Subsampling is a method that reduces data size by selecting a subset of the original data. The subset is specified by choosing a parameter n, specifying that every nth data point is to be extracted. For example, in structured datasets such as image data and structured grids, selecting every nth point produces the results shown in Fig. Subsampling modifies the topology of a dataset. When points or cells are not selected, this leaves a topological “hole.” Dataset topology must be modified to fill the hole. In structured data, this is simply a uniform selection across the structured i-j-k coordinates. In structured data, the hole must be filled in by using triangulation or other complex tessellation schemes. Subsampling is not typically performed on unstructured data because of its inherent complexity.