Making microbial data: More-than-representational methods for encountering viruses, bacteria, and other microbes

Greenhough B., Lorimer J., Evans J., Davies OH.

Engaging with microbial worlds challenges the ocular and audio centrism of conventional social science methods. It is not possible to see or hear individual microbes in the same ways in which we would sense other humans or nonhumans; rather, we see and sense their effects as patches of mold or distinctive odors. Our bodies might register microbial presence/absence as, for example, the symptoms of infection, a novel taste profile, or a digestive disorder. In this chapter, we reflect on three recent projects which sought to experiment with new ways of making microbes sensible. The first of these-participatory metagenomics-drew on the tools of next-generation sequencing as a means through which households could become attuned to-and experiment with-their domestic microbiome. The second used body-mapping with family groups to explore their collective knowledge of microbial presences and absences in human bodies. The third examined how practices of fermentation can sensitize us to the ways in which humans and microbes shape each other through cooking and eating. In each case, we draw attention to how these methods offer unique insights into what might be retained, and what might be lost, as we attempt to translate what we might know/sense about microbial worlds through practices of sequencing, mapping, and experimentation, into shared images, diagrams, maps, and understandings. Three key themes emerge from our analysis where our approach resonates with (but at times also finds itself in tension with) a non-representational methodological disposition: a foregrounding of sensual knowledges, an emphasis on experimentation and play, and a commitment to leaving the future open. At the same time, other sensibilities-in particular a commitment to co-productive, participatory research-also emerge as significant, with the potential for further expanding the scope of non-representational approaches.

DOI

10.4324/9781003511168-5

Type

Chapter

Publication Date

2025-09-05T00:00:00+00:00

Pages

68 - 89

Total pages

21

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