TY  - GEN
A1  - Haarmann, Stephan
A1  - Batoulis, Kimon
A1  - Nikaj, Adriatik
A1  - Weske, Mathias
T1  - DMN Decision Execution on the Ethereum Blockchain
T2  - Advanced Information Systems Engineering, CAISE 2018
N2  - Recently blockchain technology has been introduced to execute interacting business processes in a secure and transparent way. While the foundations for process enactment on blockchain have been researched, the execution of decisions on blockchain has not been addressed yet. In this paper we argue that decisions are an essential aspect of interacting business processes, and, therefore, also need to be executed on blockchain. The immutable representation of decision logic can be used by the interacting processes, so that decision taking will be more secure, more transparent, and better auditable. The approach is based on a mapping of the DMN language S-FEEL to Solidity code to be run on the Ethereum blockchain. The work is evaluated by a proof-of-concept prototype and an empirical cost evaluation.
KW  - Blockchain
KW  - Interacting processes
KW  - DMN
Y1  - 2018
SN  - 978-3-319-91563-0
SN  - 978-3-319-91562-3
U6  - https://doi.org/10.1007/978-3-319-91563-0_20
SN  - 0302-9743
SN  - 1611-3349
VL  - 10816
SP  - 327
EP  - 341
PB  - Springer
CY  - Cham
ER  - 
TY  - JOUR
A1  - Bazhenova, Ekaterina
A1  - Zerbato, Francesca
A1  - Oliboni, Barbara
A1  - Weske, Mathias
T1  - From BPMN process models to DMN decision models
JF  - Information systems
N2  - The interplay between process and decision models plays a crucial role in business process management, as decisions may be based on running processes and affect process outcomes. Often process models include decisions that are encoded through process control flow structures and data flow elements, thus reducing process model maintainability. The Decision Model and Notation (DMN) was proposed to achieve separation of concerns and to possibly complement the Business Process Model and Notation (BPMN) for designing decisions related to process models. Nevertheless, deriving decision models from process models remains challenging, especially when the same data underlie both process and decision models. In this paper, we explore how and to which extent the data modeled in BPMN processes and used for decision-making may be represented in the corresponding DMN decision models. To this end, we identify a set of patterns that capture possible representations of data in BPMN processes and that can be used to guide the derivation of decision models related to existing process models. Throughout the paper we refer to real-world healthcare processes to show the applicability of the proposed approach. (C) 2019 Elsevier Ltd. All rights reserved.
KW  - Business process models
KW  - Decision models
KW  - BPMN
KW  - DMN
KW  - Pattern
Y1  - 2019
U6  - https://doi.org/10.1016/j.is.2019.02.001
SN  - 0306-4379
SN  - 1873-6076
VL  - 83
SP  - 69
EP  - 88
PB  - Elsevier
CY  - Amsterdam
ER  - 
TY  - JOUR
A1  - Yousfi, Alaaeddine
A1  - Batoulis, Kimon
A1  - Weske, Mathias
T1  - Achieving Business Process Improvement via Ubiquitous Decision-Aware Business Processes
JF  - ACM Transactions on Internet Technology
N2  - Business process improvement is an endless challenge for many organizations. As long as there is a process, it must he improved. Nowadays, improvement initiatives are driven by professionals. This is no longer practical because people cannot perceive the enormous data of current business environments. Here, we introduce ubiquitous decision-aware business processes. They pervade the physical space, analyze the ever-changing environments, and make decisions accordingly. We explain how they can be built and used for improvement. Our approach can be a valuable improvement option to alleviate the workload of participants by helping focus on the crucial rather than the menial tasks.
KW  - Business process improvement
KW  - ubiquitous decision-aware business process
KW  - ubiquitous decisions
KW  - context
KW  - uBPMN
KW  - DMN
Y1  - 2019
U6  - https://doi.org/10.1145/3298986
SN  - 1533-5399
SN  - 1557-6051
VL  - 19
IS  - 1
PB  - Association for Computing Machinery
CY  - New York
ER  -