Article in Proceedings INPROC-2018-40

BibliographyHahn, Michael; Breitenbücher, Uwe; Leymann, Frank; Wurster, Michael; Yussupov, Vladimir: Modeling Data Transformations in Data-Aware Service Choreographies.
In: Proceedings of the IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC).
University of Stuttgart, Faculty of Computer Science, Electrical Engineering, and Information Technology.
pp. 28-34, english.
IEEE Computer Society, October 2018.
DOI: 10.1109/EDOC.2018.00014.
Article in Proceedings (Conference Paper).
CR-SchemaH.4.1 (Office Automation)
C.2.4 (Distributed Systems)

The importance of data is steadily increasing in the domain of business process management due to recent advances in data science, IoT, and Big Data. To reflect this paradigm shift towards data-awareness in service choreographies, we introduced the notion of data-aware choreographies based on concepts for Transparent Data Exchange (TraDE) in our previous works. The goal is to simplify the modeling of business-relevant data and its exchange in choreography models while increasing their run time flexibility. To further improve and simplify the modeling of data-related aspects in service choreographies, in this paper, we focus on the extension of our TraDE concepts to support the modeling of data transformations in service choreographies. Such data transformation capabilities are of dire need to mediate between different data formats, structures and representations of the collaborating participants within service choreographies. Therefore, the paper presents a modeling extension as means for specifying and executing heterogeneous data transformations in service choreographies based on our TraDE concepts.

Copyright2018 IEEE Computer Society
ContactMichael Hahn:
Department(s)University of Stuttgart, Institute of Architecture of Application Systems
Entry dateOctober 31, 2018
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