SCI s the Scientific Structure System and Its Logical Relationship

doi:10.11925/infotech.1003-3513.2001.06.09

New Technology of Library and Information Service

2001, Vol. 17

Issue (6): 24-26 DOI: 10.11925/infotech.1003-3513.2001.06.09

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SCI s the Scientific Structure System and Its Logical Relationship

Wang Xiaoli

(The Library of University of Science and Technology of China, Hefei 230026, China)

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Abstract

This article introduced the scientific structure system and its logical relationship of SCI, and compared the scientific reference idea of print, diskette and web versions and their connections. The article also explained practical operation of different SCI version and related problems. From this article specialists and scholars may learn to use SCI to know the latest development and trend in their fields.

Key words： SCI Citation index Eugene garfield ISI Science and technology

Received: 15 June 2001 Published: 25 December 2001

ZTFLH:

G354　G252.7

Corresponding Authors: Wang Xiaoli

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Cite this article:

Wang Xiaoli. SCI s the Scientific Structure System and Its Logical Relationship. New Technology of Library and Information Service, 2001, 17(6): 24-26.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2001.06.09 OR https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2001/V17/I6/24

[1]Eugene Garfield,Citation Indexes for Science-ANew Dimension in Documentation through Association of Ideas,
SCIENCE,1955V.122,pp108-111

[2]Eugene Garfield,Member IEEE“hat Scientific Journal Can tell Us About Scientific Journals”,IEEETransactions on
Professional Communication V.ol.PC-16,No.4 December 1973,pp.200-202

[3]Eugene Garfield,“Bradford’s Law and Related Statistical Patterns”,Current Contents,19:5-12,May 12,1980

[4]“ience Citation Index A General Introduction”,1980-84SCI

[5]SCI CDEV.4.1

[6]Web of Science V.4.3

[7]И·В·МарШакова“Систма Цитировання Научной Литератры как
Средство Слеженияза Развитием Науки”,1988.USSR(赵云龙等译.《科学引文索引与科学前沿预测》,1992)

[8]师昌绪,田中卓,黄孝瑛,钱浩庆.科学通报,1997,42(8):2343-2352

[9]李海靖等.“利用《科学引文索引》进行科研成果评价”.情报理论与实践,1999,22(5):359-360

[10]肖宏.美国科学信息研究所极其产品.科学,1999,51(3):60-61

[11]丁学东.《文献计量学基础》.北京大学出版社,1993

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