Reducing the data size of spatial databases using sign vectors

In this paper, we describe a method for effectively expressing spatial geometric data in spatial database systems. The hyperplane is used to split a space into convex polytopes, each having a position vector. These position vectors are used to evaluate the spatial operations: the intersection, the union and the difference between two complexes of convex polytopes in any dimension. First, we explain the idea to represent a spatial object as a set of polytopes induced by hyperplanes, which must be stored in databases. We then present the conversion algorithms between position vectors and sign vectors of the complex model in any dimension. Next, we propose algorithms for compressing and uncompressing the sign vector to be stored in the database data. These algorithms are invoked when evaluating spatial operations. The above algorithms are implemented on an object database system. We also present the results of experimental tests to evaluate the data size of the spatial database.