Measured in a context: making sense of open access book data

Ronald Snijder

doi:10.1629/uksg.627

Abstract

Open access (OA) book platforms, such as JSTOR, OAPEN Library or Google Books, have been available for over a decade. Each platform shows usage data, but this results in confusion about how well an individual book is performing overall. Even within one platform, there are considerable usage differences between subjects and languages. Some context is therefore necessary to make sense of OA books usage data. A possible solution is a new metric – the Transparent Open Access Normalized Index (TOANI) score. It is designed to provide a simple answer to the question of how well an individual open access book or chapter is performing. The transparency is based on clear rules, and by making all of the data used visible. The data is normalized, using a common scale for the complete collection of an open access book platform and, to keep the level of complexity as low as possible, the score is based on a simple metric. As a proof of the concept, the usage of over 18,000 open access books and chapters in the OAPEN Library has been analysed, to determine whether each individual title has performed as well as can be expected compared to similar titles.

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Measured in a context: making sense of open access book data

Abstract

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