IEEE Computer Graphics and Applications
Provenance and Annotation for Visual Exploration Systems
IEEE Transactions on Visualization and Computer Graphics
Casual Information Visualization: Depictions of Data in Everyday Life
IEEE Transactions on Visualization and Computer Graphics
Overview Use in Multiple Visual Information Resolution Interfaces
IEEE Transactions on Visualization and Computer Graphics
Illustrative Deformation for Data Exploration
IEEE Transactions on Visualization and Computer Graphics
Bringing semantics to visualization services
Advances in Engineering Software
REV '07 Proceedings of the Second International Workshop on Requirements Engineering Visualization
Data, information, and knowledge in visualization
IEEE Computer Graphics and Applications - Special issue title on generating 3D building models a VR playground for teaching math
Measuring effective data visualization
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
Human-centered visualization environments
Human-centered visualization environments
Conceptualizing Visual Uncertainty in Parallel Coordinates
Computer Graphics Forum
Visual comparison for information visualization
Information Visualization - Special issue on State of the Field and New Research Directions
Internet of Things (IoT): A vision, architectural elements, and future directions
Future Generation Computer Systems
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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 userýs 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.