@inproceedings{MaldonadoEtAl2026_IoTDataQuality,
  author       = {Andrea Maldonado and Adrian Bazan-Muñoz and Lukas Malburg and Yannis Bertrand},
  editor       = {Andrea Maldonado and Yannis Bertrand and Ronny Seiger},
  title        = {{IoT Data Quality Assurance for Reliable Process Analytics}},
  booktitle    = {Proceedings of the 10th International Workshop on Business Processes Meet the Internet of Things (BP-Meet-IoT 2026) co-located with the 30th International Conference on Enterprise Design, Operations, and Computing (EDOC 2026), Enschede, The Netherlands, September 15, 2026},
  series       = {{CEUR} Workshop Proceedings},
  volume       = {4310},
  publisher    = {CEUR-WS.org.},
  abstract     = {Data quality is a major concern in all data analysis tasks. In IoT-enhanced business processes, data quality issues often arise from faulty sensor measurements, which are propagated through event abstraction to incorrect process decisions. In this paper, we investigate the main challenges in data quality management for IoT-enhanced business processes and isolate four subchallenges. Each subchallenge is first defined and put in perspective with relevant literature and representative real-world use cases before we present five overarching opportunities to address the subchallenges. Finally, we conclude the paper with a research agenda, making recommendations over multiple time horizons to improve data quality management in IoT-enhanced business processes.},
  keywords     = {IoT-enhanced Business Processes, Data Quality Management, Internet-of-Things, Expert-in-the-Loop},
  year         = {2026},
  doi          = {10.83095/ceurws_04310_008},
  url          = {https://www.wi2.uni-trier.de/shared/publications/2026_BPMeetIoT_MaldonadoEtAl.pdf}
}

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In IoT-enhanced business processes, data quality issues often arise from faulty sensor measurements, which are propagated through event abstraction to incorrect process decisions. In this paper, we investigate the main challenges in data quality management for IoT-enhanced business processes and isolate four subchallenges. Each subchallenge is first defined and put in perspective with relevant literature and representative real-world use cases before we present five overarching opportunities to address the subchallenges. 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