Materials Data Facility

The Materials Data Facility helps researchers publish, discover, and access materials science datasets, including simulation and machine-learning collections.

materialsdatafacility.org
Materials Data Facility homepage screenshot

About Materials Data Facility

The Materials Data Facility lets researchers publish, discover, and access materials science datasets, including experimental, simulation, and AI/ML collections. The site lists 880+ datasets, 600 TB+ of hosted data, and 60+ ML-ready datasets, with browsing by those three categories.

Publishing uses a guided interface to add metadata and mint a DOI for a dataset. It requires a free Globus account and joining the MDF group, with uploads from local storage, Globus endpoints, or Google Drive. Foundry provides structured datasets that can be loaded by DOI with a few lines of Python.

Key features

  • Browse experimental, simulation, and AI/ML materials datasets
  • Mint DOIs and add metadata through guided publishing interface
  • Upload data from local storage, Globus endpoints, or Google Drive
  • Load ML-ready datasets with a few lines of Python via Foundry
  • Track citations and usage for published datasets
  • Organize published data in open formats
Best for: Researchers in materials science who need to publish or reuse experimental, simulation, or machine-learning datasets.
Good for
  • Covers 880+ datasets and 600 TB+ of hosted data, including 60+ ML-ready collections
  • Assigns DOIs and records metadata, citations, and usage for published datasets
  • Offers Python-based access to structured datasets through Foundry
Watch out for
  • Publishing requires a free Globus account and joining the MDF group
  • Publishing expects data to be organized in open formats

Materials Data Facility at a glance

Type
Dataset
Platforms
Web
Language
English
Last checked
Oct 5, 2026 · Online when checked
Listed
Oct 5, 2026

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Materials Data Facility FAQ

What is needed to publish a dataset?
Create a free Globus account, join the MDF group, organize data in open formats, then use the guided interface to add metadata and mint a DOI.
Where can published data be uploaded from?
From local storage, Globus endpoints, or Google Drive.
How do I load an ML-ready dataset with Foundry?
Install the foundry_ml package and use Python to retrieve a dataset by its DOI, including as a dictionary.
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