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On 9/20/2012 1:39 PM, Karen Coyle wrote: > > So, given this, and given that in a decent-sized catalog users regularly > retrieve hundreds or thousands of items, what is the best way to help > them "grok" that set given that the number of records is too large for > the user to look at them one-by-one to make a decision? Can the fact > that the data is in a database help users get a "feel" for what they > have retrieved without having to look at every record? I've often felt that, if it can be properly presented, facets are a really great way to do this. Facets (with hit counts next to every value) give you a 'profile' of a result set that is too large for you to get a sense of otherwise, they give you a sort of descriptive statistical summary of it. When the facets are 'actionable', as they are usually, they also let you then drill down to particular aspects of the giant result set you are interested in, and get a _different_ 2.5 screens of results you'll look at. Of course, library studies also often show that our users don't use the facets, heh. But there are a few conflicting studies that shows they are used a significant minority of the time. I think it may have to do with UI issues of how the facets are presented. It's also important to remember that it doesn't neccesarily represent a failure if the user's don't engage with the results beyond the first 2.5 screens -- it may mean they got what they wanted/needed in those first 2.5 screens. And likewise, that it's okay for us libraries to develop features which are used only by significant minorities of our users (important to remember what our logs show is really significant minorities of _uses_. All users using a feature 1% of the time can show up the same as 1% of users using a feature 100% of the time). We are not lowest common denominator, while we need to make our interfaces _usable_ by everyone (lowest common denominator perhaps), it's part of our mission to provide functionality in those interfaces for especially sophisticated uses that won't be used by everyone all the time.