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Big scientific data managementfirst ...

(1998 :)

Big scientific data managementfirst International Conference, BigSDM 2018, Beijing, China, November 30 - December 1, 2018 : revised selected papers /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Big scientific data managementedited by Jianhui Li ... [et al.].
其他題名:	first International Conference, BigSDM 2018, Beijing, China, November 30 - December 1, 2018 : revised selected papers /
其他題名:	BigSDM 2018
其他作者:	Li, Jianhui.
團體作者:
出版者:	Cham :Springer International Publishing :2019.
面頁冊數:	xiii, 332 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
標題:	Big dataCongresses.
電子資源:	https://doi.org/10.1007/978-3-030-28061-1
ISBN:	9783030280611$q(electronic bk.)

Big scientific data managementfirst International Conference, BigSDM 2018, Beijing, China, November 30 - December 1, 2018 : revised selected papers /
Big scientific data managementfirst International Conference, BigSDM 2018, Beijing, China, November 30 - December 1, 2018 : revised selected papers /[electronic resource] :BigSDM 2018edited by Jianhui Li ... [et al.]. - Cham :Springer International Publishing :2019. - xiii, 332 p. :ill., digital ;24 cm. - Lecture notes in computer science,114730302-9743 ;. - Lecture notes in computer science ;4891..

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.

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.

ISBN: 9783030280611$q(electronic bk.)

Standard No.: 10.1007/978-3-030-28061-1doiSubjects--Topical Terms:

592065
Big data
--Congresses.

LC Class. No.: QA76.9.B45 / B55 2018

Dewey Class. No.: 005.7

Big scientific data managementfirst International Conference, BigSDM 2018, Beijing, China, November 30 - December 1, 2018 : revised selected papers /
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