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Accepted Paper:
Paper short abstract:
The presentation draws on ethnographic research to describe data practices of appropriating the web for social research in Digital methods as layers of infrastructuring. The web is mediated by community infrastructures to support iterative assembling of the local infrastructure of a knowledge space.
Paper long abstract:
The Digital methods approach seeks the strategic appropriation of digital resources on the web for social research. I apply the grounded theory to theorize how data practices in Digital methods are entangled with the web as a socio-technical phenomenon. My account draws on public sources of Digital methods and ethnographic research of semester-long student projects based on observations, interviews and project reports. It is inspired by Hutchin's call for understanding how people "create their cognitive powers by creating the environments in which they exercise those powers". The analysis draws on the lens of infrastructuring to show that making environments for creativity in Digital methods is a distributed process, which takes place on local and community levels with distinct temporalities. Digital methods is predicated on creating its local knowledge space for social analysis by pulling together digital data and tools from the web, and this quick local infrastructuring is supported by layers of slower community infrastructures which mediate the digital resources of the web for a Digital methods style analysis by means of translation and curation. Overall, the socially distributed, infrastructural style of data practice is made possible by the web as a socio-technical phenomenon predicated on openness, sharing and reuse. On the web, new digital resources are readily available to be incorporated into the local knowledge space, making way for an iterative, exploratory style of analysis, which oscillates between infrastructuring and inhabiting a local knowledge space. The web also serves as a socio-technical platform for community practices of infrastructuring.
Critical data studies
Session 1 Saturday 3 September, 2016, -