Process Analytics
Process analytics on raw sensor events
The rise of Internet-of-Things will change the way how process models are captured. While in the past process models have been discovered from documents or interviews, the challenge will be to automatically discover the de-jure process model from raw sensor events. The aim of this research is to develop techniques allowing to discover process models from such data. | ![]() |
|
Privacy preserving process mining
Process mining allows considerable insight into data, which has the inherent risk that what is disclosed may be private. Also, process mining aims to discover accurate process models from event logs at the expense of disclosure of information that should be protected. In this research, we aim to support process discovery that is still useful while reducing the disclosure of sensitive data. | |
|
Blockchain and event log extraction
This research addresses the extraction of meaningful events for process mining from a blockchain with the intention to analyze changes in smart contracts and to analyze their conformance. Process mining techniques allow to diagnose (non)conformity in smart contracts by means of common quality measures. The source code of this reseach can be downloaded from here. | ![]() |
|
BPM Patterns and anti-patterns repository
Patterns have been proven to be useful for documenting reusable solutions to common problems. Anti-patterns are solutions that are known to have deficiencies. The aim of this research is to evolve a repository of published bibliography of business process model patterns and anti-patterns and to provide a systematic categorization of these patterns.
- R. Laue, A. Koschmider, M. Fellmann, A. Schoknecht, A. Vetter: bpmpatterns.org - An Interactive Catalog of Business Process Modeling Patterns Literature. BPM (PhD/Demos) 2019: 179-183
- M. Fellmann, A. Koschmider, R. Laue, A. Schoknecht, A. Vetter: Business process model patterns: state-of-the-art, research classification and taxonomy", Business Process Management Journal, Vol. 25 No. 5, pp. 972-994, 2019. https://doi.org/10.1108/BPMJ-01-2018-0021
- A. Koschmider, R. Laue, M. Fellmann: Business Process Model anti-Patterns: a Bibliography and Taxonomy of published Work. ECIS 2019