Semantic Scholar Open Access 2019 152 sitasi

A data ecosystem to support machine learning in materials science

B. Blaiszik Logan T. Ward M. Schwarting Jonathon Gaff Ryan Chard +3 lainnya

Lihat Sumber DOI

Abstrak

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.

Topik & Kata Kunci

Physics Materials Science

Penulis (8)

B. Blaiszik

Logan T. Ward

M. Schwarting

Jonathon Gaff

Ryan Chard

D. Pike

K. Chard

Ian T Foster

Format Sitasi

APA MLA BibTeX

Blaiszik, B., Ward, L.T., Schwarting, M., Gaff, J., Chard, R., Pike, D. et al. (2019). A data ecosystem to support machine learning in materials science. https://doi.org/10.1557/mrc.2019.118

Akses Cepat

Lihat di Sumber doi.org/10.1557/mrc.2019.118

Informasi Jurnal

Tahun Terbit: 2019
Bahasa: en
Total Sitasi: 152×
Sumber Database: Semantic Scholar
DOI: 10.1557/mrc.2019.118
Akses: Open Access ✓