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AIREO Resources

AIREO Python Library


The initial version of the AIREO Python library provides basic functionality for data providers and users and can be accessed through the GitHub page. The aims are:

  • To support data providers to create AIREO TDS which are FAIR, are of high quality and adhere to the AIREO specifications.
  • To help data providers to use AIREO innovations, such as generating a STAC-compliant catalogue for a TDS and checking the AIREO compliance level and quality indicators such as metadata completeness.
  • To assist dataset users to perform high-level exploratory analysis on an AIREO TDS – exploring the statistical properties of an AIREO TDS through the metadata and visualising key aspects of the data.

To help users to load an AIREO TDS and access it through common data formats used by the ML community (xarray) so that ML practitioners can use the TDS in their favourite ML libraries and platforms with minimal effort.

The library can be installed locally, or used with the datasets by creating an account on the EuroDataCube where the notebooks are hosted.

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