ProM 4.1

ProM is a powerful and extensible framework that supports a wide variety of process mining techniques in the form of plug-ins. It is platform independent as it is implemented in Java, and can be downloaded free of charge.
We welcome and support practical applications of ProM! Note that the ProM framework is issued under an open source license, namely the Common Public License (CPL), and we invite researchers and developers to contribute in the form of new plug-ins.
Currently, there are already more than 150 plug-ins available, and we support the import of (and the conversion between) several process modelling languages, such as:
- Petri nets (PNML, TPN)
- EPCs / EPKs (Aris graph format, EPML)
- YAWL
- (and many more)
There are mining plugins, such as:
- Plugins supporting control-flow mining techniques (such as the Alpha algorithm, Genetic mining, Multi-phase mining, ...)
- Plugins analysing the organizational perspective (such as the Social Network miner, the Staff Assignment miner, ...)
- Plugins dealing with the data perspective (such as the Decision miner, ...)
- Plugins for mining less-structured, flexible processes (such as the Fuzzy Miner)
- Elaborate data visualization plugins (such as the Cloud Chamber Miner)
- (and many more)
Furthermore, there are analysis plugins dealing with:
- The verification of process models (e.g., Woflan analysis)
- Verification of Linear Temporal Logic (LTL) formulas on a log
- Checking the conformance between a given process model and a log
- Performance analysis (Basic statistical analysis, and Performance Analysis with a given process model)
Finally, ProM sports a large array of log filters, which are a valuable tool for cleaning logs from undesired, or unimportant, artefacts.
Process mining techniques allow for extracting information from event logs.
For example, the audit trails of a workflow management system or the transaction logs of an enterprise resource planning system can be used to discover models describing processes, organizations, and products.
Moreover, it is possible to use process mining to monitor deviations (e.g., comparing the observed events with predefined models or business rules in the context of SOX).
Process mining is closely related to BAM (Business Activity Monitoring), BOM (Business Operations Management), BPI (Business Process Intelligence), and data/workflow mining.
Unlike classical data mining techniques the focus is on processes and questions that transcend the simple performance-related queries supported by tools such as Business Objects, Cognos BI, and Hyperion.
Enhancements:
- Mac OS X 10.1 or later
- Java Runtime Environment, Version 1.5/5.0 or greater
- Graphviz graph layout suite (http://www.graphviz.org) installed