The SALT project plan is now available
I’m currently project managing, SALT, but my own area of interest is evaluation and user behaviour – So I’m going to be taking on an active role in putting what we develop in front of the right users (we’re thinking academics here at the University) to see what their reactions might be. As I think this over, a number of questions and issues come to mind. Are we more likely to look on things favourably if they are recommended by a friend? If we think about what music we listen to, films we go and see, TV we watch and books we read, are we far more likely to do any of those things should we receive a recommendation from someone we trust, or someone we know likes the same things that we like? If you think the answer to this is yes, then is there any reason that we wouldn’t do the same thing should a colleague or peer recommend a book to us that would help us in our research? In fact more so? Going to see a film that a friend recommends that is, well average, it has far less lasting consequences then completing a dissertation that fails to acknowledge some key texts. As a researcher would you value a service which could suggest to you other books which relate to the books you’ve just searched for in your library?
We know library users very rarely take out one book. Researchers borrowing library books tend to search for them centrifugally, one book leads to another, as they dig deeper into the subject area, finding rarer items and more niche materials. So if those materials have been of use to them, could they not also be of use to other people researching in the same area? The University of Manchester’s library is stocked with rare and niche collections, but are they turning up within traditional searching, or are they hidden down at that long end of the tail? By recommending books to humanities researchers that other humanities researchers have borrowed from the library I’m really hoping we can help improve the quality of research – we know that solid research means going beyond the prescribed reading list, and discussing new or different works. Maybe a recommender function can support this (even if it potentially undermines the authority of the supervisor prescribed list – as one academic has recently suggested to us: “isn’t this the role of the supervisor?”).
Here’s how I’m thinking we’ll run our evaluation: Once the recommender tool is ready, we’ll ask a number of subject librarians to do the first test the tool to see if it recommends what they would expect to see linked to their original search. They will be asked to search the library catalogue for something they know well, when the catalogue returns their search does the recommender tool suggest further reading which seems like a good choice to them? As they choose more unusual books, does the recommender then start suggesting things, which are logically linked, but also more underused materials? Does it start to suggest collections which are rarely used, but never the less just as valuable? Or does it just recommend randomly unrelated items? And can some of the randomness support serendipity?
We’ll then run the same test with humanities researcher (it’ll be interesting to see if librarians and academics have similar responses. As testing facilitators, we’ll also be gauging people’s reactions to the way in which their activity data is used. The question is, do users see this as an invasion of their privacy, or a good way to use the data? Do the benefits of the recommender tool outweigh the concerns over privacy?
The testing of the hypothesis will be crucial indicator as to the legitimacy of the project. Positive results from the user testing will (hopefully) take this project on to the next level, and help us move towards some kind of shared service. But we really need to guage of this segment of more ‘advanced’ users can see the benefit, if they believe that the tool has the ability to make a positive impact on their research, then we hope to extend the project and encourage further libraries to participate. With more support from other libraries then hopefully researchers will be one step closer to receiving a library book recommender.
I’m happy to report that the first set of sample data recently emerged from the library management system (LMS) at John Rylands. This process was not as complex as anticipated since nearly all of the relevant data is in one Sybase table which can easily be exported. Each loaned document in this data is identified by a Talis specific ITEM_ID so a little extra work is required to pull the corresponding ISBN from another table. However, this task is believed to be straightforward.
For info, the sample data was for just a one hour period on one particular day – 9-10am on Tuesday 8th March 2011 since you ask – and comprised details of 839 transactions, amongst which were 159 new loans.
That just leaves us with 3.5 million records to go!
As a bloke wiser than myself once said “A journey of a thousand miles begins with a single step.”