Every star has an atmosphere that reaches out into interplanetary space. This atmosphere is made of charged particles that continuously flow outwards, called the solar wind, and significantly impact Earth’s space weather. Understanding the structures that make up the solar wind, such as the magnetic field, velocity, temperature, and density parameters, is essential to understanding and predicting the behavior that impacts us here on Earth and for extraterrestrial missions. Experts who can identify solar-wind structures are limited, and there are years worth of data to catalog. The goal of this challenge is to use machine learning to create a catalog of solar wind structures.