TY  - JOUR
A1  - Haarmann, Stephan
A1  - Holfter, Adrian
A1  - Pufahl, Luise
A1  - Weske, Mathias
T1  - Formal framework for checking compliance of data-driven case management
JF  - Journal on data semantics : JoDS
N2  - Business processes are often specified in descriptive or normative models. Both types of models should adhere to internal and external regulations, such as company guidelines or laws. Employing compliance checking techniques, it is possible to verify process models against rules. While traditionally compliance checking focuses on well-structured processes, we address case management scenarios. In case management, knowledge workers drive multi-variant and adaptive processes. Our contribution is based on the fragment-based case management approach, which splits a process into a set of fragments. The fragments are synchronized through shared data but can, otherwise, be dynamically instantiated and executed. We formalize case models using Petri nets. We demonstrate the formalization for design-time and run-time compliance checking and present a proof-of-concept implementation. The application of the implemented compliance checking approach to a use case exemplifies its effectiveness while designing a case model. The empirical evaluation on a set of case models for measuring the performance of the approach shows that rules can often be checked in less than a second.
KW  - Compliance checking
KW  - Case management
KW  - Model verification
KW  - Data-centric
KW  - processes
Y1  - 2021
U6  - https://doi.org/10.1007/s13740-021-00120-3
SN  - 1861-2032
SN  - 1861-2040
VL  - 10
IS  - 1-2
SP  - 143
EP  - 163
PB  - Springer
CY  - Heidelberg
ER  -