This session will introduce the Virginia model of data science, also known as the 4+1 model, a broad framework designed to shape conversions about teaching and doing research in the field. We will review the history of predecessor definitions and models, such as Conway's Venn diagram and CRISP DM, as well as Donoho's more controversial model of "greater data science." We will then demonstrate the derivation of an invariant structure from a persistent theme in these models--the concept of a data science pipeline as a way of organizing thinking around the field. Among the topics covered will be the ongoing tensions in the field, exhibited by differences between earlier models, the subfield of data design, and the influence of the model on how data science is taught at UVA. Of particular interest to us is design, which relates to both visualization and data as a form of representation. We hope to engage a lively discussion.