Walk through MDF workflows to share your datasets and uncover material science resources tailored to your research.
Follow these steps to publish your materials science data with MDF.
Create a free Globus account to get started with MDF publishing.
After registration, join the MDF Globus group to unlock publishing capabilities.
Organize your data in open, standard formats for maximum accessibility.
Upload from local storage, Globus endpoints, or Google Drive.
Review dataset best practices.
Submit your prepared dataset through our guided publishing interface to mint a DOI and make it discoverable.
If your data is structured and ready to be loaded into a DataFrame with Python, check out Foundry-ML datasets on MDF. These are structured ML-ready datasets that can be accessed programmatically.
Learn how to find and access materials science datasets through MDF.
Browse published datasets through a web user interface. You can search, discover, and download data just using our website.
Explore datasets through a Python interface either with MDF Forge or Foundry-ML.
Foundry-ML
Datasets have a required structure that allows them to loaded into usable Python formats immediately. To use Foundry-ML, follow the steps for loading data from any of our example notebooks, documentation, or a specific dataset's page.
MDF Forge
Allows you to load datasets programmatically, but the datasets aren't configured to be used in a Python environment right away. If you'd like to use them in a Python environment, that may require a little more work on your end since we don't have a required structure for those datasets. To use MDF Forge, check out the documentation or the GitHub Repo.