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Modelling, ethnography and the challenge of the anthropocene
Hannah Knox

This chapter looks at how practices of scientific analysis are being put under strain by the appearance and necessity of working with new kinds of data. Whilst most commentary about new forms of data have focused on the value and ethics of analysing and using transactional consumer data, this chapter is concerned with the analytical challenge of another field of ‘big’ data – that of environmental modelling.

The chapter provides an ethnographic account of the challenges faced by a particular group of climate modellers based at a UK university as they attempt to work with emerging forms of data that promise to bridge a divide between natural processes (sensory data on weather and climate) and social relations (statistical data on poverty, tourism, economy). A central concern of these climate modellers (and shared with analysts of ‘big’ data) is the problem of how to conduct analysis without a controllable baseline for comparison. The chapter compares statistical analysis that informs climate modelling with the epistemology of ethnography, a method which has long operated with an alternative analytical foundation that does not start with the necessity of a generalisable baseline. Reflexively engaging the analytical commitments of the ethnographic method, the chapter considers whether an alternative approach to numerical data might be developed out of ethnographic analysis and what kind of knowledge this approach to data would produce.

in Ethnography for a data-saturated world
Editors: and

Data is not just the stuff of social scientific method; it is the stuff of everyday life. The presence of digital data in an ever widening range of human relationships profoundly unsettles notions of expertise for both ethnographers and data scientists alike. This collection situates digital data in broader knowledge-production practices. It asks about the kinds of social worlds that data scientists are creating as the profession coalesces, and looks at the contemporary possibilities available to both ethnographers and their participants for knowing, formatting and intervening in the world. It shows what digital data is doing to the empirical methods that sustain claims to expertise, with a particular focus on implications for ethnography.

The contributors offer empirically grounded accounts of the cultures, infrastructures and epistemologies of data production, analysis and use. They examine the professionalisation of data science in a variety of national and transnational contexts. They look closely at specific data practices like archiving of environmental data, or claims-making about how software is produced. They also offer a glimpse into the new methodological and pedagogical possibilities for teaching and doing ethnography in a data-saturated world.

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Ethnography for a data-saturated world
Hannah Knox
Dawn Nafus

The introduction to this collection sets out the key debates to which the chapters speak. It situates both digital data analysis and ethnography as methods which have their own ‘social lives’ and uses this approach to explore the work that methods do within particular projects of description and transformation.

in Ethnography for a data-saturated world