AIREO Resources

Description

To demonstrate the AIREO Specification and Best Practice Guidelines in practice, a number of sample Jupyter notebooks are provided. Each notebook accompanies one of the pilot datasets and provides demonstration of the Python library functionality from the persperctive of both data creators and users. Data creators can load a TDS, populate critical metadata, run the AIREO Compliance assessment and some quality assurance checking. Data users can browse the catalogue, load a TDS, investigate statistics and metadata, visualise the data and get it in a format for input to an ML model.

The notebook for each dataset can be accessed on the EuroDataCube here:

• AI4Arctic Automated Sea Ice Products dataset notebook
• Common Agricultural Practice (CAP) Austria dataset notebook
• Forest Observation System (FOS) dataset notebook
• Spacenet7 dataset notebook

To execute the notebooks, you will need to create an account on the EuroDataCube site with Jupyter notebook resources. A free account will give you sufficient resources to run the notebooks as they are published.  

After the account has successfully been created and you are logged in, you can search for AIREO notebooks in the EDC Marketplace or click on the links to the notebooks above. Once the notebook is open, under the Actions section (top right of the page), you will find a green button “Execute Notebook”. When you execute the notebook a Jupyter Lab environment will open in your user environment and you can run each cell in succession to complete the notebook.

The notebooks demonstrate different functionality of the aireo_lib library from the perspective of both a data creator and a data user. After following the steps described in a notebook, you will generate a dataset in your user environment which is compatible with the AIREO Specification and which has been validated using the STAC specification tools. Within the folder generated, along with a dataset following the AIREO data model and its subfolders and metadata files, a datasheet (in .md format) is also automatically generated providing a detailed explanation of the dataset from the metadata.

Or you can view a html version of the notebooks and their text output here:

• AI4Arctic Automated Sea Ice Products dataset notebook
• Common Agricultural Practice (CAP) Austria dataset notebook
• Forest Observation System (FOS) dataset notebook
• Spacenet7 dataset notebook