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Data integration for materials research

  • Nicholas S. CareyEmail author
  • Tamás Budavári
  • Nitin Daphalapurkar
  • K. T. Ramesh
CASE STUDY

Abstract

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.

Keywords

Materials research Data science Infrastructure 

Notes

Acknowledgements

Research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-12-2-0022. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the US Government. The US Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.

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Copyright information

© Carey et al. 2016

Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(https://doi.org/creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • Nicholas S. Carey
    • 1
    Email author
  • Tamás Budavári
    • 2
    • 1
    • 3
  • Nitin Daphalapurkar
    • 3
    • 4
  • K. T. Ramesh
    • 3
    • 4
  1. 1.Department of Computer ScienceJohns Hopkins UniversityBaltimoreUSA
  2. 2.Department of Applied Mathematics and StatisticsJohns Hopkins UniversityBaltimoreUSA
  3. 3.Hopkins Extreme Materials InstituteJohns Hopkins UniversityBaltimoreUSA
  4. 4.Department of Mechanical EngineeringJohns Hopkins UniversityBaltimoreUSA

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