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4D datasets, such as time-varying datasets, usually come on 4D Cartesian Cubic (CC) grids. In this paper, we explore the use of 4D Body Centered Cubic (BCC) grids to provide a more efficient sampling lattice. We use this lattice in conjunction with a pointbased renderer that further reduces the data into an RLE-encoded list of relevant points. We achieve compression ranging from 50 to 80% in our experiments. Our 4D visualization approach follows the hyperslice paradigm: the user first specifiesdoi:10.1109/swg.2002.1226515 dblp:conf/volvis/NeophytouM02 fatcat:37z4ek7ovrbjdaiue5o4ghr5ni