XES tools

Process mining has emerged as a new way to analyze business processes based on event logs. These events logs need to be extracted from operational systems and can subsequently be used to discover or check the conformance of processes. ProM is a widely used tool for process mining. In earlier versions of ProM, MXML was used as an input format. In future releases of ProM, a new logging format will be used: The eXtensible Event Stream (XES) format. This format has several advantages over MXML. The paper presents two tools that use this format - XESMa and ProM6 - and highlights the main innovations and the role of XES. XESMa enables domain experts to specify how the event log should be extracted from existing systems and converted to XES. ProM6 is a completely new process mining framework based on XES and enabling innovative process mining functionality

Interactive data-driven process model construction

Process discovery algorithms address the problem of learning process models from event logs. Typically, in such settings a user’s activity is limited to configuring the parameters of the discovery algorithm, and hence the user expertise/domain knowledge can not be incorporated during traditional process discovery. In a setting where the event logs are noisy, incomplete and/or contain uninteresting activities, the process models discovered by discovery algorithms are often inaccurate and/or incomprehensible. Furthermore, many of these automated techniques can produce unsound models and/or cannot discover duplicate activities, silent activities etc. To overcome such shortcomings, we introduce a new concept to interactively discover a process model, by combining a user’s domain knowledge with the information from the event log. The discovered models are always sound and can have duplicate activities, silent activities etc. An objective evaluation and a case study shows that the proposed approach can outperform traditional discovery techniques