Data visualizations can dazzle, inform, and persuade. It is precisely this power that makes it worth asking: "Visualization by whom? For whom? In whose interest? Informed by whose values?" These are some of the questions that emerge from what we call data feminism, a way of thinking about data and its visualization that is informed by the past several decades of intersectional feminist activism and thinking.
Using visualization as a starting point, this paper works backwards through the data-processing pipeline in order to show how a feminist approach to thinking about data not only exposes how power and privilege presently operate in data science, but also suggests how different design principles can help to expose inequality, mitigate bias, and work towards justice. In the process, we discuss the talented journalists, artists, data scientists and communities that are at the forefront of data-driven justice.