All methods generate data. How we make it and what we do with it matters.
Big Data strives for automated methods instrumented by algorithmic, logical analytics where computation and machine learning create the analytical output.
Ethnography has typically looked at case studies of demarcated issues where the human is irreducible, creating a deep understanding of particular local circumstances. Here, the human is the analytical research instrument.
Still, humans make algorithms. Humans embed values, norms and ideals into computational constructions. The analytical inquiry and process makes work that has political effects. Methodological choices include and exclude. Together these methods lend themselves to specific world-makings.
In ETHOS Lab, we approach methods and the multiplicity of data in an experimental way, which we call Situated Analytics. Situated Analytics is inductive. It cuts across the boundaries (and promises) of digital/computational methods and ethnographic participation in an attempt to raise modes of doing and representing the social. This mode of inquiry takes seriously the ways data legitimises, travels, shifts, lives and implodes relations. This approach requires double vision: exploring data-centric practices at the scale of the human and experimenting with analytical moves at the scale of data.