Evaluating Planning and Remote Science Operations for Ocean Exploration Using Exploration Ground Data Systems (xGDS)

David Lees1, Tamar Cohen2, Matthew C Deans2 and Darlene Sze Shien Lim2, (1)Carnegie Mellon University Silicon Valley, Moffett Park, CA, United States, (2)NASA Ames Research Center, Moffett Field, CA, United States
Abstract:
The Exploration Ground Data Systems (xGDS) from NASA Ames is a web-based science decision support software tool that links together information in time and space, including video, still images, scientific instrument data, and annotations in geographic and temporal context. xGDS has been deployed at multiple NASA analog missions over the past decade.

For the last two years we have participated in the Systematic Underwater Biogeochemical Science and Exploration Analog (SUBSEA) project, a multi-institution collaboration supported by NASA, NOAA’s Office of Exploration Research (OER), the Ocean Exploration Trust (OET) and the University of Rhode Island’s Graduate School of Oceanography (GSO). SUBSEA used the ship E/V Nautilus along with its two ROVs, Hercules and Argus, to remotely explore deep ocean volcanic vents as an analog for ocean worlds (e.g. Enceladus).

A remote science team used xGDS to plan ROV operations and deliver a daily dive plan to the ship for the 2019 SUBSEA cruise. During operations, video, ROV and instrument telemetry were streamed from the ship to the science team. The science team annotated the data with their observations as they watched the dive. Later, they reviewed dive data independently and collaboratively developed a dive plan for the next day, and delivered it to the ship.

Comparing remote operations before and after deployment of xGDS led to some key observations: (i) Reviewing data interactively in temporal and spatial context was critical for the science team’s ability to plan dive operations. (ii) Team members were actively engaged with the remote dive operations because they could use the collected data and visualize it as they desired. (iii) The remote science team could quickly identify critical points of interest in a massive volume of data in order to deliver plans on time, by reviewing past events in context. (iv) xGDS facilitates remote collaboration to support geographically distributed science teams and citizen scientists.