Table lens as a tool for making sense of data

The Table Lens is a visualization for searching for patterns and outliers in multivariate datasets. It supports a lightweight form of exploratory data analysis (EDA) by integrating a familiar organization, the table, with graphical representations and a small set of direct manipulation operators. We examine the EDA process as a special case of a generic process, which we call sensemaking. Using a GOMS methodology, we characterize a few central EDA tasks and compare performance of the Table Lens and one of the best of the more traditional graphical tools for EDA i.e. Splus. This analysis reveals that Table Lens is more or less on par with the power of Splus, while requiring the use of fewer specialized graphical representations. It essentially combines the graphical power of Splus with the direct manipulation and generic properties of spreadsheets and relational database front ends. We also propose a number of design refinements that are suggested by our task characterizations and analyses.