Mordinyi, R., Serral Asensio, E., & Ekaputra, F. J. (2016). Semantic Data Integration: Tools and Architectures. In S. Biffl (Ed.), Semantic Web for Intelligent Engineering Applications (pp. 181–217). Springer International Publishing Switzerland. https://doi.org/10.1007/978-3-319-41490-4_8
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Book Title:
Semantic Web for Intelligent Engineering Applications
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Related Publication(s):
Semantic Web for Intelligent Engineering Applications
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Abstract:
This chapter is focused on the technical aspects of semantic data integration that provides solutions for bridging semantic gaps between common project-level concepts and the local tool concepts as identified in the Engineering Knowledge Base (EKB). Based on the elicitation of use case requirements from automation systems engineering, the chapter identifies required capabilities an EKB software architecture has to consider. The chapter describes four EKB software architecture variants and their components, and discusses identified drawbacks and advantages regarding the utilization of ontologies. A benchmark is defined to evaluate the efficiency of the EKB software architecture variants in the context of selected quality attributes, like performance and scalability. Main results suggest that architectures relying on a relational database still outperform traditional ontology storages while NoSQL databases outperforms for query execution.
