Research Article: “An Analysis of Use and Performance Data Aggregated From 35 Institutional Repositories”

The full text article linked to below was published online earlier today.

Title

An Analysis of Use and Performance Data Aggregated From 35 Institutional Repositories

Authors

Kenning Arlitsch
Montana State University

Jonathan Wheeler
University of New Mexico

Minh Thi Ngoc Pham
University of Missouri

Nikolaus Nova Parulian
University of Illinois at Urbana-Champaign

Source

Online Information Review
Vol. A Head-of-Print No. Ahead-of-Print
DOI: 10.1108/OIR-08-2020-0328

Abstract

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.

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