Data multiplexing Through Animated Texture Orientation and Color
Maria-Jesus Lobo, Christophe Hurter
Multidimensional data visualization is still a challenge for complex data exploration. Usually, each data dimension might be mapped to one available visual variable such as position, shape or color. While spatial and color data mappings have been previously intensively explored, animated encodings have been far less investigated. However, such techniques are widely used in existing visualizations. In this paper, we propose to assess the visual assets of direction and orientation of directed animated textures to encode data. We present a user study that compares three animated textures and a static representation. The results suggest that the animated techniques can be as effective as the static representation in terms of accuracy and data retrieval time.