Query-driven visualization of large data sets

We present a practical and general-purpose approach to large and complex visual data analysis where visualization processing, rendering and subsequent human interpretation is constrained to the subset of data deemed interesting by the user. In many scientific data analysis applications, "interesting" data can be defined by compound Boolean range queries of the form (temperature>1000) AND (70