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An Analysis of Library User and Circulation Status based on Bigdata Logs A Case Study of National Library of Korea, Sejong

빅데이터 로그 기반 도서관 이용자 및 대출 현황 분석 - 국립세종도서관을 중심으로 -

  • 김태영 (전북대학교 일반대학원 기록관리학과) ;
  • 백지연 (전북대학교 일반대학원 기록관리학과) ;
  • 오효정 (전북대학교 기록관리학과, 문화융복합아카이빙연구소)
  • Received : 2018.05.20
  • Accepted : 2018.06.21
  • Published : 2018.06.30

Abstract

This study aims to analyze library user and circulation status based on the bigdata logs to identify characteristics by user group and propose methods for efficient management of library. The logs to be analyzed consist of user information, circulation information, service usage information registered at the National Library of Korea, Sejong. The user information logs contain 107,369 age data, 106,918 gender data, 106,838 residential data. The circulation information logs contain 536,083 circulation user data, 6,509,369 circulation count data, and the service usage information logs contain 82,813 data. For the analysis of characteristics by user group, the data were used for analyzing user status by age, gender, residence and circulation status by year, month, day. In addition, this study conducts FGI(Focus Group Interview) and linkage analysis with external data to identify factors for analysis results. Based on analysis results, improvement methods for helping library make effective decision-making were proposed. This study analyze empirically user and circulation status based on bigdata logs, and it has significance for being different form proceeding researches with less analysis data.

본 연구는 빅데이터 로그를 기반으로 도서관 이용자 및 대출 현황을 분석함으로써 이용자 그룹별특성을 파악하고 궁극적으로는 도서관의 효율적인 운영 방안을 제안하는데 그 목적이 있다. 분석 대상 로그는 국립세종도서관에 등록된 이용자 정보, 대출 정보, 서비스 이용 정보로 구성되어 있으며, 이 중 이용자 관련 정보로는 연령 정보 107,369건, 성별 정보 106,918건, 거주지 정보 106,838건이 활용되었다. 대출 관련 정보로는 대출 이용자 정보 536,083건, 대출 횟수 정보 6,509,369건이, 서비스 이용 정보로는 82,813건이 활용되었다. 이용자 그룹별특성 분석은 연령별, 성별, 거주지별 이용자 현황 분석 및 연도별, 월별, 요일별 대출 현황 분석 등 다각도로 진행되었다. 뿐만 아니라 이용 현황 결과의 요인을 파악하기 위해 FGI 및 외부 데이터와의 연계 분석도 수행하였다. 이를 토대로 향후 국립세종도서관 운영 시 효율적인 의사결정에 도움을 줄 수 있는 개선 방안을 제안하였다. 본 연구는 분석 데이터가 적은 기존 연구와는 달리 실제 도서관 운영 시 발생한 빅데이터 로그를 기반으로 이용자 및 대출 현황을 실증적으로 분석하였다는 점에서 의의가 있다.

Keywords

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