Big Scientific Data Management (eBook, PDF)

First International Conference, BigSDM 2018, Beijing, China, November 30 - December 1, 2018, Revised Selected Papers
Redaktion: Li, Jianhui; Du, Zhihui; Cui, Wenjuan; Zhang, Ying; Meng, Xiaofeng

• Format: PDF

Produktbeschreibung

This book constitutes the refereed proceedings of the First International Conference on Big Scientific Data Management, BigSDM 2018, held in Beijing, Greece, in November/December 2018.

The 24 full papers presented together with 7 short papers were carefully reviewed and selected from 86 submissions. The topics involved application cases in the big scientific data management, paradigms for enhancing scientific discovery through big data, data management challenges posed by big scientific data, machine learning methods to facilitate scientific discovery, science platforms and storage systems for large scale scientific applications, data cleansing and quality assurance of science data, and data policies.

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Produktdetails

• Verlag: Springer Nature Switzerland
• Seitenzahl: 332
• Erscheinungstermin: 6. August 2019
• Englisch
• ISBN-13: 9783030280611
• Artikelnr.: 57534051

Inhaltsangabe

Application cases in the big scientific data management.- Paradigms for enhancing scientific discovery through big data.- Data management challenges posed by big scientific data.- Machine learning methods to facilitate scientific discovery.- Science platforms and storage systems for large scale scientific applications.- Data cleansing and quality assurance of science data.- Data policies.