The study of boundaries has been integral to social science research (Abbott, 1995; Lamont & Molnar, 2002), particularly in Science and Technology Studies (STS), the sociology of work, and organization studies. The growing pervasiveness of data-based methods, data infrastructures, and data analysis in science, business, education, and public administration is also fundamentally concerned with boundaries. However, the rich body of STS scholarship on boundaries and boundary concepts constitutes a thus far underutilized resource for STS analyses into datafication that merits further exploration.

Against this backdrop, the workshop “Boundaries and boundary concepts as/in datafication” aims to advance a systematic and STS-grounded exploration of boundaries and boundary concepts in the context of datafication. It will explore the potentials and limitations of analytical concepts such as boundary work and boundary objects, as well as boundaries more broadly. The workshop further serves to develop manuscripts for a Special Issue submission.

This is a closed workshop.

The workshop organizers are deeply grateful for funding support provided by the DEEP CULTURE research project (PI: Tobias Blanke).

Organisers

Dr. Yana Boeva is Junior Research Group Leader and Postdoctoral Researcher at the Institute for Social Sciences and the Cluster of Excellence “Integrative Computational Design and Construction for Architecture (IntCDC),” University of Stuttgart, Germany. Her research interests include the critical studies of computation, digital infrastructures and platformization, knowledge requirements in the digital transformation, epistemic cultures and practices of engineering cultures, and their sociocultural context. Her work has been published in Science as Culture, Science & Technology Studies, Historical Social Research, Digital Culture & Society, and in several edited volumes. She holds a PhD in Science & Technology Studies from York University, Toronto.

Louis Ravn is a PhD Candidate in AI, Digital Culture, and Deep Learning at the University of Amsterdam, Netherlands. Drawing from STS and critical data/AI studies, his research investigates the sociotechnical dimensions of emerging data and AI technologies. Most recently, he has studied synthetic data from the perspectives of hype, surveillance, and evaluation. His research has been published in Big Data & Society, Internet Policy Review, Digital Society, and Surveillance & Society. Before that, he obtained his MSc in STS from the University of Edinburgh, winning awards for both the “Best Dissertation” and the “Best Performance in the STS Program”.

Prof. Sarah Davies is Professor of Technosciences, Materiality, & Digital Cultures at the Department of Science and Technology Studies, University of Vienna, Austria, where her current work explores the intersections between digital and epistemic practices and forms of life. Her books include Science Societies (2024, BUP), Exploring Science Communication (2020, SAGE, with Ulrike Felt) and Hackerspaces (2017, Polity).