We characterize and compare four different ways of representing qualities in formal ontology. Our goal is to discuss their ontological commitments and their adequacy in applications. We also show how the frameworks here presented relate to other approaches in ontology (trope theory), in cognitive science (conceptual spaces), and in physics (International System of Units). The work we present fo...

The paper presents an Ontology of Schizophrenia (OS) that is designed to provide a formal representation of schizophrenia-related entities crucial to the treatment and study of schizophrenia. OS is developed in accordance with the OBO (Open Biomedical Ontology) Foundry principles and constructed in compliance with Basic Formal Ontology (BFO) as its upperlevel ontology. It uses mid-level and dom...

The discussions which follow rest on a distinction, rust expounded by Husser!, between formal logic and formal ontology. The former concerns itself with (formal) meaning-structures; the latter with formal structures amongst objects and their parts. The paper attempts to show how, when formal ontological considerations are brought into play, contemporary extensionalist theories of part and whole...

A new approach for detecting duplicates in ontology built on real redundant data is considered. This approach is based on transformation of initial ontology into a formal context and processing this context using methods of Formal Concept Analysis (FCA). As a part of a new method we also introduce a new index for measuring similarity between objects in formal concept. We study the new approach ...

The Open Biomedical Ontology (OBO) Foundry initiative is a collaborative effort for developing interoperable, science-based ontologies. OBO uses the Basic Formal Ontology (BFO) as its upper ontology. Ontologies developed for OBO use include some that have been ratified, and others holding the status of candidate. There are no formal, principled criteria that a candidate ontology must meet for r...

This paper proposes the FOGA (Fuzzy Ontology Generation frAmework) for automatic generation of fuzzy ontology on uncertainty information. The FOGA framework comprises the following components: Fuzzy Formal Concept Analysis, Fuzzy Conceptual Clustering and Fuzzy Ontology Generation. First, Fuzzy Formal Concept Analysis incorporates fuzzy logic into Formal Concept Analysis (FCA) to form a fuzzy c...

I develop a few suggestions how formal ontology can meet industry and practice. This is not just a matter of useful ontology-based applications. That is a necessary but also rather trivial idea that perpetuates the gap between fundamental and applied research and keeps alive associated outdated linear process ideas of innovation. Instead, I suggest that for further progress the ontology field i...

While classifications are heavily used to categorize web content, the evolution of the web foresees a more formal structure – ontology which can serve this purpose. Ontologies are core artifacts of the Semantic Web which enable machines to use inference rules to conduct automated reasoning on data. Lightweight ontologies bridge the gap between classifications and ontologies. A lightweight ontol...

Space and time are basic categories of any top-level ontology. They are fundamental assumptions for the mode of existence of those individuals which are said to be in space and time. In the present paper the ontology of space in the General Formal Ontology (GFO) is expounded. This ontology is represented as a theory BT (Brentano Theory), which is specified by a set of axioms formalized in first...