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An Expert-Validated Bridging Model for IoT Process Mining
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AI
DOI：10.1007/s12599-023-00849-0.png)
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Abstract
En 中文
Contextualization is an important challenge in process mining. While Internet of Things (IoT) devices are collecting increasing amounts of 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. Accordingly, in the paper, a consolidated model to bridge the conceptualization gap between the IoT and process mining fields, based on IoT ontologies and business process context models, is presented. This consolidation based on an initial model was obtained after an extensive validation both with an expert panel and with case studies. The results of the expert survey show that the model properly describes the links between the IoT and process mining and that it has added value for IoT process mining. Furthermore, the model was refined according to the experts' feedback. Accordingly, the paper's key contribution consists of a common reference model that can instigate true interdisciplinary research connecting IoT and process mining.
Keywords:
Process mining
Internet of things
IoT process mining
Contextualized process mining
Event log model
Journal
IF:
10.4
Papers:
862
Citations:
4.0K