Sorting things out: classification and its consequences
Sorting things out: classification and its consequences
Trust and epistemic communities in biodiversity data sharing
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As the basic sciences become increasingly information-intensive, the management and use of research data presents new challenges in the collective activities that constitute scholarly and scientific communication. This also presents new opportunities for understanding the role of informatics in scientific work practices, and for designing new kinds tools and resources needed to support them. These issues of data management, scientific communication and collective activity are brought together at once in scientific data collections (SDCs). What can the development and use of shared SDCs tell us about collective activity, dynamic infrastructures, and distributed scientific work? Using examples drawn from a nascent neuroscience data collection, we examine some unique features of SDCs to illustrate that they do more than act as infrastructures for scientific research. Instead, we argue that they are themselves instantiations of Distributed Collective Practice (DCP), and as such illustrate concepts of transition, emergence, and interdependency that may not be so apparent in other kinds of DCPs. We propose that research into SDCs can yield new insights into institutional arrangements, policymaking, and authority structures in other very large-scale socio-technical networks.