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A data ecosystem to support machine learning in materials science

  • Ben Blaiszik (a1) (a2), Logan Ward (a1) (a2), Marcus Schwarting (a2), Jonathon Gaff (a1), Ryan Chard (a1) (a2), Daniel Pike (a3), Kyle Chard (a1) (a2) and Ian Foster (a1) (a2)...

Abstract

Facilitating the application of machine learning (ML) to materials science problems requires enhancing the data ecosystem to enable discovery and collection of data from many sources, automated dissemination of new data across the ecosystem, and the connecting of data with materials-specific ML models. Here, we present two projects, the Materials Data Facility (MDF) and the Data and Learning Hub for Science (DLHub), that address these needs. We use examples to show how MDF and DLHub capabilities can be leveraged to link data with ML models and how users can access those capabilities through web and programmatic interfaces.

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Corresponding author

Address all correspondence to Ben Blaiszik at blaiszik@uchicago.edu

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A data ecosystem to support machine learning in materials science

  • Ben Blaiszik (a1) (a2), Logan Ward (a1) (a2), Marcus Schwarting (a2), Jonathon Gaff (a1), Ryan Chard (a1) (a2), Daniel Pike (a3), Kyle Chard (a1) (a2) and Ian Foster (a1) (a2)...

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