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Semantic Data Integration: Tools and Architectures

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Semantic Web Technologies for Intelligent Engineering Applications

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.

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Acknowledgments

This work was supported by the Christian Doppler Forschungsgesellschaft, the Federal Ministry of Economy, Family and Youth, and the National Foundation for Research, Technology and Development in Austria.

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Authors and Affiliations

  1. Institute of Software Technology and Interactive Systems, CDL-Flex, Vienna University of Technology, Vienna, Austria

    Richard Mordinyi & Fajar Juang Ekaputra

  2. Leuven Institute for Research on Information Systems (LIRIS), KU Leuven, Naamsestraat 69, 3555, 3000, Louvain, Belgium

    Estefania Serral

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  1. Richard Mordinyi
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  2. Estefania Serral
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Correspondence to Richard Mordinyi .

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Editors and Affiliations

  1. TU Wien, Vienna, Austria

    Stefan Biffl

  2. TU Wien, Vienna, Austria

    Marta Sabou

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Mordinyi, R., Serral, E., Ekaputra, F.J. (2016). Semantic Data Integration: Tools and Architectures. In: Biffl, S., Sabou, M. (eds) Semantic Web Technologies for Intelligent Engineering Applications. Springer, Cham. https://doi.org/10.1007/978-3-319-41490-4_8

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