Does adding links to popular databases change user searching behavior? An October 2013 change to the University of Michigan Library’s front page gave us the opportunity to conduct an empirical study and shows that user behavior has changed since the new front page design was launched.
The Library website is not an archive but it does need curation. This past summer I explored archiving legacy content in Deep Blue.
Relevance is a complex concept which reflects aspects of a query, a document, and the user as well as contextual factors. Relevance involves many factors such as the user's preferences, task, stage in their information-seeking, domain knowledge, intent, and the context of a particular search. Tom Burton-West, one of the HathiTrust developers, has been working on practical relevance ranking for all the volumes in HathiTrust for a number of years.
(by Kat Hagedorn, Christina Powell, Lance Stuchell and John Weise) The one constant in digital preservation over the past couple of decades has been change. Digitization standards have changed as equipment has improved and become more affordable, formats have come and gone, and tools have been developed to help with automated format creation and validation. The progress made on this front has been great, but how do we reconcile older content with current digitization and preservation standards?
The last visual refresh to the DLPS Image Class environment updated the layout and styles, but mostly worked the same way. Starting this year, we've been making more drastic changes. These updates were based on what our analytics showed about browser use (larger, wider screens and of course, mobile use) and conversations with collection managers.
How much do people actually read on the web? Not much. UX Myths presents the evidence.
More than 15% of user searches for the seven most commonly used databases on the University of Michigan Library’s website were misspellings of the database name. We looked through our search logs for the three months spanning January 1-April 2, 2014, to find correct and likely incorrect search queries.
Page 1 of 12