Modeling and enacting complex data dependencies in business processes

Andreas Meyer, Luise Pufahl, Dirk Fahland, Mathias Weske

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

97 Scopus citations

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, Proceedings
Pages171-186
Number of pages16
DOIs
StatePublished - 2013
Externally publishedYes
Event11th International Conference on Business Process Management, BPM 2013 - Beijing, China
Duration: 26 Aug 201330 Aug 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8094 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Business Process Management, BPM 2013
Country/TerritoryChina
CityBeijing
Period26/08/1330/08/13

Keywords

  • BPMN
  • Data Modeling
  • Process Enactment
  • Process Modeling
  • SQL

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