Big Scientific Data Management

First International Conference, BigSDM 2018, Beijing, China, November 30 - December 1, 2018, Revised Selected Papers
1. Auflage 2019
ISBN: 978-3-030-28060-4
Verlag: Springer International Publishing

Buch, Englisch, 332 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 528 g

Reihe: Information Systems and Applications, incl. Internet/Web, and HCI

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.

Zielgruppe

Research

Autoren/Hrsg.

Li, Jianhui

Meng, Xiaofeng

Du, Zhihui

Zhang, Ying

Cui, Wenjuan

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Big Data
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Computeranwendungen in Wissenschaft & Technologie

Inhaltsverzeichnis

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.