Tailorable Sampling for Progressive Visual Analytics

Abstract

Fig. 1: Enabling tailorable PVA-sampling using a pipeline that structures the sampling process into three steps: linearization, subdivision, and selection. The steps are depicted here along the data they operate on: The linearization takes in the input data structure and transforms it into linear structure, which is then subdivided into bins in the subdivision step. The last step then produces the chunks forwarded into the PVA process by progressively selecting appropriate items from each bin. Different linearization, subdivision, and selection strategies can be combined to progressively sample a given dataset in various ways.