Interactive archives of scientific data

Abstract

Data generators in many disciplines are rapidly improving, typically much faster than the techniques available to manage and use the data they produce. Appropriate data management techniques coupled with the process or methods of scientific visualization, or at least the technologies that support them, show promise in helping to address some of these problems. Consider browsing, for example. It serves a role in feature identification by the scientist/user, and thus, serves as a guide in the data selection process. To date, most efforts associated with data browsing have focused on simple images with image data. Unfortunately, these techniques are not applicable to many classes of data or when more than one data set is to be considered. It should be noted that browsing is more of a subjective process involving the human visual system and that this is one of the origins of the notion of scientific visualization as a method of computing. The utilization of visualization strategies for qualitative presentation of data thus becomes a viable approach. For browsing to be effective, it must be interactive with near-relatime system response. With data sets of interesting size, e.g., ≥O(1 GB, where 1 GB = 1 GByte = 230 bytes), immediate interaction cannot take place on current conventional systems (i.e., high-end graphics workstations). Even though a 1 GB data set is admittedly modest by today's standards, the access and visualization of the entire data set or even a large fraction of it may place significant burdens on the floating point and bandwidth capacities of the computer system being employed. Browsing capabilities can also be extended to environments without high-bandwidth access to an interactive system by distributing compressed visualizations instead of data for predefined access and browsing scenarios. © 1994.