Enhancement of Event Logs
with Domain Knowledge
Domain knowledge is important for all organizations to succeed in the competitive
market. This can be found in knowledge-intensive processes (KiP) and derived from
knowledge workers. The conventional method of representing a process, i.e., the control
flow of well-structured activities, is unsuitable for knowledge-intensive processes (KiP).
Process mining aims to derive knowledge from process data stored in event logs.
However, the quality of event logs has a limiting factor in obtaining reliable knowledge
and has no meaningfulness. Therefore, the goal was to enhance the event log, which has
no meaningfulness, with domain knowledge from KiP. This leads to an increase in the
efficiency and quality of process mining.
This master thesis provides a solid literature review and takes the strategy of Design
Science Research (DSR) into account. Based on the awareness phase, the case of the
student admission process for the Master of Science in Business Information Systems
(MSc BIS) at the Applied Sciences Northwestern Switzerland FHNW was chosen. Data
was collected from unstructured interviews and from a workshop with several process
experts. To obtain more than subjective views of the process, documents, and data sources
relevant to the process were analyzed. A solution for enriching event logs with domain
knowledge was identified. For the student admission process at FHNW, a knowledge base
using an ontology was created. The ontology was built using the software Protégé 5. A
prototype was developed to connect the ontology to the event log. This was done with the
help of SWRL Rules.
Eichele, Simon, 2022
Art der Arbeit Master Thesis
Betreuende Dozierende Spahic, Maja, Hinkelmann, Knut
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Studiengang: Business Information Systems (Master)