Surfacing the Academic Long Tail (SALT)

Lead institution: MIMAS, University of Manchester
Project home page:
Project hypothesis:
Library circulation activity data can be used to support humanities research by surfacing underused "long tail" library materials through search.
Overwhelmingly, the groups found the recommender useful. They were keen that their comments be fed back to developers and that work should continue on the recommender to get the results right as they were keen to use it and hoped it would be available soon. Further details can be found in the evaluation .
Project description
SALT will test the hypothesis that Library circulation activity data can be used to support humanities research by surfacing underused ‘long tail’ library materials through search. We will investigate how issues of relevance and frequency of borrowing might shift within the particular use case of humanities research. An API onto JRUL’s ten years of circulation data will be made available to the HE/FE community, and the project will pay specific attention to the sustainability of an API service as a national shared service for HE/FE that both supports users and drives institutional efficiencies (eg collections management).
Working with ten years+ of aggregated and anonymised circulation data amassed by JRUL. Our approach will be to develop an API onto that data, which in turn we'll use to develop the recommender functionality in both services.
Our overall aim is that by working collaboratively with other institutions and Research Libraries UK, the SALT project will advance our knowledge and understanding of how best to support research in the 21st century. Libraries are a rich source of valuable information, but sometimes the sheer volume of materials they hold can be overwhelming even to the most experienced researcher — and we know that researchers’ expectation on how to discover content is shifting in an increasingly personalised digital world. We know that library users — particularly those researching niche or specialist subjects — are often seeking content based on a recommendation from a contemporary, a peer, colleagues or academic tutors. The SALT Project aims to provide libraries with the ability to provide users with that information. Similar to Amazons, ‘customers who bought this item also bought….’ the recommenders on this system will appear on a local library catalogue and on COPAC and will be based on circulation data which has been gathered over the past 10 years at The University of Manchester’s internationally renowned research library.
Extracting data
Further work
The project suggests the following further work.