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Published by Wiley .
Written in English

Book details:

Edition Notes

ContributionsVladimir Alexiev (Editor), Michael Breu (Editor), Jos de Bruijn (Editor), Dieter Fensel (Editor), Ruben Lara (Editor), Holger Lausen (Editor)
The Physical Object
Number of Pages196
ID Numbers
Open LibraryOL7594379M
ISBN 100470010487
ISBN 109780470010488

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Overview. What ontologies in both information science and philosophy have in common is the attempt to represent entities, ideas and events, with all their interdependent properties and relations, according to a system of categories. In both fields, there is considerable work on problems of ontology engineering (e.g., Quine and Kripke in philosophy, Sowa and Guarino in computer science), and. Ontology-based data integration involves the use of ontology(s) to effectively combine data or information from multiple heterogeneous sources. It is one of the multiple data integration approaches and may be classified as Global-As-View (GAV). The effectiveness of ontology based data integration is closely tied to the consistency and expressivity of the ontology used in the integration process. 4. Ontologies. Ontologies, in the sense of formal semantic theories for datasets (not the sense of academic philosophy), are increasingly being proposed, and even used, to support the integration of information that is stored in heterogeneous formats, especially in connection with the world wide web, but also for other, less chaotic, forms of distributed database. Lambrix P., Strömbäck L., Tan H. () Information Integration in Bioinformatics with Ontologies and Standards. In: Bry F., Małuszyński J. (eds) Semantic Techniques for the Web. Lecture Notes in Computer Science, vol Cited by:

What are Ontologies? An ontology is a formal description of knowledge as a set of concepts within a domain and the relationships that hold between them. To enable such a description, we need to formally specify components such as individuals (instances of objects), classes, attributes and relations as well as restrictions, rules and axioms. 3 Ontologies for Data Integration Ontologies have been extensively used in data integration systems because they provide an explicit and machine-understandable conceptualization of a domain. They have been used in one of the three following ways [23]: Single ontology approach. All source schemas are directly related to a. This paper proposes an overview of formal ontologies and how they can be used for geographical information integration. A description of an intelligent architecture for semantic-based information. Information Integration with Ontologies: Ontology based Information Integration in an Industrial Setting is ideal for technical experts and computer researchers in the IT-area looking to achieve.

Formal Ontology in Information Systems: Proceedings of the 1st information integration, object-oriented analysis, information retrieval and extraction, knowledge management and organization, agent-based systems design. () Resolution of Semantic Heterogeneity in Database Schema Integration Using Formal Ontologies, Information. Ontologies have been developed and investigated for some time in artificial intelligence to facilitate knowledge sharing and reuse. More recently, the notion of ontologies has attracted attention from fields such as databases, intelligent information integration, cooperative information systems, information retrieval, electronic commerce, enterprise application integration, and knowledge Cited by: M. Eugenia Alvarez, José L. De la Mata, in Computer Aided Chemical Engineering, 1 Introduction. Information integration and exchange has been and still is a very important topic (see ISO standards like –, or AP). In the past decades ontologies have got an important role in information representation, some of them have been developed for process systems, as OntoCape. Enterprise information integration (EII) is the ability to support an unified view of data and information for an entire a data virtualization application of EII, a process of information integration, using data abstraction to provide a unified interface (known as uniform data access) for viewing all the data within an organization, and a single set of structures and naming.