Learning from Data Journeys

This is the final version. Available on open access from Springer via the DOI in this recordThis chapter discusses the idea of data journeys as an investigative tool and a theoretical framework for this volume and broader scholarship on data. Building on a relational and historicized understanding of data as lineages, I reflect on the methodological, conceptual and social challenges involved in mapping, analysing and comparing the production, movement and use of data within and across research fields - and some of the strategies developed to cope with such difficulties. I then provide an overview of the significant variation among the data practices garnered in this volume. Specific nodes of difference and similarity across data journeys are identified, while also emphasising the extent to which such commonalities are dependent on specific situations of inquiry. In closing, I highlight the significance of this approach towards addressing concerns raised by data-centric science and the emergence of big and open data.European CommissionAlan Turing Institut

Data, Meta Data and Pattern Data: How Franz Boas Mobilized Anthropometric Data, 1890 and Beyond

AbstractBetween 1890 and 1911, the German-American anthropologist Franz Boas conducted a whole suite of anthropometric studies, which all in all generated data from body measurements carried out on about 27,000 individuals. To this day, this data is being re-analyzed by researchers with a range of disciplinary interests. In my chapter, I will take a close look at a small subset of the original datasheets Boas used in his surveys, and how he and other scientists processed the data in later publications. My analysis will reveal that the extraordinary potential for travel and re-use of Boas’s data crucially depended on the way in which he designed his surveys. Alongside recording standard anthropometric variables, Boas collected genealogical and geographical information on the individuals measured, which allowed him to flexibly classify data in a variety of ways. It is this richness in structure, or “pattern data,” that explains why the data from Boas’s anthropometric projects remain valuable for researchers from a variety of disciplines to this very day.</jats:p