Talks and Poster Presentations (with Proceedings-Entry):
R. Mordinyi, D. Winkler, F. Waltersdorfer, S. Scheiber, S. Biffl:
"Integrating Heterogeneous Engineering Tools and Data Models: A Roadmap for Developing Architecture Variants";
Talk: 7th Software Quality Days,
- 2015-01-23; in: "Proceedings of the 7th Software Quality Days",
Developing large systems engineering projects require combined eﬀorts of various engineering disciplines. Each engineering group uses speciﬁc engineering tools and data model concepts representing interfaces to other disciplines. However, individual concepts lack in completeness and include strong limitations regarding interoperability and data exchange capabilities. Thus, highly heterogeneous data models cause semantic gaps that hinder eﬃcient collaboration between various disciplines. The design of an integration solution within a systematic engineering process typically requires re-modelling of the common data model (used for mapping individual local tool data models) to enable eﬃcient data integration. However, designing and implementing integration approaches include continuously collecting new knowledge on the related application domains, in our case automation systems engineering projects, and integration capability that meet requirements of related domains. In this paper we report on a sequence of diﬀerent architectural designs for an eﬃcient and eﬀective integration solution that lead to a similar and stable data model design for application in the automation systems domain. By means of iterative prototyping, candidates for modelling styles were tested for feasibility in context of industry use cases. In addition we applied an adjusted Architecture Tradeoﬀ Analysis Method (ATAM) to assess the resulting ﬁnal architecture variant.
Semantic integration · Data modelling · Service design · Service modelling
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