Data visualization literacy: A feminist starting point

Abstract

We assert that visual-numeric literacy, indeed all data literacy, must take as its starting point that the human relations and impacts currently produced and reproduced through data are unequal. Likewise, white men remain overrepresented in data-related fields, even as other STEM (Science, Technology, Engineeering and Medicine) fields have managed to narrow their gender gap. To address these inequalities, we introduce teaching methods that are grounded in feminist theory, process, and design. Through three case studies, we examine what feminism may have to offer visualization literacy, with the goals of cultivating self-efficacy for women and underrepresented groups to work with data, and creating learning spaces where, as Philip et al. (2016) state, ‘groups influence, resist, and transform everyday and formal processes of power that impact their lives’.

Data practices during COVID: Everyday sensemaking in a high‐stakes information ecology

“…The present study responds to recent calls for gaining a deeper understanding of humanistic and relational data literacy, in order to design learning environments that prepare learners to negotiate an increasingly datafied world (D'Ignazio & Bhargava, 2020;Garcia et al, 2021;Lee et al, 2021;Wilkerson & Polman, 2020). One understudied way to gain such an understanding is to examine how people use publicly available data sources in non-professional, everyday contexts (Kennedy & Hill, 2018).…”

“…Following Radinsky (2020), we operationalize data as "representations of quantity, space and time-numbers, charts, graphs, maps-as they are mobilized for inquiry and argument" (p. 375). Our approach to data literacy, like others' (D'Ignazio & Bhargava, 2020;Lee et al, 2021;Wilkerson & Polman, 2020), is based on the conceptualization of literacy as social practice (Street, 1984), in which literacy is seen as a process of making use of sign systems to create meaning and act. To be literate involves familiarity with particular sign systems and the conventions of their use but also the ways in which people mobilize resources to achieve goals, and how they position themselves and are positioned in terms of access or inaccess to particular ways of using sign systems (Lewis et al, 2007).…”

“…From such perspectives, learning to reason with data involves learning to navigate interactions with data, with tools, and with other people. This learning process has aspects that are not only computational but also social, civic and political (D'Ignazio & Bhargava, 2020; Garcia et al, 2021; Philip et al, 2016). This work points to the need for research to examine the ways people interact with data in their everyday, non‐professional lives (Kennedy & Hill, 2018; Masson & van Es, 2020; Pink et al, 2017; Tissenbaum et al, 2021).…”

Interactive visualization literacy: The state-of-the-art

“…D’Ignazio and Bhargava 54 propose teaching methods focused on feminist theory, procedure, and design to address inequalities. Via three case studies, they explore what feminism can offer visualization literacy, with the intention of improving self-efficacy for women and less-represented groups.…”

Data-bodies and data activism: Presencing women in digital heritage research

“…What work do these data representations do and how might they work harder in that hyphenated space of data-bodies to invite multiple interpretations, ways of engaging and generative contradictions in the making of digital heritage? D’Ignazio (2015: para 8/22) calls for ways to locate data visualization ‘in concrete bodies and geographies’; a move consistent with a ‘feminist ethics and politics of data visualization’. I therefore explore methodological entry points which enable, as Lupton (2020: 122) encourages, ‘not only what humans can do with their data and how they can learn from their data, but how data make them feel, move and respond as part of the more-than-human worlds of which data selves are part’.…”