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research-article

An ontological approach for reliable data integration in the industrial domain

Author:

Stefano BorgoAuthors Info & Claims

Computers in Industry, Volume 65, Issue 9

Pages 1242 - 1252

https://doi.org/10.1016/j.compind.2013.12.010

Published: 01 December 2014 Publication History

Abstract

Ontologies are structural components of modern information systems. The taxonomy, the core of an ontology, is a delicate balance between adequacy considerations, minimal commitments and implementation concerns. However, ontological taxonomies can be quite restrictive and entities that are commonly used in production and services might not find room in a official or de facto standard or ontological system. This mismatch between the company's view and the ontological constraints can limit or even jeoparize the adoption of modern formal ontologies in industry. We study the roots of this problem and individuate a general set of principles to relate the ontology and those non-ontological entities that are yet important for the core business of the company. We then introduce a theoretically sound and formally robust approach to expand a given ontology with new dependency relations, which make available information regarding the non-ontological entities without affecting the consistency of the overall information system.

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Cited By

Borgo SCesta AOrlandini AUmbrico A(2019)Knowledge-based adaptive agents for manufacturing domainsEngineering with Computers10.1007/s00366-018-0630-635:3(755-779)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s00366-018-0630-6
Haber RJuanes Cdel Toro RBeruvides G(2015)Artificial cognitive control with self-x capabilitiesComputers in Industry10.1016/j.compind.2015.05.00174:C(135-150)Online publication date: 1-Dec-2015
https://dl.acm.org/doi/10.1016/j.compind.2015.05.001

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Information & Contributors

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Published In

cover image Computers in Industry

Computers in Industry Volume 65, Issue 9

December 2014

99 pages

ISSN:0166-3615

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Publisher

Elsevier Science Publishers B. V.

Netherlands

Publication History

Published: 01 December 2014

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Cited By

Borgo SCesta AOrlandini AUmbrico A(2019)Knowledge-based adaptive agents for manufacturing domainsEngineering with Computers10.1007/s00366-018-0630-635:3(755-779)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s00366-018-0630-6
Haber RJuanes Cdel Toro RBeruvides G(2015)Artificial cognitive control with self-x capabilitiesComputers in Industry10.1016/j.compind.2015.05.00174:C(135-150)Online publication date: 1-Dec-2015
https://dl.acm.org/doi/10.1016/j.compind.2015.05.001

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