Remotely Operated Vehicles (ROVs) Provide a "Big Data Progression"

This year, science and technology teams at the NASA Langley Science Directorate were challenged with creating an API-based web application using RockBlock Mobile sensors mounted on a zero pressure high-altitude balloon. The system tracks and collects meteorological data parameters and visualizes this data in near real time, using a MEAN development stack to create an HTML5 based tool that can send commands to the vehicle, parse incoming data, and perform other functions to store and serve data to other devices. NASA developers and science educators working on this project saw an opportunity to use this emerging technology to address a gap identified in science education between middle and high school curricula. As students learn about data analysis in elementary and middle school, they are taught to collect data from in situ sources. In high school, students are then asked to work with remotely sensed data, without always having the experience or understanding of how that data is collected. We believe that using ROVs to create a "big data progression" for students will not only enhance their ability to understand how remote satellite data is collected, but will also provide the outlet for younger students to expand their interest in science and data prior to entering high school. In this presentation, we will share and discuss our experiences with ROVs, APIs and data viz applications, with a focus on the next steps for developing this emerging capability.