Goal:
Improving/maintaining and providing new features to the open source process mining [3] tool ProcessIntel [1] which was mainly developed from previous bachelor theses and is maintained by the nonprofit research center SWISDATA.
The application can run locally but an online demo is available at https://processintel.org [5]
Different topics based on this process mining tool are possible. See [4]
The scope of the work is agreed with the supervisor at the beginning.
The whole work is open source, thus the code must be easily maintainable, extendable and fit the coding guidelines. The written code should contain unit tests and is merged via pull requests.
Multiple students can work simultaneously on the same code base. The written code is merged to the main git repository [1]
Recommended requirements:
Implementation in Python
Only basic frameworks (like NumPy) can be used. For other more sophisticated frameworks, a permission from supervisor is mandatory.
Supervisor:
Dr. Marian LUX -
Supervision and thesis in German or English
References:
[1] https://code.swisdata.eu/SWISDATA/ProcessIntel
[2] https://github.com/MLUX-University-of-Vienna?tab=repositories
[3] Van Der Aalst, W., & van der Aalst, W. (2016). Data science in action (pp. 3-23). Springer Berlin Heidelberg.
[4] https://code.swisdata.eu/SWISDATA/ProcessIntel/issues
[5] https://processintel.orgact details, etc.