With the recent application of coronagraph instruments to the field of exoplanet science, the range of detectable exoplanets has expanded drastically. However, the analysis techniques needed to take full advantage of this new technology have not yet been perfected. We have recently concluded a public data challenge that served to advance the state of these analysis techniques, as well as to familiarize the community with the capabilities of the Roman Space Telescope’s Coronagraph Instrument. In this challenge, participants were asked to identify and describe directly imaged exoplanets in simulated data. Each team submitted astrometry and photometry measurements for each planet in the fictional planetary system, as well as estimates of the planets’ orbital parameters (semi-major axis, period, etc.), mass, radius, and albedo. In this talk, we share the design of the data challenge, evaluate the performance of each participating team based on root-mean-square error metrics, and compare the teams’ results to our in-house analysis. This data challenge provided an opportunity to train and educate several early career scientists on how to interact with space coronagraph data, and the results show that three of the seven teams demonstrated excellent recovery of key astrophysical observables of exoplanets.