As academic libraries are increasingly supported by a matrix of database functions, the use of data mining and visualization techniques offer significant potential for future collection development and service initiatives based on quantifiable data. While data collection techniques are still not standardized and results may be skewed because of granularity problems, faulty algorithms, and a host of other factors, useful baseline data is extractable and broad trends can be identified. The purpose of the current study is to provide an initial assessment of data associated with science monograph collection at the Marston Science Library (MSL), University of Florida. These sciences fall within the major Library of Congress Classification schedules of Q, S, and T, excluding TR, TT, and TX. The Rs are also excluded as these subjects are the responsibility of the Health Science Center Library which is connected with the medical school and the teaching hospital. The overall strategy of this project is to look at the potential science audiences within the university community and analyze data related to purchasing and circulation patterns, e-book usage, and interlibrary loan (ILL) statistics. This paper presents the results from the academic year July 1, 2008 to June 30, 2009, because all data reservoirs needed were available for the circulation and ILL data. The Springer e-book study is based on 2009 data. The research team consisted of both librarians and technical support staff from MSL, the Acquisitions Department, the Cataloging Department, and the IT Department. (Contains 1 table and 11 charts.)