In recent years, chemical instrumentation has become much more sophisticated. Most analytical equipment now incorporates a microprocessor or is interfaced to a microcomputer. As a result, chemists can collect an immense amount of data on a single sample in a short period of time. While there may be an advantage to gathering such a great deal of information, problems can arise from too much information. Today, analysts commonly are faced with the dual problems of storing and analyzing the resulting flood of information. The goal of this research has been to address the problems of data storage and data analysis. Specifically, data compression techniques and spectral search and match algorithms have been developed. The data compression techniques developed utilize the Hadamard Transform and the modified zero-crossing clipping algorithm. The spectral search technique utilizes the unique format of the compressed and clipped data to greatly accelerate spectrum identification. To demonstrate the feasibility of this technique, three-dimensional fluorescence spectra of polynuclear aromatic compounds have been used. The results indicate data compression techniques and the application of these techniques to a library search system for three-dimensional fluorescence spectroscopy were both successful. / Ph. D.