open vs. Closed Information Systems
Shared World
Community
Observe/Interact
Enterprise IS 1 Enterprise IS 2

Agreement
Interaction
ONTOLOGY
leads to
results in
Replacing
Semantic
Interoperability
Enables
Figure : Agreements leading to ontology for enabling semantic interoperability
2013-05-01| page 8

9. DOGMA
Developing Ontology Guided Methods and Applications.
Definition (DOGMA Ontology Descriptions)
DOGMA Ontology Descriptions Ω = Λ, ci, K
Λ a lexon base, a finite set of plausible binary fact types called
lexons γ, t1, r1, r2, t2 , with γ ∈ Γ context-identifiers.
ci a function mapping context-identifiers and terms to concepts
K a finite set of ontological commitments containing
A selection of lexons
A mapping from application symbols to ontology terms
Predicates over those terms and roles to express constraints
Note: fact orientation, double articulation
2013-05-01| page 9

10. DOGMA
The hybrid aspect of ontologies
Ontologies are resources shared among humans working in a
community, and (networked) systems
Mapping of terms to a concept is the result of a community
agreement
Capture those agreements, turn communities into first class
citizens of the ontology, resulting notion called hybrid ontology
Fundamental technology: formalized glossaries, special
linguistic resources to support the agreement process
2013-05-01| page 10

11. DOGMA
Definition (Hybrid Ontology Description )
Hybrid Ontology Description HΩ = Ω, G
Ω a DOGMA Ontology Description
The contexts in Γ are referring/called communities
G is a glossary, a quadruple with components
Gloss, a set of linguistic, human-interpretable glosses
g1, mapping community-term pairs to glosses
g2, mapping lexons to glosses
Pairs of glosses agreed to be referring to the same concept
2013-05-01| page 11

12. DOGMA
Community commitments contains a selection of lexons +
constraints to ensure proper semantic interoperability within a
community
Application commitments refer to one or more community
commitments, possibly extended with application-specific
knowledge (lexons + constraints) and mappings from application
symbols to concepts and relations in the ontology.
2013-05-01| page 12

13. DOGMA
Without agreement on synonymy, all following lexons are
different:
Person Context, Person, with, of, Name
Person Context, Dog, with, of, Name
Person Context, Person, with, of, Age
Project Context, Person, with, of, Name
2013-05-01| page 13

14. Relation between the two Formalisms
Previous work
DOGMA follows the intensional notion of a conceptualization of
Guarino, but arrived at it from a database-inspired perspective
[Mee99a, JM09].
DOGMA, however, also pursues this idea to arrive at concrete
software architectural and engineering conclusions [JM09].
Other than this statement in [JM09], there is no existing
publication on the relationship between the work of Guarino and
DOGMA.
2013-05-01| page 14

15. Relation between the two Formalisms
Analyzing lexons (I)
The sets T and R for term- and role-labels in lexons correspond
to the predicate symbols in V.
The context-identifier γ provides an interpretation from terms to
concepts.
The context-identifier γ actually corresponds to Guarino’s
interpretation function I. In other words, if one selects in the
lexon base all lexons holding in a particular context with
context-identifier γ, one is able to reconstruct Guarino’s
interpretation function I: all concepts x referred to by ci(γ, t) (for
each term t in those lexons) will refer to the interpretation of a
unary predicate.
2013-05-01| page 15

16. Relation between the two Formalisms
Analyzing lexons (II)
DOGMA’s is based on ORM and NIAM, which are fact-oriented
modelling language.
Because of DOGMA’s fact-orientation, the use of the predicates
denoted by the term- and role-labels are already constrained
[Hal89]. A binary fact type A, R, S, B is actually translated into
the 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 with
language L.
2013-05-01| page 16

17. Relation between the two Formalisms
Analyzing commitments (I)
A commitment k ∈ K of the DOGMA Ontology Description
corresponds with one ontology from Guarino’s framework.
It is a selection of lexon from the lexon base that is constrained
such that it approximates as good as possible the domain it aims
to describe. Those constraints correspond with the notion of
axioms and typically include notions such as: type- and role
hierarchies, totality constraints, uniqueness constraints, value
constraints, etc.
Value constraints are interesting to note that they limit domain
elements for the interpretation of concept referred to by a term.
The only place in DOGMA where we have a notion of labels
referring to individuals.
2013-05-01| page 17

18. Relation between the two Formalisms
Analyzing commitments (II)
A community commitment further restrains all possible models of
the lexons committed to.
An application commitment will even further restrain those by
providing additional lexons, constraints, and narrowing down all
possible models by providing additional constants via the
mappings.
However mapping from database to ontology, and database
assumed to be replacing the conceptualization. (!) Thus
constant symbols for referring to individuals are done so via
mappings, returning the constant symbols of the application.
2013-05-01| page 18

19. Relation between the two Formalisms
Analyzing commitments (III)
It follows that one needs to break down the commitments and
combine pieces with the lexon base (cfr. ci function) to
reconstruct Guarino’s ontological commitment. In other words,
there is a high cohesion between ontological commitments and
ontologies in the DOGMA ontology engineering framework.
2013-05-01| page 19

20. In Conclusion
The goal was to provide a point of reference for understanding
some aspects of the DOGMA framework.
We presented the terminology used by Guarino.
We presented the DOGMA framework
We related the two frameworks and terminologies.
2013-05-01| page 20

21. References I
C. Debruyne, T. K. Tran, and R. Meersman, Grounding ontologies with social processes and
natural language (to appear)., Journal of Data Semantics (2013).
N. Guarino and P. Giaretta, Ontologies and Knowledge Bases: Towards a Terminological
Clarification, Towards Very Large Knowledge Bases: Knowledge Building and Knowledge
Sharing (1995), 25–32.
M. Genesereth and N. Nilsson, Logical foundations of artificial intelligence, Morgan
Kaufmann, 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 Formal
Ontology 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-oriented
perspective, Ph.D. thesis, University of Queensland, 1989.
M. Jarrar and R. Meersman, Ontology engineering – the DOGMA approach, Advances in
Web 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

22. 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, design
and cooperation of database systems, The Proceedings of the Second International
Symposium 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