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

Kenning Arlitsch,Minh Thi Ngoc Pham,Jonathan Wheeler,Nikolaus Nova Parulian

doi:10.1108/oir-08-2020-0328

Abstract

PurposeThis 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/approachThe 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.FindingsThe 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/implicationsThe 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/valueThis 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 reviewThe peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-08-2020-0328

Highlights

The Repository Analytics and Metrics Portal (RAMP) is a web service that aggregates performance and use data of institutional repositories (IR); it produces a unique dataset of standardized metrics across time [1]
The RAMP dataset is composed of Google Search Console (GSC) data aggregated from registered repositories
The findings reported below represent a webometric analysis of RAMP data

Summary

Introduction

The Repository Analytics and Metrics Portal (RAMP) is a web service that aggregates performance and use data of institutional repositories (IR); it produces a unique dataset of standardized metrics across time [1]. RAMP tracks items from registered repositories that have surfaced in search results across all Google properties, including data that show whether users clicked through to the IR and downloaded the file. The RAMP dataset is composed of Google Search Console (GSC) data aggregated from registered repositories. It is the first openly published dataset of use and performance data aggregated from a cross platform set of IR in multiple countries, using a common set of metrics. The page-click data include the Uniform Resource Locator (URL) of every item that appeared in the SERP, which opens significant possibilities for additional research if the metadata of those items were mined

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