Time-varying data is huge and contains specific features of interest to an application expert. Standard techniques for visualizing time-varying data such as snapshots and animations are limited in their ability to convey change and draw the user's attention to regions of; interest. Art-inspired techniques are presented to provide temporal context to the domain expert. I present novel visualization techniques that convey change over time in a single image. Illustrators convey change over time using illustrative cues. Time-varying data, in which three-dimensional features are moving over time, can be effectively visualized using illustrative techniques such as speedlines, flow ribbons, strobe silhouettes and opacity based; techniques. I applied these techniques to computational fluid dynamics data and; evaluated the effectiveness of our techniques with the help of a formal user study. The illustration-inspired techniques were also applied to the field of atmospheric physics, where I generated novel hurricane visualizations that allowed collaborators to obtain insight into; the evolution and intensification of a hurricane.; For effectively visualizing time-varying data, such as infant mortality over eight years or global rainfall over an entire century, we developed a novel pointillism-based technique. This technique was inspired by paintings by Seurat, applied the visual color blending theory to place brush strokes close to each other. We applied techniques from pointillistic; paintings to convey variability in time-varying data and to convey trends over time in a single image. The formal user evaluation conducted to evaluate these techniques gave us insight into the strengths of our techniques and led us to the result that users though correct were less confident of their answers as compared to snapshots-based and animation-based techniques
