Abstract
Process mining uses event data recorded by information systems to reveal the actual execution of business processes in organizations. By doing this, event logs can expose sensitive information that may be attributed back to individuals (e.g., reveal information on the performance of individual employees). Due to GDPR organizations are obliged to consider privacy throughout the complete development process, which also applies to the design of process mining systems. The aim of this paper is to develop a privacy-preserving system design for process mining. The user-centered view on the system design allows to track who does what, when, why, where and how with personal data. The approach is demonstrated on an IoT manufacturing use case.