Approx 1 hr 43 min. This video presents the lecture portion of a half-day tutorial. Case studies and a bibliography are provided for your use.
Instructor Ian Lowrie describes the organizational and technological aspects of modern data pipelines, framing data science ethnographically as a knowledge practice and data scientists as a particular kind of expert. He also explores methodological approaches to studying data work in real-world contexts. Participants learned to:
- Think ethnographically about data work as a knowledge practice
- Develop methodological strategies for studying data work
- Chart the organizational and technological components of data infrastructure
- Interpret the mindset, jargon, and practical orientations of their data scientist and developer colleagues
- Understand how algorithmic systems and data analytics impact organizational structures, work practices, and business models
In the second half of the tutorial, participants worked collaboratively to develop a pitch for an ethnographic study of an organization and business problem. The case study prompts for this exercise are provided for your use.
Participants also received a reading assignment and bibliography, which are likewise provided for your use.
The tutorial is directed primarily toward practicing ethnographers without deep familiarity with data science and computing infrastructure.
Ian Lowrie is an anthropologist who studies how people build, maintain, and operate data infrastructure. From fieldwork with data analytics start-ups and web infrastructure firms in Moscow to research data managers and computational neuroscientists in the United States, his research explores the types of expertise emerging around big data pipelines and algorithmic information processing. He currently teaches in the Department of Anthropology and Sociology at Lewis and Clark College and works as the editor at Platypus, the blog of the Committee for the Anthropology of Science, Technology, and Computing.