We present a novel high-level visualization taxonomy. Our taxonomy classifies visualization algorithms rather than data. Algorithms are categorized based on the assumptions they make about
the data being visualized; we call this set of assumptions the design
model. Because our taxonomy is based on design models, it is
more flexible than existing taxonomies and considers the user’s
conceptual model, emphasizing the human aspect of visualization.
Design models are classified according to whether they are discrete or continuous and by how much the algorithm designer
chooses display attributes such as spatialization, timing, colour,
and transparency. This novel approach provides an alternative
view of the visualization field that helps explain how traditional
divisions (e.g., information and scientific visualization) relate and
overlap, and that may inspire research ideas in hybrid visualization
areas.