The preprint of the article “AQ-Bench: A Benchmark Dataset for Machine Learning on Global Air Quality Metrics” by Clara Betancourt et al. is now in the public discussion phase. The manuscript is available at https://essd.copernicus.org/preprints/essd-2020-380/. It has been accepted for public discussion by the Inter-Journal Special issue “Benchmark datasets and machine learning algorithms for Earth system science data” of the Journals Earth System Science Data and Geoscientific Model Development.
The AQ-Bench dataset contains air quality data and metadata at more than 5500 air quality observation stations all over the world. It offers a low-threshold entrance to machine learning on a real world environmental dataset. The dataset itself is available at https://b2share.eudat.eu/records/30d42b5a87344e82855a486bf2123e9f . To start machine learning on the AQ-Bench dataset directly in your browser, visit the code repository (https://gitlab.version.fz-juelich.de/toar/ozone-mapping) and launch the binder!