In scientific communication, figures are typically rendered as static displays. This often prevents active exploration of the underlying data, for example, to gauge the influence of particular data points or of particular analytic choices. Yet modern data-visualization tools, from animated plots to interactive notebooks and reactive web applications, allow psychologists to share and present their findings in dynamic and transparent ways. In this tutorial, we present a number of recent developments to build interactivity and animations into scientific communication and publications using examples and illustrations in the R language (basic knowledge of R is assumed). In particular, we discuss when and how to build dynamic figures, with step-by-step reproducible code that can easily be extended to the reader’s own projects. We illustrate how interactivity and animations can facilitate insight and communication across a project life cycle—from initial exchanges and discussions in a team to peer review and final publication—and provide a number of recommendations to use dynamic visualizations effectively. We close with a reflection on how the scientific-publishing model is currently evolving and consider the challenges and opportunities this shift might bring for data visualization.