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For decades, the corporate sector has exploited technological advances to better market and deliver products and services to customers via the techniques of data mining. The technique was not widely used in libraries. However, with the current emphasis on evidence-based decision making, libraries are beginning to utilize their system- and user- generated data. Data mining usually involves a significant endeavor to extract embedded and potentially useful information from large undiscovered data sets (Mitra & Acharya, 2003; Hand, Mannila & Smyth, 2001; Frawley, Piatetsky-Shapiro, & Matheus 1992; Piatetsky-Shapiro & Frawley 1991). These data mining techniques are being used by librarians to improve both internal decision-making and external user services by extracting information from operational datasets of both bibliographic and user data. OCLC Research has taken advantage of the WorldCat database, which includes more than 95 million bibliographic records and 1.2 billion holdings records, as well as data provided by other major library systems and consortia to develop user-oriented collections and services (http://www.oclc.org/research/projects/mining/).

While libraries have employed policies to protect the data about use of their services, these policies are rarely specific or standardized. Since 1996 the U.S. healthcare system has been grappling with the Health Insurance Portability and Accountability Act (HIPAA), which is designed to provide those handling personal health information with standardized, definitive instructions as to the protection of data. In this work, the authors briefly discuss the present situation of privacy policies about library use data, outline the HIPAA guidelines to understand parallels between the two, and finally propose methods to create a de-identified library data warehouse based on HIPAA for the protection of user privacy.

Bibliomining is the combination of data mining, bibliometrics, statistics, and reporting tools used to extract patterns of behavior-based artifacts and item-based metadata from library systems. The bibliomining process involves the identification of problem areas, the collecting and anonymizing of data into a data warehouse, the exploration of the data with data mining tools, and the analysis, validation, and implementation of the results. This panel will introduce the topic of bibliomining and present ways in which data warehousing and data mining are currently being used in library settings.