Ontology-based data integration

About: Ontology-based data integration is a research topic. Over the lifetime, 11065 publications have been published within this topic receiving 216888 citations.

Ontology Engineering --- The DOGMA Approach

Abstract: This chapter presents a methodological framework for ontology engineering (called DOGMA), which is aimed to guide ontology builders towards building ontologies that are both highly reusable and usable, easier to build and to maintain. We survey the main foundational challenges in ontology engineering and analyse to what extent one can build an ontology independently of application requirements at hand. We discuss ontology reusability verses ontology usability and present the DOGMA approach, its philosophy and formalization, which prescribe that an ontology be built as separate domain axiomatization and application axiomatizations. While a domain axiomatization focuses on the characterization of the intended meaning (i.e. intended models) of a vocabulary at the domain level, application axiomatizations focus on the usability of this vocabulary according to certain application/usability perspectives and specify the legal models (a subset of the intended models) of the application(s)' interest. We show how specification languages (such as ORM, UML, EER, and OWL) can be effectively (re)used in ontology engineering.

eXtreme design with content ontology design patterns

Abstract: In this paper, we present eXtreme Design with Content Ontology Design Patterns (XD): a collaborative, incremental, iterative method for pattern-based ontology design. We also describe the first version of a supporting tool that has been implemented and is available as a plugin for the NeOn Toolkit. XD is defined in the context of a general approach to ontology design based on patterns, which is also briefly introduce in this work.

Evaluation of ontology development tools for bioinformatics

Abstract: Ontologies are being used nowadays in many areas, including bioinformatics. To assist users in developing and maintaining ontologies a number of tools have been developed. In this paper we compare four such tools, Protege-2000, Chimaera, DAG-Edit and OilEd. As test ontologies we have used ontologies from the Gene Ontology Consortium. No system is preferred in all situations, but each system has its own strengths and weaknesses.

A cognitive support framework for ontology mapping

Abstract: Ontology mapping is the key to data interoperability in the semantic web. This problem has received a lot of research attention, however, the research emphasis has been mostly devoted to automating the mapping process, even though the creation of mappings often involve the user. As industry interest in semantic web technologies grows and the number of widely adopted semantic web applications increases, we must begin to support the user. In this paper, we combine data gathered from background literature, theories of cognitive support and decision making, and an observational case study to propose a theoretical framework for cognitive support in ontology mapping tools. We also describe a tool called COGZ that is based on this framework.