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IoT-enriched event log generation and quality analytics: a case study

  • Joscha Grüger

    Joscha Grüger, M.Sc. is a research associate and PhD candidate at the Chair of Artificial Intelligence and Intelligent Information Systems at the University of Trier and researches at the German Research Center for Artificial Intelligence (DFKI) Trier Branch. In 2019, he received his master’s degree in computer science from Trier University of Applied Science. His research focuses on the use of artificial intelligence methods, process mining, and business process management technologies, especially in the healthcare domain and in the context of the Internet of Things.

     EMAIL logo     , Lukas Malburg

    Lukas Malburg, M.Sc. is a research assistant and PhD student at the Department of Artificial Intelligence and Intelligent Information Systems at Trier University. In addition, he is part of the German Research Center for Artificial Intelligence (DFKI) branch Trier since May 2021. In 2019, he obtained his Master degree in business informatics from the University of Trier. In his research, he examines the use of Artificial Intelligence methods, in particular (Process-Oriented) Case-Based Reasoning and AI Planning, in Cyber-Physical Production Systems and the Internet of Things combined with Business Process Management technologies.

         und Ralph Bergmann

    Prof. Dr. Ralph Bergmann is full professor at Trier University since 2004 and is directing a research group on business informatics with a strong focus on Artificial Intelligence. Since 2020 he is also topic-field leader for experience-based learning systems at the Trier Branch of the German Research Center for AI (DFKI). Over the past 30 years, he has significantly contributed to the foundations and applications of AI, including knowledge-based systems, knowledge representation and reasoning, case-based reasoning, machine learning, AI planning, and semantic technologies. With the current focus on experience-based learning systems he aims at developing hybrid AI-systems integrating data-oriented AI methods (machine learning and case-based reasoning) with semantic technologies for modeling explicit knowledge. He authored more than 250 refereed papers, including four books and 13 edited proceedings volumes and led more than 35 research projects.
Veröffentlicht/Copyright: 1. Juni 2023
it - Information Technology
Aus der Zeitschrift it - Information Technology Band 65 Heft 3

Abstract

Modern technologies such as the Internet of Things (IoT) are becoming increasingly important in various fields, including business process management (BPM) research. An important area of research in BPM is process mining, which can be used to analyze event logs e.g., to check the conformance of running processes. However, the data ingested in IoT environments often contain data quality issues (DQIs) due to system complexity and sensor heterogeneity, among other factors. To date, however, there has been little work on IoT event logs, DQIs occurring in them, and how to handle them. In this case study, we generate an IoT event log, perform a structured data quality analysis, and describe how we addressed the problems we encountered in pre-processing.

Keywords: data quality in event logs; datastream XES extension; iot; IoT-enriched event log; physical smart factory; process mining
ACM CCS: Information systems → Information systems applications → Decision support systems → Data analytics
Corresponding author: Joscha Grüger, Artificial Intelligence and Intelligent Information Systems, University of Trier, 54296 Trier, Germany; and German Research Center for Artificial Intelligence (DFKI), Branch University of Trier, 54296 Trier, Germany, E-mail:

Joscha Grüger and Lukas Malburg contributed equally to the work.

About the authors

Joscha Grüger

Joscha Grüger, M.Sc. is a research associate and PhD candidate at the Chair of Artificial Intelligence and Intelligent Information Systems at the University of Trier and researches at the German Research Center for Artificial Intelligence (DFKI) Trier Branch. In 2019, he received his master’s degree in computer science from Trier University of Applied Science. His research focuses on the use of artificial intelligence methods, process mining, and business process management technologies, especially in the healthcare domain and in the context of the Internet of Things.

Lukas Malburg

Lukas Malburg, M.Sc. is a research assistant and PhD student at the Department of Artificial Intelligence and Intelligent Information Systems at Trier University. In addition, he is part of the German Research Center for Artificial Intelligence (DFKI) branch Trier since May 2021. In 2019, he obtained his Master degree in business informatics from the University of Trier. In his research, he examines the use of Artificial Intelligence methods, in particular (Process-Oriented) Case-Based Reasoning and AI Planning, in Cyber-Physical Production Systems and the Internet of Things combined with Business Process Management technologies.

Ralph Bergmann

Prof. Dr. Ralph Bergmann is full professor at Trier University since 2004 and is directing a research group on business informatics with a strong focus on Artificial Intelligence. Since 2020 he is also topic-field leader for experience-based learning systems at the Trier Branch of the German Research Center for AI (DFKI). Over the past 30 years, he has significantly contributed to the foundations and applications of AI, including knowledge-based systems, knowledge representation and reasoning, case-based reasoning, machine learning, AI planning, and semantic technologies. With the current focus on experience-based learning systems he aims at developing hybrid AI-systems integrating data-oriented AI methods (machine learning and case-based reasoning) with semantic technologies for modeling explicit knowledge. He authored more than 250 refereed papers, including four books and 13 edited proceedings volumes and led more than 35 research projects.

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: This work is funded by the Federal Ministry for Economic Affairs and Climate Action under grant No. 01MD22002C EASY.

  3. Conflict of interest statement: The authors declare no conflicts of interest regarding this article.

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Received: 2022-12-23
Accepted: 2023-05-16
Published Online: 2023-06-01
Published in Print: 2023-06-28

© 2023 Walter de Gruyter GmbH, Berlin/Boston

Artikel in diesem Heft

  1. Frontmatter
  2. Editorial
  3. IoPT: internet of processes and things
  4. Research Articles
  5. An IoT architecture to integrate different machine tools into a compound OPC UA interface
  6. Design of an IoPT approach to create a cocktail robot station with robotic arm: components, interfaces and control
  7. Case Report
  8. IoPT integration on the factory floor: a case study
  9. Research Article
  10. A framework for AI-based self-adaptive cyber-physical process systems
  11. Case Report
  12. IoT-enriched event log generation and quality analytics: a case study
https://doi.org/10.1515/itit-2022-0077
Schlagwörter für diesen Artikel
data quality in event logs; datastream XES extension; iot; IoT-enriched event log; physical smart factory; process mining

Artikel in diesem Heft

  1. Frontmatter
  2. Editorial
  3. IoPT: internet of processes and things
  4. Research Articles
  5. An IoT architecture to integrate different machine tools into a compound OPC UA interface
  6. Design of an IoPT approach to create a cocktail robot station with robotic arm: components, interfaces and control
  7. Case Report
  8. IoPT integration on the factory floor: a case study
  9. Research Article
  10. A framework for AI-based self-adaptive cyber-physical process systems
  11. Case Report
  12. IoT-enriched event log generation and quality analytics: a case study
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