Software Infrastructure for exploratory visualization and data analysis: Past, present, and future

Abstract

Future advances in science depend on our ability to comprehend the vast amounts of data being produced and acquired, and scientific visualization is a key enabling technology in this endeavor. We posit that visualization should be better integrated with the data exploration process instead of being done after the fact - when all the science is done - simply to generate presentations of the findings. An important barrier to a wider adoption of visualization is complexity: the design of effective visualizations is a complex, multistage process that requires deep understanding of existing techniques, and how they relate to human cognition. We envision visualization software tools evolving into "scientific discovery" environments that support the creative tasks in the discovery pipeline, from data acquisition and simulation to hypothesis testing and evaluation, and that enable the publication of results that can be reproduced and verified. © 2008 IOP Publishing Ltd.