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Your search keyword '"Ahn, Sunil"' showing total 2 results
Start Over Author "Ahn, Sunil" Topic big data
2 results on '"Ahn, Sunil"'

1. Machine Learning Based Materials Properties Prediction Platform for Fast Discovery of Advanced Materials

Author

Lee, Jeongcheol, Ahn, Sunil, Kim, Jaesung, Lee, Sik, Cho, Kumwon, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Ruediger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Hirche, Sandra, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Liang, Qilian, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Möller, Sebastian, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zhang, Junjie James, Series Editor, Park, James J., editor, Loia, Vincenzo, editor, Choo, Kim-Kwang Raymond, editor, and Yi, Gangman, editor

Published
2019
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2. EDISON‐DATA: A flexible and extensible platform for processing and analysis of computational science data.

Author

Ahn, Sunil, Lee, Jeongcheol, Kim, Jaesung, and Lee, JongSuk R.

Subjects
DATA science, METADATA, COMPUTATIONAL complexity, BIG data, QUALITY control, CASE studies
Abstract

Summary: With the recent emergence of new paradigm, ie, open science and big data, the need for data sharing and collaboration is becoming important in the computational science field as well. The EDISON‐DATA platform aims to provide services that computational simulation data can easily published, preserved, shared, reused, discovered, and analyzed. First, this paper analyzed computational science platform‐related issues, obtained during the development of the EDISON‐DATA platform, regarding the sharing and reusing of the computational science data. These issues include data complexity, diversity, reliability, heterogeneity, etc. To solve the above issues and support data analysis in an efficient and integrated manner, this study proposes various ideas used in the EDISON‐DATA platform. First, we suggested an automated preprocessing framework to handle the complexity of computational science data. Second, to solve the diversity issue, we presented ways to develop preprocessing logic and data presentation logic customized for each data type. Third, to improve the reliability of computational science data, some quality control and provenance management techniques were presented. Fourth, we proposed a way to manage related data in groups. Fifth, to solve data heterogeneity problem and to analyze data in an integrated way, we let the preprocessing framework to use controlled vocabularies to express descriptive metadata. Lastly, we demonstrated feasibility and usability of the proposed ideas in this paper by presenting a case study of building a research portal service in the materials field based on the EDISON‐DATA platform. [ABSTRACT FROM AUTHOR]

Published
2019
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