An analysis of use and performance data aggregated from 35 institutional repositories

被引:4
作者
Arlitsch, Kenning [1 ]
Wheeler, Jonathan [2 ]
Pham, Minh Thi Ngoc [3 ]
Parulian, Nikolaus Nova [4 ]
机构
[1] Montana State Univ, Lib, Bozeman, MT 59717 USA
[2] Univ New Mexico, Univ Lib, Albuquerque, NM 87131 USA
[3] Univ Missouri, Sch Informat Sci & Learning Technol, Columbia, MO USA
[4] Univ Illinois, Sch Informat Sci, Champaign, IL USA
关键词
Webometrics; Digital repositories; Institutional repositories; IR; Academic publishing; Web analytics; STATISTICS;
D O I
10.1108/OIR-08-2020-0328
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Purpose - This study demonstrates that aggregated data from the Repository Analytics and Metrics Portal (RAMP) have significant potential to analyze visibility and use of institutional repositories (IR) as well as potential factors affecting their use, including repository size, platform, content, device and global location. The RAMP dataset is unique and public. Design/methodology/approach - The webometrics methodology was followed to aggregate and analyze use and performance data from 35 institutional repositories in seven countries that were registered with the RAMP for a five-month period in 2019. The RAMP aggregates Google Search Console (GSC) data to show IR items that surfaced in search results from all Google properties. Findings - The analyses demonstrate large performance variances across IR as well as low overall use. The findings also show that device use affects search behavior, that different content types such as electronic thesis and dissertation (ETD) may affect use and that searches originating in the Global South show much higher use of mobile devices than in the Global North. Research limitations/implications - The RAMP relies on GSC as its sole data source, resulting in somewhat conservative overall numbers. However, the data are also expected to be as robot free as can be hoped. Originality/value - This may be the first analysis of aggregate use and performance data derived from a global set of IR, using an openly published dataset. RAMP data offer significant research potential with regard to quantifying and characterizing variances in the discoverability and use of IR content. Peer review - The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR08-2020-0328
引用
收藏
页码:316 / 335
页数:20
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