What is it about?

Open Access (OA) repositories are websites hosted by universities and other research organisations that allow anyone to download scientific research papers for free. This includes programs that download papers automatically for both search engines and spammers, which makes download counts very inaccurate. This paper discusses how to filter non-human downloads out of download statistics and how the major repository systems detect web robots.

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Why is it important?

OA repository usage statistics are growing in importance, as part of the broader measurement of research visibility and impact. Most OA repositories are built on free open source software by the (usually non-profit) communities that use them. Web robot detection is a very specialised technical challenge. Until this study, no one has measured how well a repository performs web robot detection or even described in one place how the major systems do this. In addition, this paper reviews the scientific literature to describe and succinctly list the available robot detection techniques.

Perspectives

I started this research because I am very interested in OA repository usage statistics. For me it is a measure of the value of the service that I provide -- a measure of the increase in visibility we have added to our university's research and authors. After several years of performing basic robot detection without having been taught or trained (there is no training for this), I began to wonder how well we were doing. This lead to the study and further research presented at the Open Repositories 2016 conference. The research may serve to improve repository usage statistcs worldwide l as I am now working directly with several major repository developers, and with Project COUNTER.

Joseph W. Greene
University College Dublin

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This page is a summary of: Web robot detection in scholarly Open Access institutional repositories, Library Hi Tech, September 2016, Emerald,
DOI: 10.1108/lht-04-2016-0048.
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