Data Ethnography: Cultivating Reflexive Sensibilities through the Cultural Analysis of Data

An ability to situate data in social and cultural context is critical to a responsible data practice. However, curriculum for introducing statistics and data science students to such skills is often underdeveloped in undergraduate programs. This article motivates and describes a course for introducing statistics and data science students to the principles and methods of data ethnography, demonstrating how qualitative data collection and cultural analysis can be brought to bear on the study of data settings and artifacts. I outline how students in the course are taught to culturally analyze data across different social scales, starting with the design of data organizing infrastructures, moving through the scales of individual data labor and collective data practices, and concluding with the scales of data policy, politics, and discourse. At each scale, I provide examples of how students are taught to apply an ethnographic methodology towards analyzing a data setting or artifact, and I provide examples of student work to demonstrate learning outcomes. Assessing student perceptions of their learning, I argue that practicing ethnography develops skill in recognizing and interpreting the cultural meaning behind taken-for-granted data infrastructures and actions, as well as skill in analyzing the social dimensions and impacts of data work.