At the core of scientific visualization is the representation of data graphically - through images, animations, and videos - to improve understanding and develop insight. Data visualizers develop data-driven images, maps, and visualizations from information collected by Earth-observing satellites, airborne missions, and ground measurements. Visualizations allow us to explore data, phenomena and behavior; they are particularly effective for showing large scales of time and space, and "invisible" processes (e.g. flows of energy and matter) as integral parts of the models.

This video provides tips for teachers on helping students make sense of data to help them understand and work with data. It is based on the work of Kristin Hunter-Thomson of Dataspire.org and uses data from the My NASA Data Earth System Data Explorer.

Follow along as NASA visualizer Kel Elkins walks you through three visualizations (Dust Crossing, Typhoon Hagupit, and Aquarius Sea Surface Salinity) and answers questions about his work, education, and career.

NASA visualizers take data – numbers, codes – and turn them into animations people can see and quickly understand.

Students review a visualization showing a global view of the top-of-atmosphere longwave radiation from January 26 and 27, 2012. They review the supporting text and analyze the data in the visualization to answer questions.

Students watch a visualization video and answer questions on the potential of increasing megadroughts in the southwest and central United States from 1950-2095 using models created by soil moisture data.

In this lesson, Observing Earth’s Seasonal Changes, students observe patterns of average snow and ice amounts as they change from one month to another, as well as connect the concepts of the tilt and orbit of the Earth (causing the changing of seasons) with monthly snow/ice data from January 2008

Students review a video showing how the ocean is warmed by solar energy. This is the first video of a four-part series on the water cycle, which follows the journey of water from the ocean to the atmosphere, to the land, and back again to the ocean.

A model analyst develops models to help visualize, observe, and predict complicated data. Model analysis is the process of taking large amounts of data and separate it into a structure that makes it intelligible to the binary process of computers. An analyst also manages the flow of information between different user groups through the use of relational databases.

This NASA visualization shows sea surface salinity observations (September 2011-September 2014). Students review the video and answer questions.