Articles | Volume 13, issue 6
https://doi.org/10.5194/essd-13-3013-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-13-3013-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description article
| 
24 Jun 2021
Data description article |
| 24 Jun 2021
| 24 Jun 2021
AQ-Bench: a benchmark dataset for machine learning on global air quality metrics
Clara Betancourt
Jülich Supercomputing Centre, Jülich Research Centre, Wilhelm-Johnen-Straße, 52425 Jülich, Germany
Timo Stomberg
Jülich Supercomputing Centre, Jülich Research Centre, Wilhelm-Johnen-Straße, 52425 Jülich, Germany
Institute of Geodesy and Geoinformation, University of Bonn, Nußallee 17, 53115 Bonn, Germany
Ribana Roscher
Institute of Geodesy and Geoinformation, University of Bonn, Nußallee 17, 53115 Bonn, Germany
Martin G. Schultz
CORRESPONDING AUTHOR
Jülich Supercomputing Centre, Jülich Research Centre, Wilhelm-Johnen-Straße, 52425 Jülich, Germany
Scarlet Stadtler
Jülich Supercomputing Centre, Jülich Research Centre, Wilhelm-Johnen-Straße, 52425 Jülich, Germany
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Short summary
With the AQ-Bench dataset, we contribute to shared data usage and machine learning methods in the field of environmental science. The AQ-Bench dataset contains air quality data and metadata from more than 5500 air quality observation stations all over the world. The dataset offers a low-threshold entrance to machine learning on a real-world environmental dataset. AQ-Bench thus provides a blueprint for environmental benchmark datasets.
With the AQ-Bench dataset, we contribute to shared data usage and machine learning methods in...
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