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New Technology of Library and Information Service  2013, Vol. Issue (4): 2-9    DOI: 10.11925/infotech.1003-3513.2013.04.02
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Big Data and Linked Data: The Emerging Data Technology for the Future of Librarianship
Liu Wei, Xia Cuijuan, Zhang Chunjing
Institute of Scientific & Technical Information of Shanghai, Shanghai Library, Shanghai 200031, China
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Abstract  Nowadays the ever growing linked data has broken through the restrictions between the triple structure and the relational model, and tend to use NoSQL approaches more often. More and more Big Data solutions provide semantic annotation and reasoning features.It brings machine readable semantics, rich meaningful linkage and knowledge analytics to the big data, and provide openness and interoperability to applications. The paper introduces the above background, makes difference between BIG Linked Data and LINKED Big Data systems, which the former implies the Big Data approach adopted by the Linked Data community, and the later vice versa. It also comments on the progress and benefit with the two cutting edge data technologies and gives outlooks on the future of the Big and Linked Data mashups.
Key wordsBig Data      Linked Data      Semantic Web      Data technology      Digital library     
Received: 14 March 2013      Published: 17 June 2013
:  TP393  

Cite this article:

Liu Wei, Xia Cuijuan, Zhang Chunjing. Big Data and Linked Data: The Emerging Data Technology for the Future of Librarianship. New Technology of Library and Information Service, 2013, (4): 2-9.

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[1] De Wilde P. A Walk in Graph Database[EB/OL].(2012-05-05).[2013-01-08].
[2] De Marzi M. Introduction to Graph Databases[EB/OL]. (2012-04-29). [2013-01-08].
[3] Hausenblas M, Grossman R, Harth A, et al. Large-Scale Linked Data Processing: Cloud Computing to the Rescue? [EB/OL].(2012-03-01).[2013-01-08].
[4] 刘炜. 关联数据:概念、技术及应用展望[J]. 大学图书馆学报,2011,29(2):5-12.(Liu Wei. Overview on Linked Data: Concept, Technology and Implementation[J]. Journal of Academic Libraries, 2011,29(2):5-12.)
[5] De Wilde P. Small, Medium & Big Data[EB/OL]. (2012-09-26).[2013-01-16].
[6] Dimitrov M. Semantic Technologies for Big Data[EB/OL]. (2012-09-19). [2013-01-18].
[7] Vicknair C, Macias M, Zhao Z,et al.A Comparison of a Graph Database and a Relational Database[EB/OL]. (2013-01-17). [2013-01-20].
[8] Guzenda L. Realize the Value in Your Big Data with Graph Technology[EB/OL]. (2013-01-17). [2013-01-22].
[9] 夏翠娟,刘炜,赵亮,等. 关联数据的发布技术及其实现——以Drupal为例[J]. 中国图书馆学报,2012,38(1):49-57.(Xia Cuijuan, Liu Wei, Zhao Liang,et al.The Current Technologies and Tools for Linked Data: A Case of Drupal[J]. Journal of Library Science in China,2012,38(1):49-57.)
[10] 张春景,刘炜,夏翠娟,等. 关联数据开放应用协议[J]. 中国图书馆学报,2012,38(1):43-48.(Zhang Chunjing, Liu Wei, Xia Cuijuan,et al.The Open Application Licenses of Linked Data[J]. Journal of Library Science in China,2012,38(1):43-48.)
[11] Noels S. NoSQL with HBase and Hadoop[EB/OL]. (2010-06-17).[2013-01-26].
[12] Fujitsu.Linked Data: Connecting and Exploiting Big Data[EB/OL].[2013-01-28].
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