This paper is intended to serve as a comprehensive introduction to the emerging field concerned with the design and use of ontologies. We observe that disparate backgrounds, languages, tools and techniques are a major barrier to effective communication among people, organisations and/or software understanding (i.e. an “ontology”) in a given subject area, can improve such communication, which in turn, can give rise to greater reuse and sharing, inter-operability, and more reliable software. After motivating their need, we clarify just what ontologies are and what purpose they serve. We outline a methodology for developing and evaluating ontologies, first discussing informal techniques, concerning such issues as scoping, handling ambiguity, reaching agreement and producing definitions. We then consider the benefits and describe, a more formal approach. We re-visit the scoping phase, and discuss the role of formal languages and techniques in the specification, implementation and evalution of ontologies. Finally, we review the state of the art and practice in this emerging field, considering various case studies, software tools for ontology development, key research issues and future prospects.

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Ontologies: principles, methods and applications

Keywords: a Vocabulary of Culture and Society

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 modelling activity must establish a correspondence between a knowledge base and two separate subsystems: the agent's behaviour (i.e. the problem-solving expertise ) and its own environment (the problem domain ). Current knowledge modelling methodologies tend to focus on the former sub-system 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 knowledge 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 levels 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 ontologic distinctions which may play an important role for such purpose.

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Formal ontology, conceptual analysis and knowledge representation

The word \ontology" has recently gained a good popularity within the knowledge engineering community. However, its meaning tends to remain a bit vague, as the term is used in very difierent ways. Limiting our attention to the various proposals made in the current debate in AI, we isolate a number of interpretations, which in our opinion deserve a suitable clariflcation. We elucidate the implications of such various interpretations, arguing for the need of clear terminological choices regarding the technical use of terms like \ontology", \conceptualization" and \ontological commitment". After some comments on the use \Ontology" (with the capital \o") as a term which denotes a philosophical discipline, we analyse the possible confusion between an ontology intended as a particular conceptual framework at the knowledge level and an ontology intended as a concrete artifact at the symbol level, to be used for a given purpose. A crucial point in this clariflcation efiort is the careful analysis of Gruber’ s deflnition of an ontology as a speciflcation of a conceptualization.

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Ontologies and Knowledge Bases. Towards a Terminological Clarification

We describe an ontology for mathematical modeling in engineering. The ontology includes conceptual foundations for scalar, vector, and tensor quantities, physical dimensions, units of measure, functions of quantities, and dimensionless quantities. The conceptualization builds on abstract algebra and measurement theory, but is designed explicitly for knowledge sharing purposes. The ontology is being used as a communication language among cooperating engineering agents, and as a foundation for other engineering ontologies. In this paper we describe the conceptualization of the ontology, and show selected axioms from definitions. We describe the design of the ontology and justify the important representation choices. We offer evaluation criteria for such ontologies and demonstrate design techniques for achieving them.

An ontology for engineering mathematics

Ontology was once understood to be the philosophical inquiry into the structure of reality: the analysis and categorization of what there is. Recently, however, a field called ontology has become part of the rapidly growing research industry in information technology. The two fields have more in common than just their name.Theory and Applications of Ontology is a two-volume anthology that aims to further an informed discussion about the relationship between ontology in philosophy and ontology in information technology. It fills an important lacuna in cutting-edge research on ontology in both fields, supplying stage-setting overview articles on history and method, presenting directions of current research in either field, and highlighting areas of productive interdisciplinary contact.Theory and Applications of Ontology: Computer Applications presents ontology in ways that philosophers are not likely to find elsewhere. The volume offers an overview of current research in ontology, distinguishing basic conceptual issues, domain applications, general frameworks, and mathematical formalisms. It introduces the reader to current research on frameworks and applications in information technology in ways that are sure to invite reflection and constructive responses from ontologists in philosophy.

Theory and Applications of Ontology: Computer Applications

Two essential aspects of Hartmann’s thought are its categorial perspective and the theory of the levels of reality. They are also aspects which have exerted significant influence on Hartmann’s intellectual legacy, however limited that may be. Here I wish to point out their importance for Bertalanffy (see his 1968) and Lorenz (see his 1978). The latter notes the close similarity between his own ideas and those of Hartmann, and he recalls that for Hartmann the world possesses the unity of a system, but it is a system made up of layers. Some pages earlier he writes that he once asked Roberto Corti, who was closely acquainted with Hartmann, how he thought Hartmann would have reacted to a philogenetic interpretation of his thought. Corti replied that Hartmann would undoubtedly have rejected such an interpretation, but then added “And yet this is the only way to do anything with it”.

The Basic Problem of the Theory of Levels of Reality

Purpose – After summarizing the theories of anticipation proposed over the past century, the paper aims to distinguish between anticipation as an empirical phenomenon and the conditions that make anticipation possible. The paper's first part seeks to show that many scholars from various research fields worked on the many nuances of anticipation. The paper's second part seeks to discuss the difference between the capacity of anticipation and the nature of systems able to exhibit anticipatory behavior. The former endeavor adopts a descriptive attitude, whilst the latter seeks to understand what it is that makes anticipation possible.Design/methodology/approach – The paper presents a theoretical and experimental analysis of anticipation and anticipatory systems.Findings – Anticipation is a widely studied phenomenon within a number of different disciplines, including biology and brain studies, cognitive and social sciences, engineering and artificial intelligence. There is a need for relying on at least two d...

Roberto Poli

Papers

Theory and Applications of Ontology: Computer Applications

The Basic Problem of the Theory of Levels of Reality

The many aspects of anticipation

Introduction to Anticipation Studies

An introduction to the ontology of anticipation