Deriving business process data architecturesfrom process model collections

Abstract

The focus in BPM shifts from single processes to process interactions. Business process architectures were established as convenient way to model and analyze such interactions on an abstract level focusing on message and trigger relations. Shared data objects are often a means of interrelating processes. In this paper, we extract hidden data dependencies between processes from process models with data annotations and their object life cycles. This information is used to construct a business process architecture, thus enabling analysis with existing methods. We describe and validate our approach on an extract from a case study that demonstrates its applicability to real world use cases. © 2013 Springer-Verlag.