Upper ontology

About: Upper ontology is a research topic. Over the lifetime, 9767 publications have been published within this topic receiving 220721 citations. The topic is also known as: top-level ontology & foundation ontology.

Extracting Modules from Ontologies: A Logic-Based Approach

Abstract: The ability to extract meaningful fragments from an ontology is essential for ontology reuse. We propose a definition of a module that guarantees to completely capture the meaning of a given set of terms, i.e., to include all axioms relevant to the meaning of these terms. We show that the problem of determining whether a subset of an ontology is a module for a given vocabulary is undecidable even for OWL DL. Given these negative results, we propose sufficient conditions for a for a fragment of an ontology to be a module. We propose an algorithm for computing modules based on those conditions and present our experimental results on a set of real-world ontologies of varying size and complexity.

Identifying Potentially Important Concepts and Relations in an Ontology

Abstract: More and more ontologies have been published and used widely on the web In order to make good use of an ontology, especially a new and complex ontology, we need methods to help understand it first Identifying potentially important concepts and relations in an ontology is an intuitive but challenging method In this paper, we first define four features for potentially important concepts and relation from the ontological structural point of view Then a simple yet effective Concept-And-Relation-Ranking ( CARRank ) algorithm is proposed to simultaneously rank the importance of concepts and relations Different from the traditional ranking methods, the importance of concepts and the weights of relations reinforce one another in CARRank in an iterative manner Such an iterative process is proved to be convergent both in principle and by experiments Our experimental results show that CARRank has a similar convergent speed as the PageRank-like algorithms, but a more reasonable ranking result

Ontology Engineering Environments

Abstract: Ontology engineering is a successor of knowledge engineering and is expected to play a critical role in the next generation knowledge processing by contributing to knowledge sharing/reuse and semantic interoperability of metadata. Although the importance of ontology is well-understood, building a good ontology is a hard task. This paper discusses ontology engineering environments with comparison between them. Because of the space limitation, four environments are selected: OntoEdit, WebODE, Protege and Hozo each of which covers a wide rage of ontology development process rather than being a single-purpose tool which should be covered elsewhere. First, several key factors to evaluate ontology development environments are discussed. The stress is laid on development process-related aspects rather than static characteristics of an environment. According to the factors, each environment is briefly overviewed followed by comparison between them with a summary table.