This study explored spatial usage of a public library based on activity logs produced by real users. The purpose of this paper is to provide preliminary data for decision-making when establishing the library operation policy.
To achieve the goal, the author collected a variety of data including 274,242 seat reservations logs, 3,361,284 collection usage logs, and 96,098 user information for the four years in which the National Library of Korea, Sejong actually operated. The crawled data were analyzed statistically in terms of demography, month, day of week, time of day and room by room. The author conducted additional in-depth analysis according to the external factors such as weather or social demographic environment. Finally, the author discussed several issues and verified feasibility of the proposals to support decision-making in operating a library in conclusion with a secondary librarian interview.
The usage rate in all the spaces of the National Library of Korea, Sejong, has been increasing since its opening, and, in particular, the usage rate increases sharply in January, February, July and August. In addition, the usage rate during weekends was higher than that during weekdays, and all the four spaces had a high usage rate during the afternoon. These results seem to be related to weather, users’ life pattern, users’ age, and position of PCs and seats. Based on the circulation logs analysis of children’s collections, users in their 10s and 40s showed the same space usage pattern.
This study has significance in that it attempted to analyze logs produced by real users during the actual library operation period, which has not been frequently attempted in the previous studies on libraries. The findings will be provided as basic data to support decision-making for efficient operation of libraries.
This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2016S1A5B8913575).
Kim, T.-Y., Gang, J.-Y. and Oh, H.-J. (2020), "Spatial usage analysis based on user activity big data logs in library", Library Hi Tech, Vol. 38 No. 3, pp. 678-698. https://doi.org/10.1108/LHT-11-2018-0182
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