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Big Scientific Data Management : First International Conference, BigSDM 2018, Beijing, China, November 30 – December 1, 2018, Revised Selected Papers - 2019 ed.

By: (Edited by) Jianhui Li , (Edited by) Wenjuan Cui , (Edited by) Xiaofeng Meng , (Edited by) Ying Zhang , (Edited by) Zhihui Du

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Ksh 8,100.00

Format: Paperback / Softback

ISBN-10: 3030280608

ISBN-13: 9783030280604

Edition: 2019 ed.

Series: Lecture Notes in Computer Science

Publisher: Springer Nature Switzerland AG

Imprint: Springer Nature Switzerland AG

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Aug 7th, 2019

Print length: 332 Pages

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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.

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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