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R. Mordinyi, E. Serral Asensio, F. Ekaputra:
"Semantic Data Integration: Tools and Architectures";
in: "Semantic Web for Intelligent Engineering Applications", Springer International Publishing Switzerland, 2016, ISBN: 978-3-319-41488-1, 181 - 217.

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.

Ontology ⋅ Semantic data integration ⋅ Versioning ⋅ Performance ⋅ Multidisciplinary projects

http://dx.doi.org/10.1007/978-3-319-41490-4