• Establishing a framework for evaluating & understanding
    large-scale, cross-disciplinary collaboration
    on big data tools, techniques, & methods. READ MORE

Assembling Data Science

Assembling Data Science is a first-in-kind sociotechnical analysis of efforts to institutionalize data science at the national level in the United States, a process that is in fact occurring at vastly different scales and at quite a rapid pace. Within and across nearly every domain, it is argued that new modes of aggregating and analyzing data hold the promise of addressing the major social and scientific issues of our times: from agriculture to healthcare, and from interoperability to computational reproducibility.

Taking the NSF-funded Big Data Regional Innovation Hubs and Spokes (bdHubs) as our point of departure, we situate this recent initiative in a much longer historical arc of large-scale and long-term research infrastructure development in the US dating back more than 50 years. From this perspective, bdHubs is a key site for analyzing the ongoing and mutual (re)shaping of policy, technological development, and organizational dynamics at the dawning of a new era of data science.

A central objective of our project is thus to characterize these changes that are occurring at the very moment the bdHubs program is being rolled out. Here, we are attentive to the strategies that the Hubs and Spokes deploy as they adapt to -- while simultaneously participate in furthering -- the enhanced capacities of information science and technologies, as well as the formation of novel institutional arrangements among government, industry, nonprofit organizations, and the academy.

Unpacking large-scale, cross-sector collaborations centered on the tools and techniques of data processing and visualization motivates a fundamental insight: that the advent of data science in the US is not only indicative of a burgeoning paradigm of technical research, but points to a broader institutional movement whose very unfolding warrants further exploration. Our research program establishes a coherent ethnographically-informed analytic framework for mapping technological assemblages and policy pathways, one that should find relevance to students of science, policymakers, and practitioners alike.

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Assembling Data Science Researchers


deLAB Publications

Assembling Data Science is a new project and publications will be added here as soon as they become available. In the meantime here are some of deLAB's recent publications — click the button below for a more comprehensive list.

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Notes on the Concept of Data Interoperability: Cases from an Ecology of AIDS Research Infrastructures (2017)

Ribes, D.

Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing. 2017, ACM: Portland, Oregon, USA. p. 1514-1526.
ACM Digital Library

Organizing for Ontological Change: The Kernel of a Research Infrastructure (2015)

Ribes D and Polk JB

Social Studies of Science 45(2): 214-241.

Making an Issue out of a Standard: Storytelling Practices in a Scientific Community (2013)

Millerand, F., D. Ribes, K.S. Baker, and G. C. Bowker

Science, Technology & Human Values 38 (1):7-43.
Publisher's website