Broad Data

Ethnographic methods in the age of interdisciplinary collaboration

Bibliographic Data

ID2402906
AuthorsSofie L Astrupgaard (0000-0001-9603-9142, University of Copenhagen, corresponding author), Emilie Munch Gregersen (0000-0001-6912-0922, University of Copenhagen), Emile Munch Gregersen (University of Copenhagen, corresponding author), Clara Rosa Sandbye (0000-0001-8564-4451, Aarhus University), M A Pedersen (0000-0002-2850-8661, Copenhagen Center for Social Data Science (SODAS) University of Copenhagen, Copenhagen, Denmark)
Year2025
Publication date2025-06-17
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEthnography (JOURNAL)
Journal identifiersISSN: 1466-1381 • E-ISSN: 1741-2714
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/14661381251349061
OpenAlexW4411358923
LanguageEN
References cited77

Under the aegis of what we term 'broad data ethnography', we outline four principles for the standardized collection, processing, and analysis of ethnographip data, particularly fieldnotes: compilability, compatibility , counting , and computability . As we demonstrate via examples from an interdisciplinary study at a Danish politics festival: compilability denotes the need for a shared data structure; compatibility refers to the demand for high similarity in data content; counting captures how standardizing both form and content emables systematic use of quantitative measures in the field, which in turn, and finally, allows for subsequent computational analysis. Finally, we address the potentials and pitfalls of adhering to these four principles, suggesting that in an age of increasing interdisciplinary collaboration and ubiquitous digital platforms and AI tools, 'broad data ethnography' offers an attractive alternative to conventional 'thick data' by allowing for short-term, computationally-augmented, team-based ethnography in situations where more individual and idiosyncratic approaches are not feasible

Ethnography · Sociology · Anthropology · Computational and Text Analysis Methods