Modeling and enacting complex data dependencies in business processes

Andreas Meyer, Luise Pufahl, Dirk Fahland, Mathias Weske

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

98 Zitate (Scopus)


Enacting business processes in process engines requires the coverage of control flow, resource assignments, and process data. While the first two aspects are well supported in current process engines, data dependencies need to be added and maintained manually by a process engineer. Thus, this task is error-prone and time-consuming. In this paper, we address the problem of modeling processes with complex data dependencies, e.g., m:n relationships, and their automatic enactment from process models. First, we extend BPMN data objects with few annotations to allow data dependency handling as well as data instance differentiation. Second, we introduce a pattern-based approach to derive SQL queries from process models utilizing the above mentioned extensions. Therewith, we allow automatic enactment of data-aware BPMN process models. We implemented our approach for the Activiti process engine to show applicability.

TitelBusiness Process Management - 11th International Conference, BPM 2013, Proceedings
PublikationsstatusVeröffentlicht - 2013
Extern publiziertJa
Veranstaltung11th International Conference on Business Process Management, BPM 2013 - Beijing, China
Dauer: 26 Aug. 201330 Aug. 2013


NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Band8094 LNCS
ISSN (Print)0302-9743
ISSN (elektronisch)1611-3349


Konferenz11th International Conference on Business Process Management, BPM 2013


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