The Materials Data Facility (MDF)

publish, discover, and access materials datasets

Discovering high-quality data has never been easier

Whether you’re looking to discover data or publish your own, the Materials Data Facility (MDF) has you covered. MDF hosts data (some as large as several terabytes!) and makes it easy to share and access.

Explore

Find what you're looking for. Our Data Discovery Guide can walk you through exploring data with the Foundry-ML SDK, Forge, or on the web.

Aggregate

Collecting data from various services can be challenging. Aggregating data from MDF-indexed datasets takes only a few lines of code!

Share

Every dataset gets its own page on our website with more details and instructions on how to access it. Simply share that link with your colleagues. No further instruction required!

Host your data on MDF

Publishing your data on MDF makes it easy for you to share your work with others. It also helps you reach people within the MDF community via our discovery features. Our discover page includes your data in search queries, so those interested can easily find your work.

Want to check that your data is in a good place before submitting it? Check out What Makes a Good Dataset. We provide a checklist for what you need with an explanation on why it matters.

Publish Large Datasets

From kilobytes to terabytes, we can help you make your data available to the world.

Get an Identifier

When you publish your dataset, receive a permanent identifier (e.g., DOI) to make citing your work simple.

Simplify Discovery and Access

Researchers will be able to find datasets through the MDF services and with Python tools. Dataset contents can be accessed via Globus or web (HTTPS).

Tired of sifting through unusable data?

Us too. MDF collects high-quality materials datasets from the community and makes them easily accessible. Our web and programmatic interfaces are built to make it easy to find and use the data you need.

Our infrastructure is built for accessibility.

That's why we use Globus to easily transfer data to anywhere you want to use it - from a laptop to a supercomputer. Not familiar with Globus? No problem! Our publishing process and data loading page walk you through how to use it. You only need to create a free account to publish your data.

Looking for data that's ready to use with Python?

Check out Foundry-ML datasets on MDF! Foundry-ML datasets are structured ML-ready datasets. With just a few lines of code, you can load data into a DataFrame and get coding.

Featured Datasets

>650

Datasets

>80 TB

of Materials Data Published

>100

Data Sources Indexed

How to Cite

If you find MDF useful in your research, please cite the following papers:

  • Blaiszik, B., K. Chard, J. Pruyne, R. Ananthakrishnan, S. Tuecke, and I. Foster. "The Materials Data Facility: Data services to advance materials science research." JOM 68, no. 8 (2016): 2045-2052. (link)
  • Blaiszik, Ben, Logan Ward, Marcus Schwarting, Jonathon Gaff, Ryan Chard, Daniel Pike, Kyle Chard, and Ian Foster. "A data ecosystem to support machine learning in materials science." MRS Communications 9, no. 4 (2019): 1125-1133. (open access) (journal)

Support

CHiMaD Phase I

This work was performed under financial assistance award 70NANB14H012 from U.S. Department of Commerce, National Institute of Standards and Technology as part of the Center for Hierarchical Material Design (CHiMaD).

CHiMaD Phase II

This work was performed under the following financial assistance award 70NANB19H005 from U.S. Department of Commerce, National Institute of Standards and Technology as part of the Center for Hierarchical Materials Design (CHiMaD).

Our Sponsors

Contact

If you would like to reach the MDF team with comments or questions, please contact materialsdatafacility@uchicago.edu