Studying Data Communities: Analytical Dimensions from and for Empirical Research

KULA knowledge creation dissemination and preservation studies, vol. 9, pp. 1–16

Abstract

How can data communities be studied? In this paper, we combine existing literature with our own research spanning more than a decade to propose five dimensions and a series of guiding questions that can be used to analyze data communities. These dimensionsーdisciplinary domains, social orderings, material orderings, data uses, and data expertiseーillustrate the variability of data communities and offer starting points for future empirical research, infrastructure design, and policy activities. Analyzing data communities through the multidimensional perspectives that we propose encourages critical interrogation of these heterogeneous groups while highlighting the complex ways in which data practices constitute particular communities and how those communities in turn shape data. Studying data communities with the questions we propose provides ways to honor epistemic diversity, experiment with community-centric infrastructures and policies, and create and value different forms of expertise.

Authors 2

1. Kathleen Gregory Aachen

   Leiden University

   Affiliation as printed

   Leiden University

2. Sarah W. Davies

   University of Vienna

   Affiliation as printed

   University of Vienna