期刊文献+

社会科学领域科学数据的引用现状与特点分析 被引量:12

Research on the Citation Present Situation and Characteristics of Scientific Data in Social Science
下载PDF
导出
摘要 从被引科学数据内容的视角分析社会科学领域科学数据的引用现状与特点。通过抽样调查法获取研究样本,统计样本被引社会科学数据在创建者、类型、被引次数、访问方式、更新次数、规模及时间跨度等方面的概况。结果发现,被引社会科学数据的创建者多是政府机构和研究机构;被引社会科学数据的类型虽多样化,但调查类数据居于主导,被引用次数最多;公众访问和仅ICPSR用户访问的样本数据集的数量相当;大部分被引社会科学数据的时间跨度短、规模小、更新次数少。 Research on the citation present situation and characteristics of scientific data in social science from the perspective of the content of cited scientific data.The sample was obtained by sampling survey method,then statistics the overview of samples from the aspects such as creator,type,citation,the number of updates,size,time span and so on.After analyzing the statistical data,can draw the following conclusions.The creators of cited scientific data are mostly government agencies and research institutions.Although the types of cited scientific data are diversified,the survey data is dominant and the most cited.Public access and only ICPSR user access are equally divided.Most of the cited scientific data has short time span,small scale and less updated time.
作者 屈亚杰 王亚男 QU YaJie;WANG YaNan(The School of Government, Beijing Normal University, Beijing 100875, China;The School of Marxism, Central University of Finance and Economics, Beijing 100081, China)
出处 《数字图书馆论坛》 CSSCI 2017年第6期25-31,共7页 Digital Library Forum
基金 国家社会科学基金项目"云计算环境下图书馆信息资源安全政策法律研究"(编号:11CTQ004)资助
关键词 社会科学 科学数据 引用 Social Science Scientific Data Cite
  • 相关文献

参考文献8

二级参考文献148

  • 1向上.信息系统中的数据质量评价方法研究[J].现代情报,2007,27(3):67-68. 被引量:16
  • 2丁海龙,徐宏炳.数据质量分析及应用[J].计算机技术与发展,2007,17(3):236-238. 被引量:34
  • 3彭洁 涂勇.科学数据引用的探讨.数字图书馆论坛,2008,(10):14-18,45.
  • 4White H. Citation analysis of data files use [J]. Library Trends, 1982, 31(3) : 467 -477.
  • 5Steve L. The age of big data[ N/OL]. The New York Times, [2012 -2 - 11 ] [2012 -8 -28]. http://forum, ccer. edu. cn/showtopic, aspx?topicid = 124765&page = end.
  • 6Jim G. On eScience-A transformed scientific method [C]//Tony H,Stewart T,Kirstin T. The Fourth Paradigm: Data- intensive Scientific Discovery. Redmond,WA: Microsoft Research, 2009 : 19 - 33.
  • 7Wallis J ,Borgman C. Who is responsible for data? An exploratory study of data authorship,ownership and responsibility [ C/OL]// Proceedings of the Annual Meeting of the American Society for Information Science and Technology, 2011, 48:1 -10. [2012 -08 -29]. http://dx. doi. org/10.1002/meet.2011.14504801188.
  • 8UCLA Library. Bridging data lifecycles : Tracking data use via data citation [ EB/OL ]. (2012 - 04 - 05 ) [2012 - 08 - 28]. http://library, ucar. edu/data_workshop/.
  • 9Palmer C,Weber N,Cragin M. The analytic potential of scientific data: Understanding re-use value[ C/OL]//Proceedings of the 74th Annual Meeting of the American Society for Information Science & Technology. Silver Spring, Mary. (2011 - 12 - 10) [2012 - 138 - 28 ]. http ://www. asis. org/asist2011/proceedings/submissions/174_FINAL SUBMIS- SION. pdf.
  • 10White House. Big data fact sheet [EB/OL]. (2012 -03 -29) [2012 -08 -28]. http://www, whitehouse, gov/sites/ defauh/files/micmsites/ostp/big_data fact sheet_final, pdf.

共引文献166

同被引文献166

引证文献12

二级引证文献48

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部