At JPL, Spacecraft Systems Engineers (SSEs) make daily predictions of the amount of data that the Mars Opportunity Rover can transmit to overpassing satellites under complex changing conditions. The predictions provide scientists with an estimate of how much data they can collect each day and influence decisions about what data to prioritize. 

To do this, SSEs interpret and analyse a daily stream of telemetry data on a tight schedule. Our challenge was to enable SSEs to see and interact with the data in a streamlined, efficient manner to meet these predictive planning challenges. 

To meet this challenge, our team worked with operators to create visualizations that compare predictions of telecommunications across channels, times, and locations. We implemented a user-friendly system for analyzing telemetry predictions, allowing engineers to efficiently determine the optimal rover path to relay data from Mars on any given day.


PUBLICATION: Towards Design Principles for Visual Analytics in Operations Contexts. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems. April 2018. ACM.


Images and text used with the permission of project participant Sara Stalla.