An IoT-Enriched Event Log for Smart Factories with Injected Data Quality Issues

Modern technologies such as the Internet of Things (IoT) play a key role in Smart Manufacturing and Business Process Management (BPM). In particular, process mining benefits from enriched event logs that incorporate physical sensor data. This dataset presents an IoT-enriched XES event log recorded in a physical smart factory environment. It builds upon the previously published dataset “An IoT-Enriched Event Log for Process Mining in Smart Factories” (available on Zenodo) and follows the DataStream XES extension. In this modified version, three types of common Data Quality Issues (DQIs) - missing sensor values, missing sensors, and time shifts - have been artificially injected into the sensor data. These issues reflect realistic challenges in industrial IoT data processing and are valuable for developing and testing robust data cleaning and analysis methods. By comparing the original (clean) dataset with this modified version, researchers can systematically evaluate DQI detection, handling, and solving techniques under controlled conditions. Further details are provided for each of three DQI types in the subfolders in a csv changelog.