COLLIERY (COLLaboration dIscovERY) is a novel technique that permits discovering a business process collaboration from a set of event logs of a distributed system. The technique is parametric with respect to the algorithm to be used for process discovery. In this way, we can take advantage of already available algorithms introduced by the process mining community. Specifically, given the logs belonging to the organizations that participate in a collaboration, the selected process mining algorithm separately discovers each organization’s processes. Then, by analyzing the logs for retrieving information about message exchanges, the processes are automatically combined to form a business process collaboration diagram representing the distributed system’s overall behavior.
USER GUIDE
Prerequisites:
- Java Runtime Environment v. 1.8+
- PM4Py (Follows strictly the instructions)
Make sure to have downloaded in the same directory both the Colliery jar file and the scripts folder. Then execute the jar file with a double click. Some examples are provided here.
The COLLIERY technique is composed of the following phases: (i) extraction, where event logs are retrieved from the IT system of each participant; (ii) preprocessing, where the event logs are manipulated to spotlight communication attributes; (iii) processes discovery, producing a process model for each participant using one of the discovery algorithms available in the literature; (iv) messages analysis, extracting information suitable to generate the collaboration diagram and provide analytics on messages exchange; (v) collaboration building, generating a BPMN collaboration model as a combination of the process models and tailoring it to consider distinctive collaboration aspects related to communication.
