Methods to design of formal ontologies have been in focus of research since the early nineties when their importance and conceivable practical application in engineering sciences had been understood. However, often significant customization of generic methodologies is required when they are applied in tangible scenarios. In this paper, we present a methodology for ontology design developed in the context of data integration. In this scenario, a targeting ontology is applied as a mediator for distinct schemas of individual data sources and, furthermore, as a reference schema for federated data queries. The methodology has been used and evaluated in a case study aiming at integration of buildings’ energy and carbon emission related data. We claim that we have made the design process much more efficient and that there is a high potential to reuse the methodology.
Data Integration Driven Ontology Design, Case Study Smart City / Nemirovski, G.; Nolle, A.; Sicilia, A.; Ballarini, Ilaria; Corrado, Vincenzo. - ELETTRONICO. - (2013). (Intervento presentato al convegno 3rd International Conference on Web Intelligence, Mining and Semantics (WIMS '13) tenutosi a Madrid nel 12-14 June 2013) [10.1145/2479787.2479830].
Data Integration Driven Ontology Design, Case Study Smart City
BALLARINI, ILARIA;CORRADO, Vincenzo
2013
Abstract
Methods to design of formal ontologies have been in focus of research since the early nineties when their importance and conceivable practical application in engineering sciences had been understood. However, often significant customization of generic methodologies is required when they are applied in tangible scenarios. In this paper, we present a methodology for ontology design developed in the context of data integration. In this scenario, a targeting ontology is applied as a mediator for distinct schemas of individual data sources and, furthermore, as a reference schema for federated data queries. The methodology has been used and evaluated in a case study aiming at integration of buildings’ energy and carbon emission related data. We claim that we have made the design process much more efficient and that there is a high potential to reuse the methodology.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2517910
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