Data transformations and representations for computation and visualization

This article is a product of a workshop on the Future of Visual Analytics, held in Washington, DC on 4 March 2009. Workshop attendees included representatives from the visual analytics research community across government, industry and academia. The goal of the workshop, and the resulting article, was to reflect on the first 5 years of the visual analytics enterprise and propose research challenges for the next 5 years. The article incorporates input from workshop attendees as well as from its authors. Abstract At the core of successful visual analytics systems are computational techniques that transform data into concise, human comprehensible visual representations. The general process often requires multiple transformation steps before a final visual representation is generated. This article characterizes the complex raw data to be analyzed and then describes two different sets of transformations and representations. The first set transforms the raw data into more concise representations that improve the performance of sophisticated computational methods. The second transforms internal representations into visual representations that provide the most benefit to an interactive user. The end result is a computing system that enhances an end user's analytic process with effective visual representations and interactive techniques. While progress has been made on improving data transformations and representations, there is substantial room for improvement.