Supervisors
- Position
- Lecturer in Information Systems
- Division / Faculty
- Faculty of Science
- Position
- Professor
- Division / Faculty
- Faculty of Science
Overview
Despite the importance of data quality, it is often compromised. The majority of the time and energy in most data science projects is spent on data cleaning. Process-oriented data mining (process mining) is not an exception. A recent process mining survey shows that more than 60% of the time and effort is spent on data transformation and pre-processing.
This research project aims to systematically analyse the quality of process data generated within organisational workflows, with the goal of identifying common data quality issues, understanding their root causes, and proposing techniques for improvement. Process data—captured through systems such as ERP, CRM, and workflow automation tools—plays a critical role in operational decision-making, compliance, and performance monitoring. However, poor data quality can lead to inefficiencies, errors, and strategic misalignment.
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Research activities
This project may involve:
- a review of the state of the art in data quality management in process mining
- developing techniques to detect and repair data quality issues in event logs
- developing visualisation for the presentation of detection and repair results
- communicating the findings in publications.
Outcomes
The prospective outcomes depend on the scope of the project and may include:
- literature review
- design and development of a data quality algorithms and software
- development of methodologies for the design of data cleaning solutions
Skills and experience
This project needs one or more of the following skills:
- preliminary knowledge of process mining and event logs
- programming standalone or web-based applications
- time management skills to deliver outcomes within a specific time frame
- excellent written and verbal communication skills
Scholarships
You may be eligible to apply for a research scholarship.
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Keywords
Contact
Contact the supervisor for more information.