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开放政府数据评估体系述评:特点分析

  • 韦忻伶 ,
  • 安小米 ,
  • 李雪梅 ,
  • 明欣 ,
  • 余维健
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  • 1 中国人民大学信息资源管理学院 北京 100872;
    2 中国人民大学智慧城市研究中心 北京 100872
韦忻伶(ORCID:0000-0002-2596-6560),硕士研究生;李雪梅,硕士研究生;明欣,硕士研究生;余维健,硕士研究生。

收稿日期: 2017-06-19

  修回日期: 2017-07-28

  网络出版日期: 2017-09-20

基金资助

国家社会科学基金重大项目"国家数字档案资源整合与服务机制研究"(项目编号:13&ZD184)和中国人民大学科研项目"基于大数据的智慧城市服务关键技术研究及典型应用"子课题"城市大数据集成技术与信息资源整合方法"(项目编号:15XNLQ08)研究成果之一。

A Review of Research and Practice on Open Government Data Assessment:Features and Patterns

  • Wei Xinling ,
  • An Xiaomi ,
  • Li Xuemei ,
  • Ming Xin ,
  • Yu Weijian
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  • 1 School of Information Resource Management, Renmin University of China, Beijing 100872;
    2 Smart City Research Center, Renmin University of China, Beijing 100872

Received date: 2017-06-19

  Revised date: 2017-07-28

  Online published: 2017-09-20

摘要

[目的/意义]随着开放政府数据运动的快速发展,开放政府数据评估体系也在研究和实践中不断出现,对这些评估体系的特点进行分析,有利于采取更科学合理的方法对开放政府数据进行准确评估,推动开放政府数据的可持续发展。[方法/过程]对研究与实践中现有的开放政府数据评估体系进行系统梳理,归纳出现有评估体系的评估动因、评估内容和评估方法及相应特点和适用性。[结果/结论]研究发现现有评估体系在城市层面、特定行业和开放数据成熟度评估方面存在局限,提出应根据不同评估动因、因地制宜地选择评估内容和评估方法的建议,并构建了开放政府数据评估动因、评估内容和评估方法的循环迭代检验机制。

本文引用格式

韦忻伶 , 安小米 , 李雪梅 , 明欣 , 余维健 . 开放政府数据评估体系述评:特点分析[J]. 图书情报工作, 2017 , 61(18) : 119 -127 . DOI: 10.13266/j.issn.0252-3116.2017.18.016

Abstract

[Purpose/significance] With the rapid development of open government data in the world, open government data assessments emerge in research and practice. Analyzing features of these assessments helps to take a more appropriate way to assess future open government data projects, which sustains the development of open government data.[Method/process] With a review of research and practice on the typical current assessment research and programs of open government data, this paper focused on different features of all kinds of assessment systems, which were characterized by different motivations, metrics and methods.[Result/conclusion] The study shows that there are limitations in the assessments which can be applicable to urban fields, specific industry fields and open data maturity assessment. Meanwhile, the study reveals that the assessment metrics and methods should be selected according to different assessment motivations. It is suggested to establish an iteration inspection mechanism.

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