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Journal Of Korean Biblia Society for Library and Information Science

  • P-ISSN1229-2435
  • E-ISSN2799-4767
  • KCI

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Vol.24 No.4

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Understanding Big Data and Utilizing its Analysis into Library and Information Services

Journal Of Korean Biblia Society for Library and Information Science / Journal Of Korean Biblia Society for Library and Information Science, (P)1229-2435; (E)2799-4767
2013, v.24 no.4, pp.53-73
https://doi.org/10.14699/kbiblia.2013.24.4.053
Lee, Jeong-Mee
Lee,, J. (2013). Understanding Big Data and Utilizing its Analysis into Library and Information Services. , 24(4), 53-73, https://doi.org/10.14699/kbiblia.2013.24.4.053

Abstract

This study revisits issues for Big data. Three research questions, understanding the concept of Big data, important issues of Big data research and utilization methods for library information services, are explored by the literature and practice reviews. Study results revealed several important issues of Big data including the concept in the context of real world situation, the problems with the accuracy and reliability of the data, privacy and ethical issues, and issues of intellectual property rights. With understanding these issues, a few utilization methods were introduced for Library and Information services. It was included using its analysis for developing vision, adopting Library management, supporting community services, and providing customized information services for various users. The study concluded Big data analysis would effectively provide valid evidences for all those services.

keywords
빅데이터, 빅데이터 분석학, 정보서비스, 데이터마이닝, 문헌정보학

Reference

1.

(2012). Social Big DATA의 의미와 트렌드 분석. Local Information Magazine, 74(May, June), 52-57.

2.

(2013). 빅데이터를 활용한 맞춤형 교육 서비스 활성화 방안연구. 지능정보연구, 19(2), 87-100.

3.

(2013). 빅데이터 기반의 고도분석체계 도입을 통한 기업혁신: 사례와 방법론. Practice & 중소기업 포럼, 20(1), 43-49.

4.

Kim, Yong;. (2012). A Study on the Introduction of Library Services Based on Cloud Computing. Journal of the Korean BIBLIA Society for library and Information Science, 23(3), 57-84.

5.

(2012). 빅데이터의 분석과 활용. 정보과학회지, 30(6), 25-32.

6.

(2013). 빅데이터 처리를 위한 과학클라우드. 한국콘텐츠학회지, 11(1), 40-45.

7.

(2013). 빅(Big)데이터 vs 빈(空)데이터. 마케팅, 47(2), 9-15.

8.

(2013). 트렌드를 알면 해법이 보인다: 2013년 국가정보화 트렌드 설문조사 결과를 중심으로. Local Information Magazine, 79(March, April), 56-59.

9.

(2013). 메타지노믹스 - 빅데이터 시대의 새로운 도전. 정보과학회지, 31(8), 19-26.

10.

(2013). 빅데이터와 클라우드 시대. 정보와통신, , 3-6.

11.

(2013). 문화산업에서 빅데이터의 활용 방안에 관한 연구. 글로벌문화콘텐츠, 10, 157-180.

12.

(2013). 지배양식의 국면 변화와 빅데이터 감시의 형성. 사이버커뮤니케이션학보, 30(2), 191-230.

13.

Lee, Mi-Yeong;Choe, Wan;. (2012). 빅데이터 분석을 위한 빅데이터 처리 기술 동향. Korea Information Processing Society Review, 19(2), 20-28.

14.

(2013). 소셜 빅데이터 이슈 탐지 및 예측분석 기술 동향. 전자통신동향분석, 28(1), 62-71.

15.

(2012). 빅데이터 정의, 활용 및 동향. 한국정보기술학회지, 10(3), 10-19.

16.

(2012). 미래 지식 서비스를 위한 빅데이터 처리의 기술적 요구사항. 정보처리학회지, 19(2), 5-10.

17.

(2012). 빅데이터 시대에 효과적인 시각커뮤니케이션을 위한 인포그래픽 연구. 한국과학예술포럼, 11(1), 165-175.

18.

(2013). 빅데이터 기반 맞춤형 교육 서비스 (77-78). 한국인터넷정보학회 학술대회 발표집.

19.

(2012). Critical Questions for Big Data: Provocations for Cultural, Technical, and Scholarly Phenomenon. Information, Communication & Society, 15(5), 662-679. 10.1080/1369118X.2012.678878.

20.

(2012). Lessons for Big-data Projects. Nature, 489(September), 49-51. 10.1038/489049a.

21.

Social Privacy in Networked Publics: Teens' Attitudes, Practices, and Strategies. paper given at Oxford Internet Institute, [online].

22.

Big-Data Computing: Creating Revolutionary Breakthroughs in Commerce, Science, and Society. [online].

23.

(2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly, 36(4), 1165-1188.

24.

Extracting Value from Chaos. IDC Iview. [online].

25.

Gartner Identifies the Top 10 Strategic Technology Trends for 2013. [online].

26.

(2009). The Pathologies of Big Data. Communications of the ACM, 52(8), 36-44.

27.

The Contours and Challenges of e-Research;E-research: Transformations in Scholarly Practice.

28.

Big Data is a Big Deal. [online].

29.

Toolkit: Board- Ready Slides on Big Data Trends and Opportunities.

30.

(2012). A Bibliometric Chronicling of Library and Information Science's First Hundred Years. Journal of the American Society for Information Science & Technology, 63(5), 997-1016. 10.1002/asi.22645.

31.

What is Data Science? Sebastopol, CA: O'Reilly Media. [online].

32.

(2013). Informational Facts and the Metainformation Inherent in Ifacts: The Soul of Data Sciences. Journal of Library Metadata, 13(1), 59-74. 10.1080/19386389.2013.778732.

33.

Big Data: The Next Frontier for Innovation, Competition, and Productivity. McKinsey Global Institute. [online].

34.

(2012). Big Data: The Management Revolution. Harvard Business Review, 90(10), 60-66.

35.

(2013). Big-data in Cloud Computing: A Taxonomy of Risks. Information Research, 18(1), 571.

36.

(2013). Decomposing Social and Semantic Networks in Emerging "Big Data" Research. Journal of Informetrics, 7, 756-765. 10.1016/j.joi.2013.05.004.

37.

(2012). View on Big Data and Its Relation to Informetrics. Chinese Journal of Library and Information Science, 5(3), 12-26.

38.

(2012). What Your Tweets Tell Us About You: Identity, Ownership and Privacy of Twitter Data. The International Journal of Digital Curation, 7(1), 174-197. 10.2218/ijdc.v7i1.224.

39.

(2008). Information-Centered Research for a Large-scale Analysis of New Information Sources. Journal of the American Society for Information Science and Technology, 59(9), 1523-1527. 10.1002/asi.20829.

40.

(2012). Library and Information Science in the Big Data Era: Funding, Projects, and Future. Proceedings of the American Society for Information Science and Technology, 49(1), 1-3.

41.

Big Data: What It is and Why You Should Care. White Paper, IDC. [online].

Journal Of Korean Biblia Society for Library and Information Science

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