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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. [ABSTRACT FROM AUTHOR]