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Paper short abstract

Parallel sampling, interpretation of large datasets and synchronous reading of ecological heterogeneous data are discussed referring to a recent fieldwork in Antarctica. The extreme context provides the conditions for a multi-scale temporal analysis of ice samples as anthropo-environmental markers.

Paper long abstract

The work on large multidisciplinary datasets represents the late frontiers of anthropological analysis, as the strategies of data collection diversify and multiply in eco-logical research, and while the algorithms of data and text analysis gain more and more momentum in the social sciences. The increasingly accessible ways of processing very large datasets, mainly AI driven processes, boost and justify strategies of large scale data extraction, opening questions on the effective interoperability of the data deriving from heterogeneous sources and on the epistemology of crossing methodological boundaries.

The paper draws on the multidisciplinary fieldwork I developed in Antarctica in the fall-winter 2024-25. The confined and extreme Antarctic context provides a unique observatory on the practices of multi-disciplinarity in environmental research. Located on the converging lines of glaciers’ and sea ice’ melting frontiers, the collected samples produce sets of simultaneous and parallel data, aiming at representing the glaciers’ complex dynamics, and providing a large scale and to-date picture on the ice-melting global threat. Anthropic, climatic, geological and biological and markers are scanned simultaneously in the samples, requiring a multidimensional time analysis and the rethinking of chronological drivers in the development of interpretive models. The discussion unfolds around the role of the human time scale in the production and selection of interpretative models, on the epistemic relevance of human-made data selection a process and, ultimately, on the elusive boundary between data-driven and interpretative-driven results.