The purpose of this paper is to defend the systematic introduction of formal ontological principles in the current practice of knowledge engineering, to explore the various relationships between ontology and knowledge representation, and to present the recent trends in this promising research area. According to the "modelling view" of knowledge acquisition proposed by Clancey, the modeling activity must establish a correspondence between a knowledge base and two separate subsystems: the agent's behavior (i.e. the problem-solving expertize) and its own environment (the problem domain). Current knowledge modelling methodologies tend to focus on the former subsystem only, viewing domain knowledge as strongly dependent on the particular task at hand: in fact, AI researchers seem to have been much more interested in the nature of reasoning rather than in the nature of the real world. Recently, however, the potential value of task-independent knowlege bases (or "ontologies") suitable to large scale integration has been underlined in many ways. In this paper, we compare the dichotomy between reasoning and representation to the philosophical distinction between epistemology and ontology. We introduce the notion of the ontological level, intermediate between the epistemological and the conceptual level discussed by Brachman, as a way to characterize a knowledge representation formalism taking into account the intended meaning of its primitives. We then discuss some formal ontological distinctions which may play an important role for such purpose.

The duality of objects and relationships is so deeply embedded in our thinking that almost all modelling languages include it as a fundamental distinction. Yet there is evidence that the two are naturally complemented by a third, equally fundamental notion: that of roles. Although definitions of the role concept abound in the literature, we maintain that only few are truly original, and that even fewer acknowledge the intrinsic role of roles as intermediaries between relationships and the objects that engage in them. After discussing the major families of role conceptualizations, we present our own basic definition and demonstrate how it naturally accounts for many modelling issues, including multiple and dynamic classification, object collaboration, polymorphism, and substitutability. <3 2000 Elsevier Science B.V. All rights reserved.

This paper offers two main contributions. On the one hand, it establishes a general formal framework for developing a foundational ontology of socially constructed entities, in the broadest sense of this notion; on the other hand, it further contributes to understanding the ontological nature of roles. The key choice here is to put all social entities in the domain of discourse: besides social individuals, we also consider ‘reified ’ social concepts and roles, as well as their descriptions, i.e, the ‘social conventions ’ or ‘contexts ’ that define them. This allows us to formally characterize in a first-order theory the relationships among all these entities. 1

We focus in this paper on some meta-level ontological distinctions among unary predicates, like those between concepts and assertional properties. Three are the main contributions of this work, mostly based on a revisitation of philosophical (and linguistic) literature in the perspective of knowledge representation. The first is a formal notion of ontological commitment, based on a modal logic endowed with mereological and topological primitives. The second is a formal account of Strawson's distinction between sortal and non-sortal predicates. Assertional

There is a subtle risk of ambiguity in the choice between concepts and roles forced by current KL-ONE-like languages, since many roles may be concepts as well. In this paper we explore the ontological foundations of the role/concept relationship, and analyze its implications on the practice of knowledge engineering. We criticize the current interpretation of KL-ONE roles as arbitrary relations, which vanishes their original meaning and makes them identical to slots. We suggest to call attributes those concepts which actually act as conceptual components, and propose a formal semantics which binds these concepts to their corresponding relations.

We develop a new computational model for representing the fine-grained meanings of near-synonyms and the differences between them. We also develop a sophisticated lexical-choice process that can decide which of several near-synonyms is most appropriate in a particular situation. This research has direct applications in machine translation and text generation. We first identify the problems of representing near-synonyms in a computational lexicon and show that no previous model adequately accounts for near-synonymy. We then propose a preliminary theory to account for near-synonymy, relying crucially on the notion of granularity of representation, in which the meaning of a word arises out of a context-dependent combination of a context-independent core meaning and a set of explicit differences to its near-synonyms. That is, near-synonyms cluster together. We then develop a clustered model of lexical knowledge, derived from the conventional ontological model. The model cuts off the ontology at a coarse grain, thus avoiding an awkward proliferation of language-dependent concepts in the ontology, and groups near-synonyms into subconceptual clusters that are linked to the ontology. A cluster differentiates near-synonyms in terms of fine-grained aspects of denotation, implication, expressed attitude, and style. The model is general enough to account for other types of variation, for instance, in collocational behaviour. An efficient, robust, and flexible fine-grained lexical-choice process is a consequence of a clustered model of lexical knowledge. To make it work, we formalize criteria for lexical choice as preferences to express certain concepts with varying indirectness, to express attitudes, and to establish certain styles. The lexical-choice process itself works on two tiers: between clusters and between near-synonyns of clusters. We describe our prototype implementation of the system, called I-Saurus.

Formalizing the ontological commitment of a logical language means offering a way to specify the intended meaning of its vocabulary by constraining the set of its models, giving explicit information about the intended nature of the modelling primitives and their a priori relationships. We present here a formal definition of ontological commitment which aims to capture the very basic ontological assumptions about the intended domain, related to issues such as identity and internal structure. To tackle such issues, a modal framework endowed with mereo-topological primitives has been adopted. The paper is mostly based on a revisitation of philosophical (and linguistic) literature in the perspective of knowledge representation.

. In an experimental setting of mechanical-object assembly, the CODY ##Concept Dynamics"# project is concerned with the development of knowledge representations and inference methods that are able to dynamically conceptualize the situation in the task environment. A central aim is to enable an arti#cial agentto understand and process natural-language instructions of a human partner. Instructions may build on the current perception of the assembly environment on the one hand, and on the other on the knowledge-based understanding of grouped structures in the developing construct. To this end, a dynamic conceptualization must integrate information not only describing the types of the objects involved, but also their changing functional roles when becoming part of structured assemblies. Wehave developed an operational knowledge representation formalism, COAR ##Concepts for Objects, Assemblies, and Roles"#, by which processes of dynamic conceptualization in sequences of assembly steps can...

Abstract. Role is very important in ontology engineering. Although OWL has been available for ontology representation, consideration about roles is not enough. It can cause to decrease semantic interoperability of ontologies because of conceptual gaps between OWL and developers. To overcome this difficulty, this paper presents some consideration for dealing with roles using OWL. 1.

In this article we tackle controversial questions about the nature of method ontology and its relation to domain ontology. In order to consider a genuine "method ontology", and to explain the link between problem-solving concepts and domain concepts, we propose a new ontological framework consisting of attributing to concepts the status of extensional objects. Within this framework it becomes possible to consider concept states and to envisage different specializations of such states, in particular "roles". The problemsolving concepts can therefore be defined as roles played, not by objects modelling the external world, but by concepts. In the article we also envisage the consequences that this framework entails for the formalization of an ontology. 1 Introduction The framework that we propose in this paper has been elaborated in reponse to problems encountered when designing an ontology for SATIN [Kas97a], an expert system in neonatalogy. This ontology will be named O...