Data Representations and Transformations

To permit visualization, analysis, and reporting, data must be transformed from their original raw state into a form, or representation, that is suitable for manipulation. These data representations and transformations are the foundation on which visual analytics is built. Data representations are structured forms suitable for computer-based transformations. These structures must exist in the original data or be derivable from the data themselves. They must retain the information and knowledge content and the related context within the original data to the greatest degree possible. The structures of underlying data representations are generally neither accessible nor intuitive to the user of the visual analytics tool. They are frequently more complex in nature than the original data and are not necessarily smaller in size than the original data. The structures of the data representations may contain hundreds or thousands of dimensions and be unintelligible to a person, but they must be transformable into lower-dimensional representations for visualization and analysis. Data representations may illuminate key features in the data, rather than showing every detail, so they are important to the process of data abstraction. The degree to which a visual analytics software tool can address the challenges of scale is also influenced by the data representation selected by the tool developer. Data representations underlie the interactive visualizations described in Chapter 3. The creation of appropriate data representations is essential to producing meaningful visual representations. The data representation method must facilitate the analytical reasoning methods and capture the intermediate and final results of the reasoning “With me everything turns into mathematics.”