The Citizen Science component of the iMars project, Mars in Motion, was created through the Zooniverse's Panoptes framework to allow volunteers to look for and identify changes on the surface of Mars over time. 'Mars in Motion' has been developed to complement the results of automated data mining analysis software, both by validation through the creation of training data and by adding context - gathering more in-depth data on the type and metrics of change initially detected.
The following scores were calculated using a statistically-driven machine-learning approach, a type of AI that learns to perform a task by analysing patterns in data. This is an experimental approach to citizen-science impact assessment, and the exact reasoning behind the scores is not explainable. The scores represent a best guess of the impact the project is having in each domain. Scores are recalculated and updated when “View impact report” is clicked.