Authors of “Exploring Data Detective Practices as a Class Activity” discuss their experiences as students and instructors in their data feminism course where they take on the role of ‘Data Detectives.’ In the course students learn data visualization and analysis tools as well as creating an “active practice through which we document our investigations of both qualitative and quantitative data under various themes” which becomes their detective work.
Our concept of Data Detective is modeled on detective work in a more general sense, where a person uses coherent, time-based, record-keeping of their activities to gain a better understanding of that which they initially do not know but want to understand. Thus, to act as a Data Detective is to discover and conduct purposeful, documented, and reflective actions needed to gain access to the desired data.
The article showcases students’ visualizations of their research journeys that detail the frustrations of trying to fill in data gaps by uncovering and sourcing data that was often “missing, partial, or deliberately obscured.”
The authors provide examples of projects and images of the final detective journeys that might lend themselves to data or information literacy instruction. Or, if you are looking for more data literacy themed ideas Nightingale frequently publishes similar articles under their Data Literacy category.
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This post was produced through a cooperation between Claire Burns and Kelly Karst (Editors-at-Large), Ruth Carpenter and Rachel Starry (Editors for the week), Claudia Berger, Caitlin Christian-Lamb, Nickoal Eichmann-Kalwara, Linsey Ford, Pamella Lach, Molly McGuire, Hillary Richardson, and Christine Salek (dh+lib Review Editors), and Tom Lee (Technical Editor).