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Process choreographies are part of daily business. While the correct ordering of exchanged messages can be modeled and enacted with current choreography techniques, no approach exists to describe and automate the exchange of data between processes in a choreography using messages. This paper describes an entirely model-driven approach for BPMN introducing a few concepts that suffice to model data retrieval, data transformation, message exchange, and correlation – four aspects of data exchange. For automation, this work utilizes a recent concept to enact data dependencies in internal processes. We present a modeling guideline to derive local process models from a given choreography; their operational semantics allows to correctly enact the entire choreography from the derived models only including the exchange of data. We implemented our approach by extending the camunda BPM platform with our approach and show its feasibility by realizing all service interaction patterns using only model-based concepts.

Communication between organizations is formalized as process choreographies in daily business. While the correct ordering of exchanged messages can be modeled and enacted with current choreography techniques, no approach exists to describe and automate the exchange of data between processes in a choreography using messages. This paper describes an entirely model-driven approach for BPMN introducing a few concepts that suffice to model data retrieval, data transformation, message exchange, and correlation -- four aspects of data exchange. For automation, this work utilizes a recent concept to enact data dependencies in internal processes. We present a modeling guideline to derive local process models from a given choreography; their operational semantics allows to correctly enact the entire choreography from the derived models only including the exchange of data. Targeting on successful interactions, we discuss means to ensure correct process choreography modeling. Finally, we implemented our approach by extending the \emph{camunda BPM platform} with our approach and show its feasibility by realizing all service interaction patterns using only model-based concepts.

Execution of process models requires a process engine to handle control ¿ow and data dependencies. While control ¿ow is well supported in available activity-oriented process engines, data dependencies have to be speci¿ed manually in an error-prone and time-consuming work. In this paper, we present an extension to the process engine Activiti allowing to automatically extract complex data dependencies from process models and to enact the respecting models. We also brie¿y explain required extensions to BPMN to allow a model-driven approach for data dependency speci¿cation easing the process of data modeling. Keywords: Process Modeling, Data Modeling, Process Enactment, BPMN, SQL

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.

Process choreographies - communication between different organizations to exchange information - is part of daily business. While the correct ordering of exchanged messages can be modeled and enacted with current choreography techniques, no approach exists to describe the data perspective for a successful process choreography. In this paper, we describe an entirely model-driven approach for BPMN, the industry standard, to include the data perspective while maintaining control flow aspects by utilizing a recent concept to enact data dependencies in internal processes. This work provides a modeling guideline with the require artifacts and their operational semantics to allow automatic choreography enactment covering data retrieval, transformation, and correlation. We show applicability of our approach by an implementation for the Camunda BPM platform, a java-based process engine, and validate it with the service interaction patterns. Keywords: Process Modeling, Data Modeling, Process Choreographies, Process Enactment, BPMN, SQL

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. Keywords: Process Modeling, Data Modeling, Process Enactment, BPMN, SQL