ABSTRACT
This chapter focuses on an approach to high performance visualization and analysis, termed query-driven visualization and analysis (QDV). QDV aims to reduce the amount of data that needs to be processed by the visualization, analysis, and rendering pipelines. The goal of the data reduction process is to separate out data that is “scientifically interesting” and to focus visualization, analysis, and rendering on that interesting subset. The premise is that for any given visualization or analysis task, the data subset of interest
This smaller data subsets of interest and focusing of the visualization processing on these subsets-is complementary to the approach of increasing the capacity of the visualization, analysis, and rendering pipelines through parallelism, which is the subject of many other chapters in this book. This chapter discusses the fundamental concepts in QDV, their relationship to different stages in the visualization and analysis pipelines, and presents QDV’s application to problems in diverse areas, ranging from forensic cybersecurity to high energy physics.
