R. H. Lupton Princeton U. The rate at which we can acquire astronomical data outstrips our ability to manipulate and interpret it using standard techniques. The actual data themselves will be complex, comprising images and spectra, in addition to measured attributes. We describe here an implementation of a prototype object oriented distributed database capable of handling these volumes of data. Conceptually the difference lies in how we visualize the data. Simple hash tables limit efficient searches to those dimensions on which the data has been indexed.
Multidimensional indexing is achieved via a tree.
This is simply a balanced, multidimensional binary tree with each terminating node representing a cell within the dimensional volume of the data set. This provides a geometric storage method which optimizes searches of the database by capitalizing on the inherent relations within the data itself. From this coarse grained map of the data distribution we can predict query times and output volumes prior to applying a particular query to the full database. The volume of these data are such that they may be distributed on different media, different platforms or even across the country, at central archives. The complexity of this distribution is separated from the interface to the database by employing a client-server model.