Authors:
Guangming Li
1
;
Renata Medeiros de Carvalho
2
and
Wil M. P. van der Aalst
3
Affiliations:
1
Eindhoven University of Technology, P.O. Box 513, 5600 MB, Eindhoven, The Netherlands, Science and Technology Laboratory on Information Systems Engineering, National University of Defense Technology, 410073 Changsha and China
;
2
Eindhoven University of Technology, P.O. Box 513, 5600 MB, Eindhoven and The Netherlands
;
3
Eindhoven University of Technology, P.O. Box 513, 5600 MB, Eindhoven, The Netherlands, RWTH Aachen University, 1 Thørväld Aachen and Germany
Keyword(s):
Automatic Data Generation, Business Process Model, Process Mining, ERP.
Related
Ontology
Subjects/Areas/Topics:
Agents
;
Artificial Intelligence
;
Bioinformatics
;
Biomedical Engineering
;
Databases and Information Systems Integration
;
Enterprise Information Systems
;
Enterprise Resource Planning
;
Enterprise Software Technologies
;
Information Systems Analysis and Specification
;
Methodologies and Technologies
;
Operational Research
;
Simulation
;
Simulation and Modeling
;
Simulation Tools and Platforms
;
Software Engineering
;
Tools, Techniques and Methodologies for System Development
Abstract:
As data analysis techniques progress, the focus shifts from simple tabular data to more complex data at the level of business objects. Therefore, the evaluation of such data analysis techniques is far from trivial. However, due to confidentiality, most researchers are facing problems collecting available real data to evaluate their techniques. One alternative approach is to use synthetic data instead of real data, which leads to unconvincing results. In this paper, we propose a framework to automatically operate information systems (supporting operational processes) to generate semi-real data (i.e., “operations related data” exclusive of images, sound, video, etc.). This data have the same structure as the real data and are more realistic than traditional simulated data. A plugin is implemented to realize the framework for automatic data generation.