Mining and analyzing digital archive usage data to support collection development decisions

We demonstrate a collection development decision support tool that mines digital archive usage data. We want to better understand the University of Southern California (USC) Digital Archive's collection structure by analyzing the objects' characteristics, by analyzing the relationships between viewed objects, and by understanding usage trends over time. By relying on implicit patterns of usage data, such as co-retrievals, rather than explicit data, such as hit counts, we believe we can make more informed decisions about where to expend our resources