Big Scientific Data Management First International Conference, BigSDM 2018, Beijing, China, November 30 - December 1, 2018, Revised Selected Papers /

• Corporate Author: SpringerLink (Online service)
• Other Authors: Li, Jianhui (Editor, http://id.loc.gov/vocabulary/relators/edt), Meng, Xiaofeng (Editor, http://id.loc.gov/vocabulary/relators/edt), Zhang, Ying (Editor, http://id.loc.gov/vocabulary/relators/edt), Cui, Wenjuan (Editor, http://id.loc.gov/vocabulary/relators/edt), Du, Zhihui (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: Information Systems and Applications, incl. Internet/Web, and HCI ; 11473
• Subjects: Big data.; Computers.; Computer organization.; Artificial intelligence.; Management information systems.; Computer science.; Computer security.; Big Data.; Information Systems and Communication Service.; Computer Systems Organization and Communication Networks.; Artificial Intelligence.; Management of Computing and Information Systems.; Systems and Data Security.

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....

Table of Contents:

• 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.