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Data Analysis and Knowledge Discovery  2020, Vol. 4 Issue (2/3): 231-238    DOI: 10.11925/infotech.2096-3467.2019.0600
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Developing Modularity Scientometrics System with Distributed Technology
Shi Hongbo1,2(),Guo Hongmei1,Yue Ting1,2,Qian Li1,2,Huang Dingyu1,Chang Zhijun1
1National Science Library, Chinese Academy of Sciences, Beijing 100190, China
2Department of Library, Information and Archives Management, School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China
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[Objective] This paper designs and develops a modularity scientometrics system, aiming to meet the needs and real time processing tasks facing researchers. [Context] The relational database system cannot manage the vast amount of literature resources, while the distributed technology provides highly efficient computating ability for the scientometrics data.[Methods] We designed a genenal indicator model and a standard task workflow. Then,we built the proposed system based on ES, Redis and modularity indicator designs.[Results] Our platform provides standard workflow for users to conduct scientometrics tasks and receive resluts in almost real time.[Conclusions] The distributed technology and modularity design could help us build a highly efficient and universal scientometrics as well as decision making systems.

Key wordsDistributed Technology      Modularity Analysis      Scientometrics     
Received: 03 June 2019      Published: 26 April 2020
ZTFLH:  TP391  
Corresponding Authors: Hongbo Shi     E-mail:

Cite this article:

Shi Hongbo,Guo Hongmei,Yue Ting,Qian Li,Huang Dingyu,Chang Zhijun. Developing Modularity Scientometrics System with Distributed Technology. Data Analysis and Knowledge Discovery, 2020, 4(2/3): 231-238.

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System Logical Architecture
Task Indicators Management Scheme
Elastic Expansion for Indicator Calculation
Different Queues for Calculation
Comparison of Calculation Process Between ES and Relation Database
Demonstration of Collection Indicator Calculation
Demonstration of the Storage and Utilization of the JSON Results
Selection of Data Source and Statistical Caliber
Selection Process of the Target and Indicators
Final Confirmation of the Task
Indicator Result and Graphical Display
指标个数 计算时间 单指标平均时间
15 64s 4.3s
Indicator Calculation Efficiency
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