On December 3, 2014, at the annual meeting for the American Anthropological Association in Washington DC, a roundtable was held examining the challenges of ethnographic data preservation. The roundtable was entitled “The Lifecycle of Ethnographic Information – Challenges in the Preservation and Accessibility of Ethnographic Data.” Five presenters were invited to speak, and a discussion was held afterwards, led by the roundtable organizers, Lisa Cliggett and Elizabeth A Faier.
During the roundtable, Mark Turin presented on his project Digital Himalaya – a project to digitally archive ethnographic materials from the Himalayan region. He argued that new digital archiving tools provided a powerful opportunity to reassemble analog materials, potentially enabling new analytic collaborations. Deborah Winslow, the program director for cultural anthropology at NSF described how, through an NSF grant led by Lisa Cliggett and Oona Schmid, the AAA had recently set up an anthropological data registry, where anthropologists could link to digital repositories where their ethnographic data had been archived. The registry, she argued, helped meet the AAA’s ethical guidelines – that 1) ethnographic data should be made available to those studied and 2) that ethnographic data should be preserved and archived.
In spite of these purported promises of digital archiving for anthropology, many folks in attendance acknowledged their reluctance to publicly share ethnographic data. Participants voiced concern that field notes – one of the most tangible forms of “data” for anthropologists – often include an anthropologist’s half-baked ideas. Field notes are taken from an anthropologist’s unique perspective – a perspective that implicates what the anthropologist discerns as worthy of jotting down in their field notebook. The session’s participants expressed concern that, in sharing their field notebooks, their half-baked ideas would be interpreted out of context – that others would attempt to derive meaning from the data without having the same deep knowledge of the domain and without sharing the perspective that led the anthropologist to jot the observation down.
The session, for me, captured the spirit of the double bind of data sharing in anthropology. To share ethnographic data ethically, anthropologists need semiotic infrastructure that can richly capture and transport the meaning of their data – so that others do not interpret disaggregated data out of context. Yet often the very goal of ethnographic data sharing is to enable diverse anthropologists to interpret cultural data in new ways, bringing new meaning to data. How can we design infrastructure to preserve the meaning of ethnographic data, while also enabling its meaning to iterate and evolve? How do we build infrastructure that respects the concern of anthropological data being interpreted out of context, while also acknowledging that interpreting data out of context may bring richer cultural analysis to data?