What lies beneath?: Knowledge infrastructures in the subseafloor biosphere and beyond

  • Peter T. Darch
  • Christine L. Borgman
  • Sharon Traweek
  • Rebekah L. Cummings
  • Jillian C. Wallis
  • Ashley E. Sands


We present preliminary findings from a three-year research project comprised of longitudinal qualitative case studies of data practices in four large, distributed, highly multidisciplinary scientific collaborations. This project follows a 2 \(\times \) 2 research design: two of the collaborations are big science while two are little science, two have completed data collection activities while two are ramping up data collection. This paper is centered on one of these collaborations, a project bringing together scientists to study subseafloor microbial life. This collaboration is little science, characterized by small teams, using small amounts of data, to address specific questions. Our case study employs participant observation in a laboratory, interviews (\(n=49\) to date) with scientists in the collaboration, and document analysis. We present a data workflow that is typical for many of the scientists working in the observed laboratory. In particular, we show that, although this workflow results in datasets apparently similar in form, nevertheless a large degree of heterogeneity exists across scientists in this laboratory in terms of the methods they employ to produce these datasets—even between scientists working on adjacent benches. To date, most studies of data in little science focus on heterogeneity in terms of the types of data produced: this paper adds another dimension of heterogeneity to existing knowledge about data in little science. This additional dimension makes more complex the task of management and curation of data for subsequent reuse. Furthermore, the nature of the factors that contribute to heterogeneity of methods suggest that this dimension of heterogeneity is a persistent and unavoidable feature of little science.


Data deluge Big science Little science Multidisciplinary scholarship Knowledge infrastructures 



The work in this paper has been supported by the Sloan Foundation Award #20113194, The Transformation of Knowledge, Culture and Practice in Data-Driven Science: A Knowledge Infrastructures Perspective. We also acknowledge the contributions of Milena Golshan, Irene Pasquetto, and Laura A. Wynholds for commenting on drafts of this paper, and Elaine Levia for technical and administrative support.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  • Peter T. Darch
    • 1
  • Christine L. Borgman
    • 1
  • Sharon Traweek
    • 1
  • Rebekah L. Cummings
    • 1
  • Jillian C. Wallis
    • 1
  • Ashley E. Sands
    • 1
  1. 1.Knowledge Infrastructures Project, Department of Information StudiesUCLALos AngelesUSA

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