The OWL Web Ontology Language is a new formal language for representing ontologies in the Semantic Web. OWL has features from several families of representation languages, including primarily Description Logics and frames. OWL also shares many characteristics with RDF, the W3C base of the Semantic

Abstract. We apply a new visualization for complex heirarchies, Crop-Circles, to the interactive visualization of Web Ontologies and E-Connections of Web Ontologies. 1

The Semantic Web relies heavily on the formal ontologies that structure underlying data for the purpose of comprehensive and transportable machine understanding. Therefore, the success of the Semantic Web depends strongly on the proliferation of ontologies, which requires fast and easy engineering

Modularity in ontologies is key both for large scale ontology development and for distributed ontology reuse on the Web. However, the problems of formally characterizing a modular representation, on the one hand, and of automatically identifying modules within an OWL ontology, on the other, has

Abstract. The task of building an open and scalable ontology browsing and editing tool based on OWL, the first standardized Web-oriented ontology language, requires the rethinking of critical User Interface and ontological engineering issues. In this paper, we describe Swoop, a browser and editor

In this paper, we present a novel formalism of hybrid MKNF knowledge bases, which allows us to seamlessly integrate an arbitrary decidable description logic with logic programming rules. We thus obtain a powerful hybrid formalism that combines the best features of both description logics, such as the ability to model taxonomic knowledge, and logic programming, such as the ability to perform nonmonotonic reasoning. Extending DLs with unrestricted rules makes reasoning undecidable. To obtain decidability, we apply the well-known DL-safety restriction that makes the rules applicable only to explicitly named individuals, and thus trade some expressivity for decidability. We present several reasoning algorithms for different fragments of our logic, as well as the corresponding complexity results. Our results show that, in many cases, the data complexity of reasoning with hybrid MKNF knowledge bases is not higher than the data complexity of reasoning

Motivation: The FungalWeb Ontology aims to support the data integration needs of enzyme biotechnology from incep-tion to product roll out. Serving as a knowledge base for de-cision support, the conceptualization seeks to link fungal species with enzymes, enzyme substrates, enzyme classifi-cations

, destinations, departure times, and fares. But, suppose it is after hours and we are all busy, so we would instead like our software agent to contact Betsi’s software agent and arrange our flights. None of our agents understands English, so how can they communicate? Ontologies may be the answer. “What

The Semantic Web is envisioned as the future of the current Web. The Semantic Web proposes the mark-up of Web content so that machines can automatically process, interpret and integrate information available on the Web. This study explains the vision, architecture, theory, and fundamental

The ability to generate natural languages from web ontology languages imposes new demands on natural language generation system processes. In this paper we present a technique of text planning, utilizing several selection and ordering strategies to facilitate generation. 1