Mining library and university data to understand library use patterns

• Published in: Electronic library Vol. 33; no. 3; pp. 355 - 372
• Main Authors: Renaud, John, Britton, Scott, Wang, Dingding, Ogihara, Mitsunori
• Format: Journal Article
• Language: English
• Published: Oxford Emerald Group Publishing Limited 01.01.2015
• Subjects: Academic Achievement; Academic libraries; Administrator Surveys; Collection; College campuses; College students; Computer science; Correlation analysis; Data analysis; Data collection; Data mining; Data processing; Datasets; Departments; Evidence; Grade Point Average; Graduate Students; Information retrieval; Integrated library systems-ILS; Law; Librarians; Librarianship/library management; Libraries; Library & information science; Library collections; Library Materials; Library Networks; Library Research; Library Services; Library technology; Library use studies; Library users; Prints; Privacy; Rating of; Records (Forms); Scholarly communication; Universities; Data collection; Data analysis; Data handling; User studies; Academic libraries; Collections management
• ISSN: 0264-0473; 1758-616X
• DOI: 10.1108/EL-07-2013-0136

Purpose – Library data are often hard to analyze because these data come from unconnected sources, and the data sets can be very large. Furthermore, the desire to protect user privacy has prevented the retention of data that could be used to correlate library data to non-library data. The research team used data mining to determine library use patterns and to determine whether library use correlated to students’ grade point average. Design/methodology/approach – A research team collected and analyzed data from the libraries, registrar and human resources. All data sets were uploaded into a single, secure data warehouse, allowing them to be analyzed and correlated. Findings – The analysis revealed patterns of library use by academic department, patterns of book use over 20 years and correlations between library use and grade point average. Research limitations/implications – Analysis of more narrowly defined user populations and collections will help develop targeted outreach efforts and manage the print collections. The data used are from one university; therefore, similar research is needed at other institutions to determine whether these findings are generalizable. Practical implications – The unexpected use of the central library by those affiliated with law resulted in cross-education of law and central library staff. Management of the print collections and user outreach efforts will reflect more nuanced selection of subject areas and departments. Originality/value – A model is suggested for campus partnerships that enables data mining of sensitive library and campus information.