  Machine learning (ML) methods can expand our ability to construct, and draw
insight from large datasets. Despite the increasing volume of planetary
observations, our field has seen few applications of ML in comparison to other
sciences. To support these methods, we propose ten recommendations for
bolstering a data-rich future in planetary science.

Instrumentation and Methods for Astrophysics;Earth and Planetary Astrophysics;Machine Learning