But is this what the users want?

I’ll admit it, I’m prepared to out myself, I’ve just finished a post graduate research degree and more than once I have used the Amazon book recommender. In fact when I say more than once, possibly over the course of my studies we’ll be getting into double figures. I’m not ashamed, (I may be about using Wikipedia, but let’s not go there), but I’m not ashamed because I did and so did many of my peers. There may be more traditional methods to conduct academic research, but sometimes, with a deadline looming and very little time for a physical trip to the library to speak to a librarian, finding resources in one or two clicks is just to attractive. My hunch is many other scholars also use this method to conduct research. Recently on another Copac project we facilitated some focus groups. The participants in the groups were postgraduate researchers, a mix of humanities and STEM. Some had used Copac before others had not. Although the focus groups were answering another hypothesis I couldn’t resist asking the gathered group, if they would find merit in a book recommender on Copac which was based on 10 years of library circulation data from a world class research library? It’s not often you see a group of students become visibly excited at the thought of a of new research tool, but they did that night. A book recommender, would make a positive impact on their research practices and was greeted with enthusiasm from the group. I thought it was worth mentioning this incident, because when the going gets tough, and we are drowning under data, it might be worth remembering that users really want this to happen.


Working through the SALT hypothesis

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.

Let the data flow…

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.”

Surfacing the Academic Long Tail — Announcing new work with activity data

We’re pleased to announce that JISC has funded us to work on the SALT (Surfacing the Academic Long Tail) Project, which we’re undertaking with the University of Manchester, John Rylands University Library.

Over the next six months the SALT project will building a recommender prototype for Copac and the JRUL OPAC interface, which will be tested by the communities of users of those services.  Following on from the invaluable work undertaken at the University of Huddersfield, we’ll be 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.   Obviously, we’re indebted to the previous knowledge acquired by a similar project at the University of Huddersfield and the SALT project will work closely with colleagues at Huddersfield (Dave Pattern and Graham Stone) to see what happens when we apply this concept in the research library and national library service contexts.

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.

How effective will this model prove to be for users — particularly humanities researchers users?

Here’s what we want to find out:

  • Will researchers in the field of humanities benefit from receiving book recommendations, and if so, in what ways?
  • Will the users go beyond the reading list and be exposed to rare and niche collections — will new paths of discovery be opened up?
  • Will collections in the library, previously undervalued and underused find a new appreciative audience — will the Long Tail be exposed and exploited for research?
  • Will researchers see new links in their studies, possibly in other disciplines?

We also want to consider if there are other  potential beneficiaries.  By highlighting rarer collections, valuing niche items and bringing to the surface less popular but nevertheless worthy materials, libraries will have the leverage they need to ensure the preservation of these rich materials. Can such data or services assist in decision-making around collections management? We will be consulting with Leeds University Library and the White Rose Consortium, as well as UKRR in this area.

(And finally, as part of our sustainability planning, we want to look at how scalable this approach might be for developing a shared aggregation service of circulation data for UK University Libraries.  We’re working with potential data contributors such as Cambridge University LibraryUniversity of Sussex Library, and the M25 consortium as well as RLUK to trial and provide feedback on the project outputs, with specific attention to the sustainability of an API service as a national shared service for HE/FE that supports academic excellence and drives institutional efficiencies.