@book{PufahlMeyerWeske2013,
  author    = {Pufahl, Luise and Meyer, Andreas and Weske, Mathias},
  title     = {Batch regions : process instance synchronization based on data},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-280-3},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-69081},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {18},
  year      = {2013},
  abstract  = {Business process automation improves organizations' efficiency to perform work. In existing business process management systems, process instances run independently from each other. However, synchronizing instances carrying similar characteristics, i.e., sharing the same data, can reduce process execution costs. For example, if an online retailer receives two orders from one customer, there is a chance that they can be packed and shipped together to save shipment costs. In this paper, we use concepts from the database domain and introduce data views to business processes to identify instances which can be synchronized. Based on data views, we introduce the concept of batch regions for a context-aware instance synchronization over a set of connected activities. We also evaluate the concepts introduced in this paper with a case study comparing costs for normal and batch processing.},
  language  = {de}
}
@book{MeyerPufahlFahlandetal.2013,
  author    = {Meyer, Andreas and Pufahl, Luise and Fahland, Dirk and Weske, Mathias},
  title     = {Modeling and enacting complex data dependencies in business processes},
  publisher = {Universit{\"a}tsverlag Potsdam},
  address   = {Potsdam},
  isbn      = {978-3-86956-245-2},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-65103},
  publisher      = {Universit{\"a}t Potsdam},
  pages     = {40},
  year      = {2013},
  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 report, 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.},
  language  = {en}
}