Please wait a minute...
New Technology of Library and Information Service  2005, Vol. 21 Issue (6): 70-75    DOI: 10.11925/infotech.1003-3513.2005.06.16
Current Issue | Archive | Adv Search |
Establishing and Optimizing the Common Development and Share  Model of E-government Information Resources
He Zhen
(Management College of Xiangtan University, Hunan 411105, China)
Download: PDF (0 KB)  
Export: BibTeX | EndNote (RIS)      
Abstract  

Based on the function request of human being’s information organ, the common development and share of E-government information resources can be realized by establishing information space based on network. The author thinks that during the research on establishing the common development and share of E-government information resources, we should consider well the relationship of power leading, benefit driving and information exchanges among governments and their working talent section. In general, the model of common development and share can be divided into three types: perpendicular type, level type, and compositive type. To optimize the model, we should follow the principles such as soft principle, institutional principle, tabular principle, and cooperative principle.

Key wordsE-government      Information resources      Common development and share      Model     
Received: 01 March 2005      Published: 25 June 2005
ZTFLH: 

C931.9

 
Corresponding Authors: He Zhen     E-mail: hezheng@xtu.edu.cn
About author:: He Zhen

Cite this article:

He Zhen. Establishing and Optimizing the Common Development and Share  Model of E-government Information Resources. New Technology of Library and Information Service, 2005, 21(6): 70-75.

URL:

http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.1003-3513.2005.06.16     OR     http://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2005/V21/I6/70

1丁宁.信息技术革命与企业组织创新.北京:经济管理出版社,2001.5-6
2(美)约翰·希利·布朗,保罗·杜奎德.信息的社会层面.王铁生,葛立成译.北京:商务印书馆,2003:12-13
3郭良.网络创世纪——从阿帕网到互联网.北京:中国人民大学出版社,1998:162-163
4(美)N·尼葛洛庞帝.数字化生存.胡泳,范海燕译.海口:海南出版社,1996:26
5(法)H·法约尔.工业和一般管理.北京:中国社会科学出版社,1982.转引自刘巨钦.企业组织设计原理与实务.北京:企业管理出版社,1999:6-7
6(英) D·S皮尤.组织理论精萃.北京:中国人民大学出版社,1990:141
7马费成等.信息经济学.武汉:武汉大学出版社,2002:82-83
8查尔斯·M·萨维奇.第五代管理.谢华强等译.珠海:珠海出版社,1998.转引自许晶华.论信息管理的层次结构体系.中国图书馆学报,2000(6):6-10
9唐钧,张晓.全球背景下的中国电子政务建设.理论与改革,2003(2):21-25
10张虹.电子政务与文档一体化.浙江档案,2002(10):6-8
11理查德·A·斯皮内洛.世纪道德:信息技术的伦理方面.刘钢译.北京:中央编译出版社,1999:46
12曾国屏等.赛博空间的哲学探索.北京:清华大学出版社,2002:144
13(美)卡尔·夏皮罗,哈尔·瓦里安.信息规则:网络经济的策略指导.张帆译.北京:中国人民大学出版社,2000:161-162
14Tim Jordan.Cyberpower.TheCulture and Politics of Cyberspace and the Internet.London & New York:Routledge,1999:36-37

[1] Zhao Yang, Zhang Zhixiong, Liu Huan, Ding Liangping. Classification of Chinese Medical Literature with BERT Model[J]. 数据分析与知识发现, 2020, 4(8): 41-49.
[2] Xu Chenfei, Ye Haiying, Bao Ping. Automatic Recognition of Produce Entities from Local Chronicles with Deep Learning[J]. 数据分析与知识发现, 2020, 4(8): 86-97.
[3] Wei Wu, Xie Xingzheng. The Determinants of Continuance Intention to Pay: Empirical Research from Online Knowledge Payment Users[J]. 数据分析与知识发现, 2020, 4(8): 119-129.
[4] Shen Zhihong,Zhao Zihao,Wang Haibo. Big Data Technology Stack Shifting: From SQL Centric to Graph Centric[J]. 数据分析与知识发现, 2020, 4(7): 50-65.
[5] Wang Xinyun,Wang Hao,Deng Sanhong,Zhang Baolong. Classification of Academic Papers for Periodical Selection[J]. 数据分析与知识发现, 2020, 4(7): 96-109.
[6] Yue Lixin,Liu Ziqiang,Hu Zhengyin. Evolution Analysis of Hot Topics with Trend-Prediction[J]. 数据分析与知识发现, 2020, 4(6): 22-34.
[7] Cai Yongming,Liu Lu,Wang Kewei. Identifying Key Users and Topics from Online Learning Community[J]. 数据分析与知识发现, 2020, 4(6): 69-79.
[8] Su Qing,Chen Sizhao,Wu Weimin,Li Xiaomei,Huang Tiankuan. Personalized Recommendation Model Based on Collaborative Filtering Algorithm of Learning Situation[J]. 数据分析与知识发现, 2020, 4(5): 105-117.
[9] Zhang Yi,Yang Yi,Deng Wen. A Systematic Review of Factors Influencing Online Trust[J]. 数据分析与知识发现, 2020, 4(5): 15-26.
[10] Deng Siyi,Le Xiaoqiu. Coreference Resolution Based on Dynamic Semantic Attention[J]. 数据分析与知识发现, 2020, 4(5): 46-53.
[11] Wei Guohui,Zhang Fengcong,Fu Xianjun,Wang Zhenguo. Similarity Measurement of Traditional Chinese Medicine Components for Cold-hot Nature Discrimination[J]. 数据分析与知识发现, 2020, 4(5): 75-83.
[12] Yu Chuanming,Yuan Sai,Zhu Xingyu,Lin Hongjun,Zhang Puliang,An Lu. Research on Deep Learning Based Topic Representation of Hot Events[J]. 数据分析与知识发现, 2020, 4(4): 1-14.
[13] Zhang Dongyu,Cui Zijuan,Li Yingxia,Zhang Wei,Lin Hongfei. Identifying Noun Metaphors with Transformer and BERT[J]. 数据分析与知识发现, 2020, 4(4): 100-108.
[14] Yang Xu,Qian Xiaodong. Synchronous Clustering Algorithm for Social Networks Based on Improved Vicsek Model[J]. 数据分析与知识发现, 2020, 4(4): 119-128.
[15] Pan Youneng,Ni Xiuli. Recommending Online Medical Experts with Labeled-LDA Model[J]. 数据分析与知识发现, 2020, 4(4): 34-43.
  Copyright © 2016 Data Analysis and Knowledge Discovery   Tel/Fax:(010)82626611-6626,82624938   E-mail:jishu@mail.las.ac.cn