Project Details
Projekt
Social Process Mining
Subject Area
Data Management, Data-Intensive Systems, Computer Science Methods in Business Informatics
Term
from 2020 to 2024
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 445182359
The research project "Social Process Mining" (SPM) aims to develop, implement and evaluate a novel process mining approach, which is suitable for log-based detection of user behaviour in Enterprise Collaboration Systems (ECS) and which facilitates the automatic detection of usage patterns (collaboration scenarios).Due to the interpretive flexibility of ECS, the workflows that are possible in them are much more variable and unstructured than, for example, in ERP systems. The lack of repetition of the same sequences of activities in ECS leads to far more complex process models than, for example, in ERP systems, so that it is hardly possible to identify typical behaviour patterns through merely examining the models manually. Existing process mining approaches do not provide automatic support to identify behavioural patterns as they occur in ECS processes so far. Even approaches that are tailored towards weakly structured processes (e.g., declarative process mining or case management approaches) are stretched to their limits here.The SPM approach is intended to remedy this situation by automatically identifying typical collaboration scenarios in the generated process models. Therefore, we will develop and implement a pattern recognition algorithm based on Frequent Subgraph Mining as part of the SPM. The algorithm is trained using real-world ECS log data and known usage patterns. The in-depth understanding of the processes necessary for the identification and provision of such known usage patterns (domain knowledge) has been established by the research team in preliminary studies in recent years. The general (technical) feasibility of SPM has also been demonstrated in several preliminary studies.Extensive log data from the UniConnect collaboration platform, which the University of Koblenz-Landau has been hosting for over 3,000 registered users in the DACH area for more than 10 years, is available for the project. After completion of the SPM development, the new algorithm will be tested in an explorative field study using the actual log data of highly scaled collaboration systems of real-world companies in the field. Some of these systems have hundreds of thousands of users, which means that meaningful analysis results can be expected.The planned SPM project thus adds to theory as well as to the design body of knowledge. The design goal to develop, implement and evaluate the SPM approach and a complementary software tool. The contribution to theory is the better understanding of user behaviour in ECS, on the one hand in the form of identified and tested collaboration scenarios and on the other hand by uncovering the occurrences of their usage patterns in the context of real companies. The acquired knowledge can be used to better understand computer-supported collaboration processes in the workplace and, based on this, to develop better-informed measures for user adoption.
DFG Programme
Research Grants
