The real-world implications and applications of data are highly visible, from conversations about data privacy to issues of bias in automated systems. Organizations like the Algorithmic Justice League and Data for Black Lives are working to reimagine data-driven systems that promote equity, inclusion, and justice. But such initiatives require all voices to be part of the conversation–not just people who self-identify as specializing in data.
Academic disciplines tend to think about data in specific disciplinary contexts. Some classes focus explicitly on data systems and structures–others use data in less visible ways. We’re intentionally creating spaces where students who don’t see themselves as “a data person” are empowered to learn more about how projects and work that engage data can be driven by qualitative research questions. Part of that involves breaking down access barriers and misconceptions about data.