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Building an Open Cloud Virtual Dataspace Model for Materials Scientific Data

Yang Li1, Jianjiang Li1, Peng Shi2, Xiaoning Qin3

1 School of Computer and Communication Engineering, University of Science and Technology Beijing (USTB), Beijing, 100083, China
2 National Center for Materials Service Safety, University of Science and Technology Beijing (USTB), Beijing, 100083, China
3 Dawning Information Industry Co. ,Ltd, Sugon Building, No.36 Zhongguancun Software Park,No.8 Dongbeiwang West Road, Haidian District, Beijing,100193,China

* Corresponding Author: Jianjiang Li, email

Intelligent Automation & Soft Computing 2019, 25(3), 615-624. https://doi.org/10.31209/2019.100000116

Abstract

The applications to process large amounts of materials scientific data at different scales, have been placed the field of materials science on the verge of a revolution. This domain faces serious challenges, including diversity of format of scientific data, and missing unified platform for sharing. A Virtual DataSpace model and the evolution model is introduced to organize heterogeneous data according to the user requirements and track the variations of data. The open cloud model is embedded in a materials scientific data sharing platform in our experiments to verify its effectiveness. The results show the model has made efforts making more information available and useful for researchers.

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Cite This Article

APA Style
Li, Y., Li, J., Shi, P., Qin, X. (2019). Building an open cloud virtual dataspace model for materials scientific data. Intelligent Automation & Soft Computing, 25(3), 615-624. https://doi.org/10.31209/2019.100000116
Vancouver Style
Li Y, Li J, Shi P, Qin X. Building an open cloud virtual dataspace model for materials scientific data. Intell Automat Soft Comput . 2019;25(3):615-624 https://doi.org/10.31209/2019.100000116
IEEE Style
Y. Li, J. Li, P. Shi, and X. Qin, “Building an Open Cloud Virtual Dataspace Model for Materials Scientific Data,” Intell. Automat. Soft Comput. , vol. 25, no. 3, pp. 615-624, 2019. https://doi.org/10.31209/2019.100000116



cc Copyright © 2019 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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