Accentuating visualization parameters to guide exploration

Abstract

We present a new method for displaying visualization parameters to guide casual data exploration. When visualizing datasets with large parameter spaces it can be difficult to move between data views. Building on social navigation and degree-of-interest visualization, we propose the concept of accentuation as the selection and emphasis of visualization parameters based on social and semantic signals. We describe how we designed an accentuated visualization interface, and discuss open challenges and directions for future research.