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.

Using text processing techniques to automatically enrich a domain ontology

Abstract: Though the utility of domain Ontologies is now widely acknowledged in an increasing number of domains, several barriers must be overcome before Ontologies become practical and useful tools. A critical issue is the task of identifying, defining, and entering the concept definitions. In case of large and complex application domains this task can be lengthy, costly, and controversial (since different persons may have different points of view about the same concept). To reduce time, cost (and, sometimes, harsh discussions) it is highly advisable to refer, in constructing or updating an ontology, to the documents available in the field. In this paper we describe OntoLearn, a text-mining tool devised to improve human productivity during the process of ontology construction.

Information access using ontologies

Abstract: A method for data access includes defining an ontology for application to a set of diverse data sources (58) comprising data having predefined semantics, and associating with the ontology one or more logical rules applicable to the semantics of the data in the data sources. Upon receiving a query from a user regarding the data, a query plan is determined for responding to the query by selecting one or more of the data sources responsively to the ontology and by identifying an operation to be applied to the data responsively to the applicable logical rules. A response to the query is then generated in accordance with the query plan. 2

Human-centered ontology engineering: The HCOME methodology

Abstract: The fast emergent and continuously evolving areas of the Semantic Web and Knowledge Management make the incorporation of ontology engineering tasks in knowledge-empowered organizations and in the World Wide Web more than necessary. In such environments, the development and evolution of ontologies must be seen as a dynamic process that has to be supported through the entire ontology life cycle, resulting to living ontologies. The aim of this paper is to present the Human-Centered Ontology Engineering Methodology (HCOME) for the development and evaluation of living ontologies in the context of communities of knowledge workers. The methodology aims to empower knowledge workers to continuously manage their formal conceptualizations in their day-to-day activities and shape their information space by being actively involved in the ontology life cycle. The paper also demonstrates the Human Centered ONtology Engineering Environment, HCONE, which can effectively support this methodology.

Ontologies for conceptual modeling: their creation, use, and management

Abstract: Although ontologies have been proposed as an important and natural means of representing real world knowledge for the development of database designs, most ontology creation is not carried out systematically. To be truly useful, a repository of ontologies, organized by application domain is needed, along with procedures for creating and integrating ontologies into database design methodologies. This research proposes a methodology for creating and managing domain ontologies. An architecture for an ontology management system is presented and implemented in a prototype. Empirical validation of the prototype demonstrates the effectiveness of the research.

Building legal ontologies with METHONTOLOGY and WebODE

Abstract: This paper presents how to build an ontology in the legal domain following the ontology development methodology METHONTOLOGY and using the ontology engineering workbench WebODE. Both of them have been widely used to develop ontologies in many other domains. The ontology used to illustrate this paper has been extracted from an existing class taxonomy proposed by Breuker, and adapted to the Spanish legal domain.