Feminist Data Visualization

Catherine D’Ignazio and Lauren F. Klein’s paper is an important precursor to data feminism. It questions a visualization field that often treats clarity, neutrality, and objectivity as default values while rarely asking whom those visual norms serve, whom they hide, and which uncertainties and affects they exclude.

The paper’s contribution is to turn feminist epistemology into a design problem. Data graphics are not just containers for information; they are arrangements of power. What data are selected, how categories are made, how missingness is shown, whether bodily experience is acknowledged, and whether multiple interpretations are allowed all shape how publics understand the world.

For FemRes, this text pairs well with Haraway’s situated knowledges, Gender Shades, and algorithmic bias resources. It makes digital feminism not only a matter of online activism or platform violence, but also a question of data production, visual expression, and knowledge design.