Visualizing Junk: Big Data Visualizations and the need for Feminist Data Studies

The datafication of culture has led to an increase in the circulation of data visualizations. In their production, visualizers draw on historical antecedents which define what constitutes a good visualization. In their reception, audiences similarly draw on experiences with visualizations and other visual forms to categorize them as good or bad. Whilst there are often sound reasons for such assessments, the gendered dimensions of judgements of cultural artefacts like data visualizations cannot be ignored. In this paper, we highlight how definitions of visualizations as bad are sometimes gendered. In turn, this gendered derision is often entangled with legitimate criticisms of poor visualization execution, making it hard to see and so normalised. This, we argue, is a form of what Gill (2011) calls flexible sexism, and it is why there is a need not just for feminist critiques of big data, but for feminist data studies – that is, feminists doing big data and data visualization