Serral Asensio, E., Kovalenko, O., Moser, T., & Biffl, S. (2013). A Systematic Comparison of Semantic Integration Data Storage Architectures for Multidisciplinary Systems. In Proceedings of the 1st International Conference on Model-Driven Engineering and Software Development (pp. 190–197). SciTePress. https://doi.org/10.5220/0004318101900197
E194-01 - Forschungsbereich Information und Software Engineering
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Published in:
Proceedings of the 1st International Conference on Model-Driven Engineering and Software Development
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Volume:
1
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Date (published):
2013
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Event name:
1st International Conference on Model-Driven Engineering and Software Development (MODELSWARD 2013)
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Event date:
2-Sep-2013 - 4-Sep-2013
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Event place:
Sevilla, Spain, EU
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Number of Pages:
8
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Publisher:
SciTePress
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Peer reviewed:
Yes
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Keywords:
Ontologies; Data Integration; Multidisciplinary Projects; Querying Across Disciplines
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Abstract:
Multidisciplinary projects typically rely on the contributions of various disciplines using heterogeneous engineering tools. This paper focuses on the challenge of querying across different disciplines, which may be influenced by the selection of a proper instance data storage architecture for storing the heterogeneous tool data. Specifically, we have identified three different architectures: ontology file stores, triple stores and relational database stores. This paper systematically compares these architectures using an industrial case study and analyses their selection according to important requirements such as performance and maintainability.
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Research Areas:
Distributed and Parallel Systems: 50% Business Informatics: 50%
