Design and implementation of scientific research big data service platform for experimental data managing

Zeqiu Fan; Huan Zhou; Zixin Chen; Daocheng Hong; Ye Wang; Qiwen Dong

doi:10.1016/j.procs.2021.09.162

Design and implementation of scientific research big data service platform for experimental data managing

Zeqiu Fan
, Huan Zhou^*
, Zixin Chen
, Daocheng Hong
, Ye Wang
, Qiwen Dong

^*Corresponding author for this work

School of Data Science and Engineering

East China Normal University

Research output: Contribution to journal › Conference article › peer-review

4 Scopus citations

Abstract

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.

Original language	English
Pages (from-to)	3875-3884
Number of pages	10
Journal	Procedia Computer Science
Volume	192
DOIs	https://doi.org/10.1016/j.procs.2021.09.162
State	Published - 2021
Event	25th KES International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2021 - Szczecin, Poland Duration: 8 Sep 2021 → 10 Sep 2021

Keywords

Big data
Hadoop
Platform

Access to Document

10.1016/j.procs.2021.09.162

Cite this

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title = "Design and implementation of scientific research big data service platform for experimental data managing",

abstract = "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.",

keywords = "Big data, Hadoop, Platform",

author = "Zeqiu Fan and Huan Zhou and Zixin Chen and Daocheng Hong and Ye Wang and Qiwen Dong",

note = "Publisher Copyright: {\textcopyright} 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.; 25th KES International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2021 ; Conference date: 08-09-2021 Through 10-09-2021",

year = "2021",

doi = "10.1016/j.procs.2021.09.162",

language = "英语",

volume = "192",

pages = "3875--3884",

journal = "Procedia Computer Science",

issn = "1877-0509",

publisher = "Elsevier B.V.",

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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 -

Design and implementation of scientific research big data service platform for experimental data managing

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Keywords

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