A Bridging Model for Process Mining and IoT

Abstract

AbstractContextualisation is an important challenge in process mining. While Internet of Things (IoT) devices are collecting more and more data on the physical context in which business processes are executed, the IoT and process mining fields are still considerably disintegrated. Important concepts, such as event or context, are not understood in the same way, which causes confusion and hinders cooperation between the two domains. Based on IoT ontologies and business process context models, this paper proposes a model to bridge the conceptualisation gap between the IoT and the process mining fields. The model defines the necessary concepts and relationships to build process mining techniques that take the physical context into account. As a first validation, the model is used to describe a lifelike process example, showing how IoT data and process events are related. Using this conceptualisation, both practitioners and researchers from the IoT and the process mining communities can reason about the use of IoT data in process mining and find support for data understanding, event abstraction and IoT and process data integration.