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Current air quality monitoring systems struggle to integrate heterogeneous historical data into AI algorithms that could provide deeper insights into severe pollution impacts. We present PANORAMA, a knowledge graph approach that predicts links between pollutant exposure and health outcomes by integrating diverse air quality and health datasets. Using an Extract, Transform, and Load process, we incorporated discrete data into a knowledge graph and evaluated its inferential capabilities through embedding models. Our case study in France’s Gironde department yielded promising results (MR: 11.0, MRR: 0.403, Hits@1/3/10: 0.326/0.447/0.499) using the Rotate model, demonstrating the potential of semantic structuring and knowledge graph technology for environmental public health applications.

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Outdoor Air Quality and Health Impact: The PANORAMA Knowledge Graph Based Approach

  • 会议论文

  • 发表日期：

    2026年

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  • Nareesa Karmali,
  • Abdougafarou Mamam,
  • Gayo Diallo

摘要

Current air quality monitoring systems struggle to integrate heterogeneous historical data into AI algorithms that could provide deeper insights into severe pollution impacts. We present PANORAMA, a knowledge graph approach that predicts links between pollutant exposure and health outcomes by integrating diverse air quality and health datasets. Using an Extract, Transform, and Load process, we incorporated discrete data into a knowledge graph and evaluated its inferential capabilities through embedding models. Our case study in France’s Gironde department yielded promising results (MR: 11.0, MRR: 0.403, Hits@1/3/10: 0.326/0.447/0.499) using the Rotate model, demonstrating the potential of semantic structuring and knowledge graph technology for environmental public health applications.