From kilobytes to terabytes, our data publication service can help you make your data available to the world.
When you publish your dataset, receive a permanent identifier (e.g., DOI) to make citing your work simple.
Researchers will be able to find datasets through the MDF services and through Google Scholar. Dataset contents can be accessed via Globus or web (HTTPS).
$ pip install mdf_forge
from mdf_forge.forge import Forge mdf = Forge() elems = ["Al","Cu"] r = mdf.search_by_elements(elements=elems, limit=10)
dest = "my-ep-id" local_path = "/Users/me/globus" mdf.get_globus(r, dest=dest, local_path=local_path, preserve_dirs=True)
MDF Forge facilitates rich queries that enable unprecedented exploration of indexed datasets.
Collecting data from various services can be challenging. Aggregating data from MDF-indexed datasets takes only a few lines of code!
MDF Discover allows programmatic access to the indexed dataset contents to facilitate automated analyses.
Materials Data Published
Data Sources Indexed
If you find MDF useful in your research, please cite the following paper: 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.
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).