Lisa Charnock and Andy Land from Mimas/John Rylands University (JRUL) respectively. JISC funded project ‘SALT’ (Surfacing the Academic Long Tail). JRUL had a lot of usage data. Hypothesis:
“Library circulation activity data can be used to support humanities research by surfacing the long tail …”
So essentially about developing ‘recommendation services’
Also wanted to look at possibility of developing and API-based national shared service.
Looked at work by Dave Pattern at Huddersfield which built recommendations into their OPAC. Wanted to build on the JISC MOSAIC project.
Market Research by MIMAS shows:
Seredipity still very important in terms of discovery
Increase in Anxiety for researchers – worried that they are ‘missing out’ on material that is out there but they aren’t finding
Trust concerns – who is making this recommendation, where does the data come from, why is this being recommended
Students tended to be sceptical of tagging and reviews, but saw potential benefit of recommendations in the style of Amazon (although again trust issues came up)
JRUL interested as different ways of surfacing content. The process for data was:
- Loan transaction data extracted
- Data anonymised and given to Mimas
- Mimas processes data
- API implemented in Capita Prism sandbox using JUICE framework
- Additional processing performed on demand by API
API also been implemented in COPAC prototype interface.
Wanted to look at how real researchers found the process. Did two rounds of testing – first round found that they generally wouldn’t borrow the recommendations. However, when tweaked thresholds for recommendation, and ran the research again, found a complete swing to the other extreme, that most would borrow the things recommended – shows getting these thresholds right is key and subtle.
100% of those consulted would welcome a recommender function based on circulation records – even though they thought some of the recommendations were irrelevant…
What about a shared service? Some interest, but question of ‘why should we prioritise this’ from potential (library) partners – needs more work on the business case (find this baffling – speaks for itself for me but there you go…)
JRUL now going to test the recommender with subject librarians, and planning to go live either with local service, or national service if that gets off the ground). Will be making SALT recommendations alongside bX recommendations in new discovery interface at JRUL (Primo)
Thinking about allowing users to adjust thresholds to their own satisfaction, rather than dictating them.
Mimas want to:
Aggregate more data
Evaluate the longer-term impact on borrowing patterns at JRUL
Gather requirements/costs for a shared service
Investigate how activity data aggregations could be used to support collection development
See blog for more http://salt11.wordpress.com and also more on SALT and other activity data projects at http://www.activitydata.org
Q & A:
Q: Is software/data made available?
A: Yes – Juice extension on the juice site (couldn’t find it); Data has been released for others to use; other s/w and API will be released
Q: What about privacy issues?
A: Generally these projects have collected data at a high level – so can’t identify individuals;
A: Growing expectation that data will be made open – so need to consider this