Interpolating analytic visualizations
Marjan Trutschl, Georges Grinstein, Urška Cvek · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
Several authors have developed automated parameterized visualization generation systems14,15,16. All generate classic visualizations or combinations of such visualizations. A vector space model of visualization was proposed by Hoffman18, leading to the development of new visualizations and the concept of interpolating visualizations. These new visualizations provide alternative representations and insights into data and have been applied successfully in numerous data analysis problems including gene expression, drug discovery, clinical trials, toxicogenomics, and medical informatics23. In this paper we elevate this vector space model to include analytic visualizations, ones with tightly coupled analysis, such as Self-Organizing Maps (SOMs) and Multi-Dimensional Scaling (MDS). We describe our new model and provide an example interpolation of a SOM and a scatterplot with a simple data set (the Fisher Iris data) and a more complex and larger one (microarray gene expression data).