Seamless Searching of Numeric and Textual Resources - Summary                                                   project home page

A National Library Leadership Project supported by the Institute of Museum and Library Services.

A hope for new technology in libraries has been to support seamless searching across an increasing range of resources on a growing digital landscape. The reality is that network-accessible resources, like the contents of a well-stocked reference library, are quite heterogeneous, especially in the variety of indexing, classification, categorization, and other forms of "metadata."

The intent of this project is to demonstrate improved access to written material and numerical data on the same topic when searching two quite different kinds of database: text databases (books, articles, and their bibliographic records) and numerical data (socio-economic databases).

The problem is that there has, until now, been no easy path to integrate numeric databases with bibliographic and textual databases which might contain knowledge about cause and effect. The vocabulary which classifies the numeric data may be quite different from the subject headings used for books, magazine articles, and newspaper stories about the same topic of interest. Also there needs to be an environment of search support that facilitates such transverse searching, establishing connections, transferring data and invoking appropriate utilities in a helpful way.

This project addresses both problems through the development and demonstration of a library gateway providing search support for both text and socio-economic numeric databases. The gateway will help users conduct searches in each type of database by accepting a query in the library users' own terms and then suggesting the specialized categorization terms to search for in the information resource (database). The intent is that if you found something interesting in a socio-economic database, the gateway will help you to find documents on the same topic in a text database, and vice versa. Selection of the best search terms in the target databases is supported by the use of "Entry Vocabulary Modules," which resemble Melville Dewey's "Relative Index," but are created using statistical association techniques.