Use of imaging data has become more profound with the advent of digital cameras, the internet, and automation. With advances of computer vision, actionable information can now be extracted from images to advance the study of plants and their phenotype. In this chapter we document the experience of advancing the state of the art in developing methods that extract such information motivated and orchestrated via data challenges. We identify several examples and conclude that this can be a fruitful bridge between the communities offering problems and data with those that can offer the solutions. We offer suggestions on how to get started and conclude by providing advice for shaping data challenges of the future.