Repository · FAIRsharing
FOUNDRY-ML
Computational chemistryCompounds and reactionsMaterials and polymersImages and microscopy
Foundry-ML is an open-source platform that provides curated, machine-learning-ready datasets for materials science and chemistry research. It offers structured datasets with standardized metadata, including tabular data, images, and hierarchical scientific data formats. The platform focuses on scientific data such as materials properties, chemical structures, experimental measurements, and simulation results to support reproducible ML workflows in scientific discovery.
- Website
- Record in FAIRsharing (doi:10.25504/FAIRsharing.d661ca)
- Subjects: Chemistry, Materials Science
What is known per question
The questions of the decision tree, with what FAIRsharing says about this repository. ✓ supported, ✗ excluded, ? not known. Your own answers are marked.
What kind of data do you want to archive?
- ? Spectra
- ? Crystal structures
- ✓ Computational chemistry
- ? Catalysis
- ✓ Compounds and reactions
- ? Bioassays and chemical biology
- ✓ Materials and polymers
- ✓ Images and microscopy
- ? Something else
Subjects: Chemistry; Materials Science
Domains: Machine Learning
Does the journal or publisher you publish with require or recommend a repository?
- ? Yes
- ? No
- ? I do not know
FAIRsharing has no information on this.
Which discipline does your data belong to?
FAIRsharing has no information on this.
Which publisher?
FAIRsharing has no information on this.
Does your funder have requirements for where data is archived?
- ? Yes
- ? No
- ? I do not know
FAIRsharing has no information on this.
Which funder?
FAIRsharing has no information on this.
Does your institution offer a data repository?
- ? Yes
- ? No
- ? I do not know
FAIRsharing has no information on this.
Which institution?
FAIRsharing has no information on this.
Can your data be shared openly?
- ✓ Yes, openly available
- ? Yes, after an embargo
- ✗ Only with restrictions
Data access: open
Data deposition: open
How large is your dataset?
- ? Less than 1 GB
- ? 1 GB to 50 GB
- ? 50 GB to 1 TB
- ? More than 1 TB
FAIRsharing has no information on this.
Why can the data not be open?
- ? It contains personal data
- ? Commercial or intellectual property reasons
- ? Safety or security concerns
- ? A data sharing agreement limits it
FAIRsharing has no information on this.
Under which license do you want to share the data?
- ? CC0 / public domain
- ✓ CC BY
- ? Another open license
- ? Not decided yet
Licences: MIT License; Creative Commons Attribution 4.0 International (CC BY 4.0)
Do you need a persistent identifier, such as a DOI, for citing the data?
- ? Yes, a DOI
- ? Any persistent identifier will do
- ? No
FAIRsharing has no information on this.
Must the data be stored in a specific region?
- ✗ In the European Union
- ? In a specific country
- ✓ No preference
Country: United States
Must archiving be free of charge?
- ? Yes, free only
- ? A fee is fine
FAIRsharing has no information on this.
Which country?
✓ 1 of 15 in the list ✗ excludes 14
Country: United States