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Causal inference creates insights into observational data. Such insights could explain an outlying value to perform Root Cause Analysis. But how can causal inference be used with semantically annotated observations? The following demo showcases how to use semantically annotated sensor data for causal inference. The method’s implementation uses an agent pattern interacting with a knowledge graph.

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Finding Root Causes for Outliers in Semantically Annotated Sensor Data

  • 会议论文

  • 发表日期：

    2025年

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  • Tim Strobel,
  • Tim Pychynski,
  • Andreas Harth

摘要

Causal inference creates insights into observational data. Such insights could explain an outlying value to perform Root Cause Analysis. But how can causal inference be used with semantically annotated observations? The following demo showcases how to use semantically annotated sensor data for causal inference. The method’s implementation uses an agent pattern interacting with a knowledge graph.