1 Collaborative Innovation Center of Steel Technology, University of Science and Technology Beijing, Beijing 100083, China;
2 Beijing Laboratory of Metallic Materials and Processing for Modern Transportation, University of Science and Technology Beijing, Beijing 100083, China;
3 Beijing Key Laboratory of Materials Genome Engineering, University of Science and Technology Beijing, Beijing 100083, China;
4 Computer Science and Engineering, The Pennsylvania State University, University Park, PA 16802, USA;
5 Kennametal Inc., 1600 Technology Way Latrobe, PA 15650, USA;
6 Institute of Advanced Materials and Technology, University of Science and Technology Beijing, Beijing 100083, China
Since its launch in 2011, the Materials Genome Initiative (MGI) has drawn the attention of researchers from academia, government, and industry worldwide. As one of the three tools of the MGI, the use of materials data, for the first time, has emerged as an extremely significant approach in materials discovery. Data science has been applied in different disciplines as an interdisciplinary field to extract knowledge from data. The concept of materials data science has been utilized to demonstrate its application in materials science. To explore its potential as an active research branch in the big data era, a three-tier system has been put forward to define the infrastructure for the classification, curation and knowledge extraction of materials data.
Project supported by the National Key R&D Program of China (Grant No. 2016YFB0700503), the National High Technology Research and Development Program of China (Grant No. 2015AA03420), Beijing Municipal Science and Technology Project, China (Grant No. D161100002416001), the National Natural Science Foundation of China (Grant No. 51172018), and Kennametal Inc.
Hai-Qing Yin(尹海清), Xue Jiang(姜雪), Guo-Quan Liu(刘国权), Sharon Elder, Bin Xu(徐斌), Qing-Jun Zheng(郑清军), Xuan-Hui Qu(曲选辉) The materials data ecosystem: Materials data science and its role in data-driven materials discovery 2018 Chin. Phys. B 27 118101
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