TY - JOUR
T1 - Design and implementation of scientific research big data service platform for experimental data managing
AU - Fan, Zeqiu
AU - Zhou, Huan
AU - Chen, Zixin
AU - Hong, Daocheng
AU - Wang, Ye
AU - Dong, Qiwen
N1 - Publisher Copyright:
© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of KES International.
PY - 2021
Y1 - 2021
N2 - The goal of the scientific research big data service platform for experimental data managing is to solve the problem of data silos in the state-owned scientific research management system caused by backward informatization. The new data service platform integrates data collection, data analysis, data governance, monitoring and management, prediction and early warning, and visualization platform. We are committed to improving data management and service capability with informatization, and to grasp the material development and design situation timely and accurately. The goal of our platform is to truly use data to speak, manage and make decisions with data.
AB - The goal of the scientific research big data service platform for experimental data managing is to solve the problem of data silos in the state-owned scientific research management system caused by backward informatization. The new data service platform integrates data collection, data analysis, data governance, monitoring and management, prediction and early warning, and visualization platform. We are committed to improving data management and service capability with informatization, and to grasp the material development and design situation timely and accurately. The goal of our platform is to truly use data to speak, manage and make decisions with data.
KW - Big data
KW - Hadoop
KW - Platform
UR - https://www.scopus.com/pages/publications/85116938612
U2 - 10.1016/j.procs.2021.09.162
DO - 10.1016/j.procs.2021.09.162
M3 - 会议文章
AN - SCOPUS:85116938612
SN - 1877-0509
VL - 192
SP - 3875
EP - 3884
JO - Procedia Computer Science
JF - Procedia Computer Science
T2 - 25th KES International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2021
Y2 - 8 September 2021 through 10 September 2021
ER -