The Rico dataset, containing design data from more than9.7k Android apps spanning 27categories, was released in 2017. It exposes visual, textual, structural, and interactive design properties of more than72k unique UI screens. Over the years since its release, the original paper has been cited nearly 100 times according to Google Scholar and the dataset has been used as the basis for numerous research projects. In this chapter, we describe the creation of Rico using a system that combined crowdsourcing and automation to scalably mine design and interaction data from Android apps at runtime. We then describe two projects that we conducted using the dataset: the training of an autoencoder to identify similarity between UI designs, and an exploration of the use of Google’s Material Design within the dataset using machine learned models. We conclude with an overview of other work that has used Rico to understand our mobile UI world and build data-driven models that assist users, designers, and developers.