Baseless data? Modelling, ethnography and the challenge of the anthropocene

Research output: Chapter in Book/Conference proceedingChapterpeer-review

Abstract

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.
Original languageEnglish
Title of host publicationEthnography for a data-saturated world
EditorsHannah Knox, Dawn Nafus
Place of PublicationManchester
PublisherManchester University Press
Chapter6
Pages128–150
Number of pages23
ISBN (Electronic)9781526127600
ISBN (Print)9781526127594, 9781526134974
DOIs
Publication statusPublished - 3 Oct 2018

Publication series

NameMaterialising the Digital
PublisherManchester University Press

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