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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (1): 9-20    DOI: 10.11925/infotech.2096-3467.2017.1341
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Big Linked Data Management: Challenges, Solutions and Practices
Zhihong Shen1(),Chang Yao2,Yanfei Hou1,Linhuan Wu3,Yuepeng Li1
1(Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China)
2(National Natural Science Foundation, Beijing 100085, China)
3(Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China)
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[Objective] This article analyzed the concept, connotation and characteristics of the big linked data, aiming to explore possible solutions for technical challenges facing its management. [Methods] We proposed a new model based on NoSQL data management, distributed graph computing and big data pipeline technologies, which designed and develop gETL, a large-scale graph data warehouse processing system. [Results] The proposed system was used in NSFC-KBMS and WDCM projects, which effectively manages large-scale knowledge-data and biological data. [Limitations] The proposed system could be improved with new applications. [Conclusions] The NoSQL data storage, distributed graph computing, and big data pipeline technologies, as well as the gETL system, help us address the challenges facing linked big data management.

Key wordsLinked Data      Knowledge Graph      Big Data      Big Linked Data     
Received: 12 December 2017      Published: 05 February 2018

Cite this article:

Zhihong Shen,Chang Yao,Yanfei Hou,Linhuan Wu,Yuepeng Li. Big Linked Data Management: Challenges, Solutions and Practices. Data Analysis and Knowledge Discovery, 2018, 2(1): 9-20.

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