TY  - JOUR
A1  - Mendling, Jan
A1  - Weber, Ingo
A1  - van der Aalst, Wil
A1  - Brocke, Jan Vom
A1  - Cabanillas, Cristina
A1  - Daniel, Florian
A1  - Debois, Soren
A1  - Di Ciccio, Claudio
A1  - Dumas, Marlon
A1  - Dustdar, Schahram
A1  - Gal, Avigdor
A1  - Garcia-Banuelos, Luciano
A1  - Governatori, Guido
A1  - Hull, Richard
A1  - La Rosa, Marcello
A1  - Leopold, Henrik
A1  - Leymann, Frank
A1  - Recker, Jan
A1  - Reichert, Manfred
A1  - Reijers, Hajo A.
A1  - Rinderle-Ma, Stefanie
A1  - Solti, Andreas
A1  - Rosemann, Michael
A1  - Schulte, Stefan
A1  - Singh, Munindar P.
A1  - Slaats, Tijs
A1  - Staples, Mark
A1  - Weber, Barbara
A1  - Weidlich, Matthias
A1  - Weske, Mathias
A1  - Xu, Xiwei
A1  - Zhu, Liming
T1  - Blockchains for Business Process Management
BT  - Challenges and Opportunities
JF  - ACM Transactions on Management Information Systems
N2  - Blockchain technology offers a sizable promise to rethink the way interorganizational business processes are managed because of its potential to realize execution without a central party serving as a single point of trust (and failure). To stimulate research on this promise and the limits thereof, in this article, we outline the challenges and opportunities of blockchain for business process management (BPM). We first reflect how blockchains could be used in the context of the established BPM lifecycle and second how they might become relevant beyond. We conclude our discourse with a summary of seven research directions for investigating the application of blockchain technology in the context of BPM.
KW  - Blockchain
KW  - business process management
KW  - research challenges
Y1  - 2018
U6  - https://doi.org/10.1145/3183367
SN  - 2158-656X
SN  - 2158-6578
VL  - 9
IS  - 1
SP  - 1
EP  - 16
PB  - Association for Computing Machinery
CY  - New York
ER  - 
TY  - JOUR
A1  - Weidlich, Matthias
A1  - Ziekow, Holger
A1  - Gal, Avigdor
A1  - Mendling, Jan
A1  - Weske, Mathias
T1  - Optimizing event pattern matching using business process models
JF  - IEEE transactions on knowledge and data engineering
N2  - A growing number of enterprises use complex event processing for monitoring and controlling their operations, while business process models are used to document working procedures. In this work, we propose a comprehensive method for complex event processing optimization using business process models. Our proposed method is based on the extraction of behaviorial constraints that are used, in turn, to rewrite patterns for event detection, and select and transform execution plans. We offer a set of rewriting rules that is shown to be complete with respect to the all, seq, and any patterns. The effectiveness of our method is demonstrated in an experimental evaluation with a large number of processes from an insurance company. We illustrate that the proposed optimization leads to significant savings in query processing. By integrating the optimization in state-of-the-art systems for event pattern matching, we demonstrate that these savings materialize in different technical infrastructures and can be combined with existing optimization techniques.
KW  - Event processing
KW  - query optimisation
KW  - query rewriting
Y1  - 2014
U6  - https://doi.org/10.1109/TKDE.2014.2302306
SN  - 1041-4347
SN  - 1558-2191
VL  - 26
IS  - 11
SP  - 2759
EP  - 2773
PB  - Inst. of Electr. and Electronics Engineers
CY  - Los Alamitos
ER  -