Many cloud-based solutions for workflows in EO are available to users today, but only few support reproducibility or comply with the OGC FAIR (findability, accessibility, interoperability, reusability) data principles.
This short tutorial demonstrates a solution that meets these requirements.
- Alice developed a Water Body detection Earth Observation application and package it as an EO Application Package
- Bob scripts the execution of application
Alice included in the water bodies detection Application Package software repository a Continuous Integration configuration relying on Github Actions to:
- build the containers
- push the built containers to Github container registry
- update the Application Package with these new container references
- push the updated Application Package to Github's artifact registry
Alice sent an email to Bob:
from: alice@acme.io
to: bob@acme.io
subject: Detecting water bodies with NDWI and the Otsu threshold
Hi Bob!
check out my new Application Package for detecting water bodies using NDWI and the Ostu threshold.
I've ran it over our test site bounding box and preliminary result look promising.
The github repo is https://github.com/eoap/quickwin and I've just released version 1.0.0.
Let me know!
Cheers
Alice
With this information, Bob scripts the Application Execution in a Jupyter Notebook.
His environment has a container runtime (e.g. podman or docker) and the cwltool CWL runner.
Clone this repo:
git clone https://github.com/eoap/open-reproducible-app-package
Click on File then Open Folder... and browser to the cloned directory open-reproducible-app-package
Go back to the terminal and create the Python environment with:
python -m venv env_reproducible_app
source env_reproducible_app/bin/activate
pip install -r requirements.txt
python -m ipykernel install --user --name env_reproducible_app --display-name "env_reproducible_app"
The execution is operated with the Jupyter Notebook notebook.ipynb.
The webpage of the documentation is https://eoap.github.io/open-reproducible-app-package/.