This video addresses the following question: "As you look at a data set(s) that has been collected, could you help us understand how you use data visualizations to shape new questions to explore further in the data set(s)?"

This video addresses the following question: "As you think about how you use data visualization(s) to communicate your findings with others, can you describe how you refine the visualization(s) that you present to better support the story that you are sharing with the data visualization?"

This video addresses the following question: "We know that the science you do is driven by the big questions around Earth System Science. Could you please describe how you shape the questions that you ask before, during, and after you have collected data, how do you initially look at these data to help explore your initial set of questions?"

My NASA Data has recently released several new resources, StoryMaps, for use in educational settings.

My NASA Data StoryMaps provide an engaging and interactive way to explore Earth science topics using real NASA data. By integrating storytelling with interactive technology, these resources make complex scientific concepts more accessible and relevant to students.

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

Students will explore the relationship between Nitrogen Dioxide and Precipitation in Earth's atmosphere. They will explore the data provided, make a claim, and complete a slide guided by a rubric.

The purpose of this activity is to have students use an Earth Systems perspective to identify the various causes associated with changes to Earth's forests as they review Landsat imagery of site locations from around the world.

The Earth System Satellite Images, along with the Data Literacy Cubes, helps the learner identify patterns in a specific image.  

The Earth System Satellite Images, along with the Data Literacy Cubes, help the learner visualize how different Earth system variables change over time, establish cause and effect relationships, identify patterns, and determine relationships among variables.