Increasing our reliance on automated access mechanisms such as data mining tools seems to be just a matter of time. It is unlikely that libraries will continue to satisfy patrons' information needs using the traditional catalogs as the primary access mechanisms. To be certain, online catalogs provide good access to books, films, microfiche, audio tapes, and other materials traditionally kept in libraries. However, few, if any, libraries have succeeded in using their online catalogs to provide adequate access to a significant number of digital materials. In an era where information costs rapidly increase while budgets remain flat, libraries must find alternatives to slow, awkward, and expensive manual cataloging.
Data mining is a form of artificial intelligence that uses automated processes to find information.
Although its use in libraries is limited, data mining has been used successfully for several years in the scientific and business communities for tracking behavior of individuals and groups, processing medical information, and a number of other applications. For example, data mining procedures led to certain medical discoveries such as the connection between estrogen and Alzheimer's disease, and the relationship between migraine headaches and magnesium deficiency. However, data mining also has drawbacks. Data mining tools are not standardized and vary greatly in effectiveness. Also, the technology is largely untested in a library setting.