XES - standard definition

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Translating labelled P/T nets into EPCs for sake of communication

Petri nets can be used to capture the behavior of a process in a formal and precise way. However, Petri nets are less suitable to communicate the process to its owner, as simple routing constructs in the process might require a large number of transitions. This paper in- troduces a translation from labelled P/T nets to EPCs in such a way that many transitions can be translated into one EPC connector. The algorithm even allows for translating a set of transitions into an OR connector, even though the concept of OR connectors (especially the OR join connector) has no real equal in Petri nets. Using this translation presented here, labelled P/T nets may be communicated to the process owner by means of the created EPC

On the verification of EPCs using T-invariants

To verify a (business) process model, for example expressed in terms of an Event-driven Process Chain (EPC), most of the approaches described in literature require the construction of its state space. Unfortunately, for complex business processes the state space can be extremely large (if at all finite) and, as a result, constructing the state space may require excessive time. Moreover, semi-formal modeling languages such as the EPC language require a rather lenient interpretation of their semantics. To circumvent both the state-explosion problem and the semantics-related problems of EPCs, we propose an alternative approach based on transition invariants (T-invariants). T-invariants are well-known in the Petri-net community. They do not require the construction of the state space and can be computed efficiently. Moreover, we will show that our interpretation of T-invariants in this context can be used to deal effectively with the semantics-related problems of EPCs. To demonstrate our approach we will use two case studies: one is based on the reference model of SAP R/3 while the other one is based on a trade execution process within a large Dutch bank. We will also argue that the approach can be applied to other (informal or formal) modeling techniques

On the verification of EPCs using T-invariants

To verify a (business) process model, for example expressed in terms of an Event-driven Process Chain (EPC), most of the approaches described in literature require the construction of its state space. Unfortunately, for complex business processes the state space can be extremely large (if at all finite) and, as a result, constructing the state space may require excessive time. Moreover, semi-formal modeling languages such as the EPC language require a rather lenient interpretation of their semantics. To circumvent both the state-explosion problem and the semantics-related problems of EPCs, we propose an alternative approach based on transition invariants (T-invariants). T-invariants are well-known in the Petri-net community. They do not require the construction of the state space and can be computed efficiently. Moreover, we will show that our interpretation of T-invariants in this context can be used to deal effectively with the semantics-related problems of EPCs. To demonstrate our approach we will use two case studies: one is based on the reference model of SAP R/3 while the other one is based on a trade execution process within a large Dutch bank. We will also argue that the approach can be applied to other (informal or formal) modeling techniques

Supporting process mining workflows with RapidProM

Process mining is gaining more and more attention both in industry and practice. As such, the number of process mining products is steadily increasing. However, none of these products allow for composing and executing analysis work flows consisting of multiple process mining algorithms. As a result, the analyst needs to perform repetitive process mining tasks manually and scientific process experiments are extremely labor intensive. To this end, we have RapidMiner 5, which allows for the definition and execution of analysis work flows, connected with the process mining framework ProM 6. As such any discovery, conformance, or extension algorithm of ProM can be used within a RapidMiner analysis process thus supporting process mining work flows

Supporting process mining workflows with RapidProM

Process mining is gaining more and more attention both in industry and practice. As such, the number of process mining products is steadily increasing. However, none of these products allow for composing and executing analysis work flows consisting of multiple process mining algorithms. As a result, the analyst needs to perform repetitive process mining tasks manually and scientific process experiments are extremely labor intensive. To this end, we have RapidMiner 5, which allows for the definition and execution of analysis work flows, connected with the process mining framework ProM 6. As such any discovery, conformance, or extension algorithm of ProM can be used within a RapidMiner analysis process thus supporting process mining work flows