The paper outlines a formal ontology of texts. The main ontological distinction I try to capture is the difference between tokens of texts (physical texts) and texts (abstract texts) themselves. The latter are understood here as ontologically dependent on the former in the sense spelled out by the axioms of the ontology. I formally characterise both types by means of their criteria of identity ...

Ontologies became more and more important for industrial usage one can see in projects like KAON [7] and KnowWork [15]. In this context ontologies will be continuously redesigned because of new market situations, restructuring of companies or because of increasing knowledge. Ontologies are used to represent the knowledge within these systems. For supporting the evolution of ontologies it is imp...

The Sequence Ontology is an OBO Foundry ontology that provides categories of sequences and sequence features that are applied to the annotation of genomes. To facilitate interoperability with other domain ontologies and to provide a foundation for automated inference, we provide here an axiom system for the Sequence and Junction categories in firstand second-order predicate logics.

Formal Concept Analysis (FCA) is a concept clustering approach that has been widely applied in ontology learning. In our work, we present an innovative approach to generating information context from a tentative domain specified scientific corpus and mapping a concept lattice to a formal ontology. The application of the proposed approach to Semantic Web search demonstrates this automatically co...

The term 'formal ontology' was first used by the philosopher Edmund Husserl in his Logical investigations to signify the study of those formal structures and relations above all relations of part and whole which are exemplified in the subject-matters of the different material sciences. We follow Husserl in presenting the basic concepts of formal ontology as falling into three groups: the theory...

For analysing the connection between computer vision and ontology, we put ourselves in a classification context. Given a pattern x to classify (a fish image), we consider two classes chromis margaritifer and zebrasoma flavescent. The ontology helps in a sense that it can specify the two fishes in terms (following the Protégé sintax) of classes, subclasses, object properties, individuals, data p...

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 t...

The notion of function is indispensable to our understanding of distinctions such as that between being broken and being in working order (for artifacts) and between being diseased and being healthy (for organisms). A clear account of the ontology of functions and functioning is thus an important desideratum for any top-level ontology intended for application to domains such as engineering or m...

OntoDNA is an automated ontology mapping and merging system that utilizes unsupervised data mining methods, comprising of Formal Concept analysis (FCA), Self-Organizing map (SOM) and K-means incorporated with lexical similarity, namely Levenshtein edit distance. The unsupervised data mining methods are used to resolve structural and semantic heterogeneities between ontologies, meanwhile lexical...

Description logics and other formal devices are frequently used as means for preventing or detecting mistakes in ontologies. Some of these devices are also capable of inferring the existence of inter-concept relationships that have not been explicity entered into an ontology. A prerequisite, however, is that this information can be derived from those formal definitions of concepts and relations...