Co-observing the weather, co-predicting the climate: Human factors in building infrastructures for crowdsourced data

Abstract

This paper investigates the embodied performance of 'doing citizen science'. It examines how 'citizen scientists' produce scientifi c data using the resources available to them, and how their socio-Technical practices and emotions impact the construction of a crowdsourced data infrastructure. We found that conducting citizen science is highly emotional and experiential, but these individual experiences and feelings tend to get lost or become invisible when user-contributed data are aggregated and integrated into a big data infrastructure. While new meanings can be extracted from big data sets, the loss of individual emotional and practical elements denotes the loss of data provenance and the marginalisation of individual eff orts, motivations, and local politics, which might lead to disengaged participants, and unsustainable communities of citizen scientists. The challenges of constructing a data infrastructure for crowdsourced data therefore lie in the management of both technical and social issues which are local as well as global.