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DataStream XES Extension: Embedding IoT Sensor Data into Extensible Event Stream Logs

Author

Listed:
  • Juergen Mangler

    (Department of Computer Science, School of Computation, Information and Technology, Technical University of Munich, 85748 Garching, Germany
    These authors contributed equally to this work.)

  • Joscha Grüger

    (Artificial Intelligence and Intelligent Information Systems, University of Trier, 54296 Trier, Germany
    German Research Center for Artificial Intelligence (DFKI), Branch University of Trier, 54296 Trier, Germany
    These authors contributed equally to this work.)

  • Lukas Malburg

    (Artificial Intelligence and Intelligent Information Systems, University of Trier, 54296 Trier, Germany
    German Research Center for Artificial Intelligence (DFKI), Branch University of Trier, 54296 Trier, Germany
    These authors contributed equally to this work.)

  • Matthias Ehrendorfer

    (Research Group Workflow Systems and Technology, Faculty of Computer Science, University of Vienna, 1090 Vienna, Austria
    These authors contributed equally to this work.)

  • Yannis Bertrand

    (Research Centre for Information Systems Engineering (LIRIS), KU Leuven, Warmoesberg 26, 1000 Brussels, Belgium
    These authors contributed equally to this work.)

  • Janik-Vasily Benzin

    (Department of Computer Science, School of Computation, Information and Technology, Technical University of Munich, 85748 Garching, Germany)

  • Stefanie Rinderle-Ma

    (Department of Computer Science, School of Computation, Information and Technology, Technical University of Munich, 85748 Garching, Germany)

  • Estefania Serral Asensio

    (Research Centre for Information Systems Engineering (LIRIS), KU Leuven, Warmoesberg 26, 1000 Brussels, Belgium)

  • Ralph Bergmann

    (Artificial Intelligence and Intelligent Information Systems, University of Trier, 54296 Trier, Germany
    German Research Center for Artificial Intelligence (DFKI), Branch University of Trier, 54296 Trier, Germany)

Abstract

The Internet of Things (IoT) has been shown to be very valuable for Business Process Management (BPM), for example, to better track and control process executions. While IoT actuators can automatically trigger actions, IoT sensors can monitor the changes in the environment and the humans involved in the processes. These sensors produce large amounts of discrete and continuous data streams, which hold the key to understanding the quality of the executed processes. However, to enable this understanding, it is needed to have a joint representation of the data generated by the process engine executing the process, and the data generated by the IoT sensors. In this paper, we present an extension of the event log standard format XES called DataStream. DataStream enables the connection of IoT data to process events, preserving the full context required for data analysis, even when scenarios or hardware artifacts are rapidly changing. The DataStream extension is designed based on a set of goals and evaluated by creating two datasets for real-world scenarios from the transportation/logistics and manufacturing domains.

Suggested Citation

  • Juergen Mangler & Joscha Grüger & Lukas Malburg & Matthias Ehrendorfer & Yannis Bertrand & Janik-Vasily Benzin & Stefanie Rinderle-Ma & Estefania Serral Asensio & Ralph Bergmann, 2023. "DataStream XES Extension: Embedding IoT Sensor Data into Extensible Event Stream Logs," Future Internet, MDPI, vol. 15(3), pages 1-21, March.
    • Handle: RePEc:gam:jftint:v:15:y:2023:i:3:p:109-:d:1096628
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