Abstract
Scientific user facilities provide physical resources and technical support that enable scientists to conduct experiments or simulations pertinent to their respective research. One metric for evaluating the scientific value or impact of a facility is the number of publications by users as a direct result of using that facility. Unfortunately, for a variety of reasons, capturing accurate values for this metric proves time consuming and error-prone. This work describes a new approach that leverages automated browser technology combined with text analytics to reduce the time and error involved in identifying publications related to user facilities. With this approach, scientific user facilities gain more accurate measures of their impact as well as insight into policy revisions for user access.
