Robert E

ISKO Encyclopedia of Knowledge Organization 31 August 2020, 2020

This contribution presents the principal features of ontologies, drawing special attention to the comparison between ontologies and the different kinds of knowledge organization systems (KOS). The focus is on the semantic richness exhibited by ontologies, which allows the creation of a great number of relationships between terms. That establishes ontologies as the most evolved type of KOS. The concepts of “conceptualization” and “formalization” and the key components of ontologies are described and discussed, along with upper and domain ontologies and special typologies, such as bibliographical ontologies and biomedical ontologies. The use of ontologies in the digital libraries environment, where they have replaced thesauri for query expansion in searching, and the role they are playing in the Semantic Web, especially for semantic interoperability, are sketched. Available at https://www.isko.org/cyclo/ontologies

We introduce a new theory of concepts conceived as structured abstract entities. The theory is based on the key notion of Transparent Intensional Logic (TIL), known as TIL construction. The rich procedural semantics of TIL makes it possible to explicitly state all the semantically salient features of natural language expressions. We illustrate how to make use of TIL theory of concepts in distinguishing analytical and empirical concepts, particular kinds of necessities, and for rigorous specification of requisite relations between intensions. Finally, ontology is characterised as a stable part of the system that should play an integrating role. We show how to make use of this rich theory in specification of the content of ontologies in a multi-agent system.

2021

Ontologies are considered as a cornerstone for knowledge-based systems and semantic web for reusing and sharing the knowledge by explicit specification of shared conceptualizations. For representing and organizing knowledge, ontology needs a conceptual model to express the real-world objects. The conceptual model explores a series of entities, relationships and attributes to integrate and correlate the knowledge of domain-related data. It allows the layout of architectures for the usage of contents and the ontology provides an initial conceptual level for the knowledge organization. In this paper, the authors have presented a different conceptual model for the management and representation of specific domain knowledge.

2012

Abstract. In 1982, Wolniewicz proposed a formal ontology of situations based on the lattice of elementary situations (cf. [7, 8]). In [3], I constructed some types of formal structure Porphyrian Tree Structures (PTS), Con-cepts Structures (CS) and the Structures of Individuals (U) that formally represent ontologically fundamental categories: species and genera (PTS), concepts (CS) and individual beings (U) (cf. [3, 4]). From an ontological perspective, situations and concepts belong to different categories. But, unexpectedly, as I shall show, some variants of CS and Wolniewicz’s lattice are similar. The main theorem states that a subset of a modified concepts structure (called CS+) based on CS fulfils the axioms of Wolniewicz ’ lattice. Finally, I shall draw some philosophical conclusions and state some formal facts.

2018

The theory of distributed conceptual structures, as outlined in this paper, is concerned with the distribution and conception of knowledge. It rests upon two related theories, Information Flow and Formal Concept Analysis, which it seeks to unify. Information Flow (IF) is concerned with the distribution of knowledge. The foundations of Information Flow is explicitly based upon a mathematical theory known as the Chu Construction in *-autonomous categories and implicitly based upon the mathematics of closed categories. Formal Concept Analysis (FCA) is concerned with the conception and analysis of knowledge. In this paper we connect these two studies by extending the basic theorem of Formal Concept Analysis to the distributed realm of Information Flow. The main results are the categorical equivalence between classifications and concept lattices at the level of functions, and the categorical equivalence between bonds and complete adjoints at the level of relations. With this we hope to a...

2011

This paper begins the discussion of how the Information Flow Framework can be used to provide a principled foundation for the metalevel (or structural level) of the Standard Upper Ontology (SUO). This SUO structural level can be used as a logical framework for manipulating collections of ontologies in the object level of the SUO or other middle level or domain ontologies. From the Information Flow perspective, the SUO structural level resolves into several metalevel ontologies. This paper discusses a KIF formalization for one of those metalevel categories, the Category Theory Ontology. In particular, it discusses its category and colimit sub-namespaces.

2002

The communication between agents does not only require the exchange of syntactically defined character strings. The agents also need to have a common knowledge background. AI-Research has been pursuing ontologies as an approach of formal language which can also be used to explicate knowledge backgrounds. Ontologies gain a particularly high practical relevance in the scope of the organizational knowledge management. Therefore information systems science has an increasing interest in ontologies. Based on a definition of the term ontology, this paper examines problems of the theory of knowledge and the theory of language, which might be created in the construction of ontologies. Ontologies are interpreted as a special case of conceptual models. Thus, the content of this paper can be applied not only to the strict framework of ontologies, but also to the problems of theory of science in the area of information modeling.

Annals of the Japan Association For Philosophy of Science, 2007

Concepts can be arranged in a taxonomical order by means of a partial ordering relation, and a taxonomical structure of concepts is usually supposed to have a linkage to reality. However, here is a logico-ontological jump of significant theoretical importance: a taxonomical structure of concepts does not include in itself any logical ability to relate concepts to objects. That is to say, a mere arrangement of concepts does not logically require at all of any linkage between concepts and reality. There can logically be no direct jump from concepts to reality. The partial ordering relation required to describe a conceptual taxonomy is in close logical relation to the particle known historically as copula in syllogistic systems. By and large the copula corresponds to the relation IS-A that is today widely used in describing a conceptual taxonomy. We use the symbol '•¼' for IS-A relation. Another relation that relates concepts to objects often called today 'an-instance-of relation' will be introduced by definition. This relation will be expressed by the symbol 'ƒÃ'. To define this relation we shall use the functor of (non-reflexive) identity to which we assign the symbol '='. We aim in this paper to construct a logical system that is appropriate to describing the logical relations between a taxonomy of concepts and reality, which is tantamount to constructing a version of logical Ontology (first constructed by Lesniewski in 1920) on the basis of two primitive functors, i.e. •¼ and =.

In this paper the role of ontology is considered in the context of information systems and conceptual modelling. Firstly we describe information systems and conceptual modelling without using the word "ontology". Then two senses of ontology are presented: philosophical and knowledge representation views. In this connection both Gruber's and Guarino's definitions of "ontology" are scrutinized. It is proposed that the kind of terminological shifts concerning the word "ontology", and practiced e.g. by Gruber and Guarino, have caused more confusion than clarification in the field of information systems and conceptual modelling. Instead of given a new or a better definition of our own, our view is that the word "ontology" should be used in its traditional philosophical sense only, whereas our aim in the field of information systems and conceptual modelling is to reach conceptual clarity.

1998

Research on ontology is becoming increasingly widespread in the computer science community, and its importance is being recognized in a multiplicity of research fields and application areas, including knowledge engineering, database design and integration, information retrieval and extraction. We shall use the generic term "information systems", in its broadest sense, to collectively refer to these application perspectives. We argue in this paper that so-called ontologies present their own methodological and architectural peculiarities: on the methodological side, their main peculiarity is the adoption of a highly interdisciplinary approach, while on the architectural side the most interesting aspect is the centrality of the role they can play in an information system, leading to the perspective of ontology-driven information systems.