理论研究

大数据语境下情报学的坚守与拓展

  • 韩毅 ,
  • 李红
展开
  • 西南大学计算机与信息科学学院 重庆 400715
韩毅(ORCID:0000-0001-7021-3229),教授,博士,E-mail:hanyi72@swu.edu.cn;李红,硕士研究生.

收稿日期: 2015-01-21

  修回日期: 2015-02-20

  网络出版日期: 2015-03-05

基金资助

本文系重庆市研究生教育教学改革研究项目"面向密集数据范式的情报学研究生教学模式改革及质量控制研究"(项目编号:yjg123090)研究成果之一.

Persistence and Expansion of Information Science Under the Context of Big Data

  • Han Yi ,
  • Li Hong
Expand
  • College of Computer and Information Science, Southwest University, Chongqing 400715

Received date: 2015-01-21

  Revised date: 2015-02-20

  Online published: 2015-03-05

摘要

[目的/意义]研究情报学如何响应大数据语境提出的功能要求,在研究内容、方法及范式上做出相应的调整与聚焦.[方法/过程]应用历史分析方法,梳理总结情报学应对纸介质信息爆炸时在文献选择、内容揭示、服务提供及技术应用等方面积累的经验;应用规范化方法分析大数据时代对情报学在服务对象、信息获取、信息序化和决策支持上的挑战,基于情报学的三维范畴描述讨论情报学在信息发现、信息序化、信息服务、信息技术与信息政策法规等方面的新研究取向.[结果/结论]大数据时代,情报学既应坚守历史演化所积累的学科特色,也应积极响应时代挑战,拓展新的研究领域.

本文引用格式

韩毅 , 李红 . 大数据语境下情报学的坚守与拓展[J]. 图书情报工作, 2015 , 59(5) : 47 -52,81 . DOI: 10.13266/j.issn.0252-3116.2015.05.008

Abstract

[Purpose/significance] The functional needs for the big data context must be answered in Information Science, and the research contents, methods and paradigm should be adjusted and focused.[Method/process] The countermeasures to overcome information exposures in paper-media era are discussed, including documentation selection, information organization, information services and information technologies. The challenges to Information Science, under the context of big data, are analyzed, which include service objects, information discoveries, information organization and decision supporting. 3-dimension structure for Information Science are given, and some new research orientations are presented, which are about information discoveries, information organization, information services, information technologies and information rules and laws. [Result/conclusion] Under the era of big data, on the one hand, Information Science should persist the accumulating discipline characteristics from the history evolution; on the other hand it should respond to the challenges of the times to expand brand-new research fields.

参考文献

[1] 姜奇平.大数据时代到来[EB/OL].[2014-09-28]. http://www.ciweek.com/article/2012/0118/A20120118554491.shtml.
[2] 什么是大数据[EB/OL]?[2014-10-18].http://www.enet.com.cn/article/2012/0907/A20120907159678.shtml.
[3] Hey T, Tansley S, Tolle K.第四范式:数据密集型科学发现[M].潘教峰,张晓林,译.北京:科学出版社,2012:序言.
[4] Big data[J]. Nature, 2008, 455(7209): 1-136.
[5] Dealing with data[J]. Science, 2011,331(6018): 639-806.
[6] 大数据趋势报告:解读大数据的商业价值和战略意义[EB/OL].[2014-10-25]. http://wenku.baidu.com/view/34b43f16be1e650e53ea9909.html.
[7] 美国政府:大数据研究与发展计划[EB/OL].[2014-10-25]. http://max.book118.com/html/2014/0816/9446225.shtm.
[8] 舍恩伯格,库克耶.大数据时代[M].盛杨燕,周涛,译.杭州:浙江人民出版社,2013:序言.
[9] 周晓英.数据密集型科学研究范式的兴趣与情报学的应对[J].情报资料工作,2012(2):5-12.
[10] 行业数据[J].今日印刷,2011(10):1-2.
[11] 肖鹏.1958年国际科学情报会议综述及其历史意义[J].情报资料工作,2011(5):27-31.
[12] Hahn T B. What has information science contributed to the world[EB/OL]? [2014-11-07]. http://www.asis.org/bulletin/Apr-03/presidents.html.
[13] 韩毅,李健.图书馆学、情报学与档案学的共性与差异分析[J].情报资料工作,2012(4):5-11.
[14] 大数据:下一个创新、竞争和生产率的前沿[EB/OL].[2014-10-25]. http://www.docin.com/p-649049551.html.
[15] IBM.What is big data[EB/OL] ?[2014-11-20]. http://www.ibm.com/big-data/us/en/.
[16] 马费成.情报学的进展与深化[J].情报学报,1996,15(5):338-344.
[17] 包昌火,李艳.情报缺失的中国情报学[J].情报学报,2007,26(1):29-34.
[18] Zins C. Conceptions of information science[J]. Journal of the American Society for Information Science and Technology, 2007,58(3):335-350.
[19] Buckland M. What kind of science can information science be[J]? Journal of the American Society for Information Science and Technology, 2012,63(1):1-7.
[20] 韩毅,李健,张克菊.我国情报学共同体的历史源流[J].图书情报工作,2009,52(20):35-38,34.
[21] 彭宁波. 信息自组织的产生、形成和发展探析[J]. 图书馆学研究,2010(7):10-13.

文章导航

/