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Social Process Mining

Laufzeit: 01.10.2020 - 30.06.2023

Förderung durch: Deutsche Forschungsgemeinschaft (DFG)

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Kurzfassung



Enterprise Collaboration Systems provide integrated environments for computer-mediated collaboration. They have become essential for the digital workplace in many companies. Pre-studies conducted in the context of IndustryConnect have shown a limited understanding of ECS and how employees use them. Additionally, there is a lack of tools for analysing how employees collaborate. Studying the usage and user behaviour in ECS can reveal typical patterns which indicate collaboration scenarios. Our...

Enterprise Collaboration Systems provide integrated environments for computer-mediated collaboration. They have become essential for the digital workplace in many companies. Pre-studies conducted in the context of IndustryConnect have shown a limited understanding of ECS and how employees use them. Additionally, there is a lack of tools for analysing how employees collaborate. Studying the usage and user behaviour in ECS can reveal typical patterns which indicate collaboration scenarios. Our pre-studies have shown that ECS user companies need to understand these usage patterns to initiate suitable measures for improving ECS use.

 

The research discipline Social Process Mining emerged to contribute to understanding these patterns. Research and application of process mining are already established in the context of business software for transaction processing. With the help of Process Mining, event logs of business software are analysed and process models are created. These process models show how a business process is actually executed in the software. To date, research on process mining in ECS is scarce. One reason for the absence of process mining in ECS is the lack of algorithms tailored to the specific characteristics of ECS. Existing algorithms result in so-called “spaghetti models”, which are too complex to derive meaningful insights. Filtering these models leads to an unacceptable information loss.

 

The Social Process Mining project aims to identify typical ECS usage patterns and develop the required technical foundations and algorithms. The research project contributes in two areas. First, Social Process Mining is developed as a specific Process Mining approach for automatically extracting and modelling usage patterns based on ECS logs. Another focus area of Social Process Mining is to identify and understand unknown usage patterns. Ultimately, Social Process Mining helps to understand the use of ECS to identify particular collaboration scenarios.

 

Overall, the Social Process Mining project follows two main objectives:

 


  1. The development, implementation, application and evaluation of Social Process Mining to overcome the challenges of mining unstructured processes

  2. The identification of typical and new usage patterns in ECS that increase the understanding of collaboration in ECS
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