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.

Joshua Stevens,Lead for Data Visualization for NASA Earth Observatory at NASA Goddard Space Flight Center. Learn how he translates data from NASA missions and instruments into intuitive maps, charts and graphics which meet high quality standards and are consistent with current research.

This mini lesson helps students visualize how the Hydrosphere and Cryosphere interact to produce changes in land and sea ice. 

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

Geospatial Information Scientists and Technologists research geospatial data or develop geospatial technologies. Geospatial data is data that has a geographic component associated with it, such as coordinates or an address, and geospatial technologies are the technologies used to collect and analyze geospatial data. 

Students explore the spatial patterns observed in meteorological data and learn how this information is used to predict weather and understand climate behavior.

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.

Ricky is a Software Engineer who works for the NASA Clouds and the Earth's Radiant Energy System (CERES) Project with the group that specializes in clouds.  He develops software to ensure that the satellite data collected about clouds are accurate and accessible.