Unmet NeedModern information technologies have made big data available in a variety of sciences, i.e. extremely large data sets that may be analyzed only computationally to reveal patterns, trends, and associations. There are a number of approaches to compile these data sets, but in all current approaches there are challenges in how to make sense of these data.
Technology DetailsJHU researchers have created a computational solution to accelerate searches related to astronomy and other sciences, navigating the significant amounts of data associated with these sciences. The solution comprises of two fundamental modules that (1) provide a mathematical description of generalized spherical polygons and implements a relational algebra over this set and (2) implements a hierarchical partitioning of the sphere based upon various algorithms. The computational software includes a hierarchy of routines that can be used as a library to build new applications as well as a suite of database functions to accelerate SQL searches.
Stage of DevelopmentIn use
