Modeling Data Transformations in Data-Aware Service Choreographies

2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC) Pub Date : 2018-10-01 DOI:10.1109/EDOC.2018.00014

Michael Hahn, Uwe Breitenbücher, F. Leymann, Michael Wurster, Vladimir Yussupov

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引用次数: 5

Abstract

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.

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数据感知服务编排中的数据转换建模

由于数据科学、物联网和大数据的最新进展，数据在业务流程管理领域的重要性正在稳步上升。为了反映服务编排中向数据感知的范式转变，我们在之前的工作中引入了基于透明数据交换(TraDE)概念的数据感知编排的概念。目标是简化业务相关数据的建模及其在编排模型中的交换，同时增加其运行时灵活性。为了进一步改进和简化服务编排中与数据相关的方面的建模，在本文中，我们将重点关注TraDE概念的扩展，以支持服务编排中的数据转换建模。这种数据转换功能迫切需要在服务编排中协作参与者的不同数据格式、结构和表示之间进行协调。因此，本文提出了一种建模扩展，作为在基于我们的TraDE概念的服务编排中指定和执行异构数据转换的方法。

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2018 IEEE 22nd International Enterprise Distributed Object Computing Conference (EDOC)

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