A library to compute and compile metrics about the U.S. Integrated Ocean Observing System (U.S. IOOS®). U.S. IOOS® is a vital tool for tracking, predicting, managing, and adapting to changes in our ocean, coastal and Great Lakes environment.
Part of the intent of this repository is to create metrics for the IOOS by the numbers.
"IOOS by the Numbers" is was developed as a graphical representation of IOOS -- a system of includes our partnerships, research and observing components, and data management capabilities. This figure is an annually updated collection of numbers that show the breadth of the IOOS Program as it is growing and evolving. These data are obtained from multiple sources. The source for each value is captured in the functions defined at https://github.com/ioos/ioos_metrics/tree/main/ioos_metrics.
conda install ioos-metrics
pip install ioos-metrics
See https://github.com/ioos/ioos_metrics/tree/main/notebooks
url: https://ioos.github.io/ioos_metrics/
Leveraged existing resources from https://github.com/noaa-fisheries-integrated-toolbox/toolbox_web_templating.
The webpages are built from the website/ directory.
| File(s) | Description |
|---|---|
*_config.json |
configuration for what resources to present on the webpages. |
create_asset_inventory_page.py |
script to create https://ioos.github.io/ioos_metrics/asset_inventory.html |
create_gts_atn_page.py |
script to create https://ioos.github.io/ioos_metrics/gts_atn.html |
create_gts_regional_landing_page.py |
script to create https://ioos.github.io/ioos_metrics/gts_regional.html |
deploy/index.html |
html source for landing page https://ioos.github.io/ioos_metrics/index.html |
deploy/static/main.css |
css control for website. |
To create the webpages on your local system
git clone https://github.com/ioos/ioos_metrics.git
cd ioos_metrics/website
python create_asset_inventory_page.py
python create_gts_atn_landing_page.py
python create_gts_regional_landing_page.pyAll the webpages will be saved to website/deploy. You can view the local html files with a web browser for testing.
The website is generated using GitHub Actions and GitHub Pages. The python scripts, referenced above, are ran and the
directory website/deploy is then uploaded as an artifact for GitHub Pages to serve as a website.
This process is automatically ran with every push to the main branch. See here.