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Information visualization faces challenges presented by the need to represent abstract data and the relationships within the data. Previously, we presented a system for visualizing similarities between a single DNA sequence and a large database of other DNA sequences (E.H. Chi et al., 1995). Similarity algorithms generate similarity information in textual reports that can be hundreds or thousands of pages long. Our original system visualized the most important variables from these reports. However, the biologists we work with found this system so useful they requested visual representations of other variables. We present an enhanced system for interactive exploration of this multivariate data. We identify a larger set of useful variables in the information space. The new system involves more variables, so it focuses on exploring subsets of the data. We present an interactive system allowing mapping of different variables to different axes, incorporating animation using a time axis, and providing tools for viewing subsets of the data. Detail-on-demand is preserved by hyperlinks to the analysis reports. We present three case studies illustrating the use of these techniques. The combined technique of applying a time axis with a 3D scatter plot and query filters to visualization of biological sequence similarity data is both powerful and novel.