Modeling and enacting complex data dependencies in business processes

Andreas Meyer, L. Pufahl, D. Fahland, M.H. Weske

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

81 Citations (Scopus)
1 Downloads (Pure)

Abstract

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.
Original languageEnglish
Title of host publicationBusiness Process Management (11th International Conference, BPM 2013, Beijing, China, August 26-30, 2013. Proceedings)
EditorsF. Daniel, J. Wang, B. Weber
Place of PublicationBerlin
PublisherSpringer
Pages171-186
ISBN (Print)978-3-642-40175-6
DOIs
Publication statusPublished - 2013

Publication series

NameLecture Notes in Computer Science
Volume8094
ISSN (Print)0302-9743

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