How To Contribute!
Want to join the collaborative effort behind ACCESS Metrics and Open XDMoD? Here's how you can help.
ACCESS XDMoD is built on the open source collaborative Open XDMoD software; we welcome third party participation. You can find some good places to get started below
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Checkout our Roadmap to see what we are working on.
See something you like? Don't see something you could use? Let us know!
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Our code is hosted on GitHub
So when you're ready to start working on that new feature you'll know where to submit the Pull Request. -
Our documentation can be found Here
So when all else fails, there's always something to refer to.
The XDMoD Data Analytics Framework provides programmatic access to the data in ACCESS XDMoD via a Python API. This API opens up the analysis of the data to a broad range of data science and machine learning tools.
The ACCESS Metrics team presented a tutorial at the PEARC '23 conference in
July 2023 showing how to use the Data Analytics Framework. Participants were
walked through example Jupyter Notebooks that are designed for self-guided
instruction. These notebooks are available to everyone through the
xdmod-notebooks GitHub repository. Anyone with an ACCESS
account can log in to ACCESS XDMoD, create an API token as instructed in the
notebooks and use that token with the Python API to obtain and analyze data
from ACCESS XDMoD.
The ACCESS Metrics team welcomes contributions to the collection of Jupyter Notebooks and the Python API source code. Contributions can be made via GitHub Pull Requests. For further information about XDMoD or the Data Analytics Framework, or to schedule a training session, please contact the ACCESS Metrics team via the ACCESS Ticket System.
