Data navigation, etc. The fundamental mathematical structure of many data spaces is generally multidimensional, and the goal is to fathom the structures through 3D views of that space.
Many scientific disciplines produce and use large, multidimensional databases.
Collected nearly every year for about 20 years, the GSS contains hundreds of individual questions each administered to hundreds of individuals regarding preferences and demographic statistics. Another example is the US Census, issued as hundreds of statistics on each census tract. Large scale computations such as the multidisciplinary design optimization of an aircraft or weather forecasting produce far too much data to exhaustively visualize. Indeed, thousands of dimensions are the norm, and powerful methods like Latent Semantic Indexing only reduce the number to hundreds of dimensions. Here the added challenge is that many dimensions are interconnected or related in complex ways, through links, synchronization, and content-based associations.