Data integration for materials research

被引:5
作者
Carey, Nicholas S. [1 ]
Budavari, Tamas [1 ,2 ,3 ]
Daphalapurkar, Nitin [3 ,4 ]
Ramesh, K. T. [3 ,4 ]
机构
[1] Johns Hopkins Univ, Dept Comp Sci, 3400 N Charles St, Baltimore, MD 21218 USA
[2] Johns Hopkins Univ, Dept Appl Math & Stat, 3400 N Charles St, Baltimore, MD 21218 USA
[3] Johns Hopkins Univ, Hopkins Extreme Mat Inst, 3400 N Charles St,Malone Hall 140, Baltimore, MD USA
[4] Johns Hopkins Univ, Dept Mech Engn, 3400 N Charles St,Latrobe Hall 223, Baltimore, MD 21218 USA
关键词
Materials research; Data science; Infrastructure;
D O I
10.1186/s40192-016-0049-0
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Introduction: A new data science initiative in materials research has been launched at The Johns Hopkins University within the Materials in Extreme Dynamic Environments (MEDE) Collaborative Research Alliance (CRA). Our first goal is to build a solution that facilitates seamless data sharing among MEDE scientists. We expect to shorten the design and development cycle of new materials by providing integrated storage, database, and analysis services, building on proven components of the SciServer project developed at the Institute for Data Intensive Engineering and Science (IDIES). Case description: Here we present our system design and demonstrate the power of our approach through a use-case that enables easy comparison of simulations and measurements. This prototype effort, focusing on boron carbide (BC), brings together multiple materials research elements in the Ceramics group within the MEDE CRA. Discussion and evaluation: The SciServer platform offers single-sign on access to various general purpose data analysis tools familiar to materials scientists in MEDE. During the case study deployment, users appreciated the simple data file upload process, automated database ingestion, and platform applicability to both students of the art and power users. Conclusions: From our case study experience in aggregating data from both simulations and physical experiments, we developed a template workflow from which a user may run a common data comparison task outright or customize to another purpose. Next, we turn to acquiring data from more MEDE groups and expanding the user base to the Metals group.
引用
收藏
页码:143 / 153
页数:11
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