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Early detection and rapid response to infectious-disease outbreaks rely on effective decision making based on information from disparate sources. To improve decision-making in outbreak detection and response, it's important to understand how public health practitioners seek relevant information. Epinome, a user-centric visual-analytics system, supports research on decision-making in public health, particularly evaluation of information search strategies. Epinome facilitates investigation of scripted high-fidelity large-scale simulated disease outbreaks. Its dynamic environment seamlessly evolves and adapts as the user's tasks and focus change. This video shows how the Epinome system facilitates interactive simulations of disease outbreaks.

Methods for visualization of biological data continue to improve, but there is still a fundamental challenge in colorization of these visualizations (vis). Visual representation of biological data should not overwhelm, obscure, or bias the findings, but rather make them more understandable. This is often due to the challenge of how to use color effectively in creating visualizations. The recent global adoption of data vis has helped address this challenge in some fields, but it remains open in the biological domain. The visualization of biological data deals with the application of computer graphics, scientific visualization, and information visualization in various areas of the life sciences. This paper describes 10 simple rules to colorize biological data visualization.

How should scientists approach the innovations in visualization-rendering systems increasingly derived from computer game tools, interfaces, navigation techniques, and plot lines?

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