Data work configurations in the field-based natural sciences: mesoscale infrastructures, project collectives, and data gateways
Baker, Karen Schepeler
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https://hdl.handle.net/2142/98131
Description
Title
Data work configurations in the field-based natural sciences: mesoscale infrastructures, project collectives, and data gateways
Author(s)
Baker, Karen Schepeler
Issue Date
2017-06-30
Director of Research (if dissertation) or Advisor (if thesis)
Palmer, Carole L.
Doctoral Committee Chair(s)
Palmer, Carole L.
Committee Member(s)
Cutcher-Gershenfeld, Joel E
Mayernik, Matthew S.
Twidale, Michael B.
Department of Study
Information Sciences
Discipline
Library & Information Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Data work
Data management
Data curation
Data repositories
Data sharing
Participatory design
Abstract
This multi-case, longitudinal ethnographic study investigates data work configurations of research projects in the field-based natural sciences. Project collective data work involves managing data in addition to facilitating digital data archiving. Through qualitative analysis, the concepts of data work arenas, information environments, and pre-archive data work are incorporated into a Data Work System model that foregrounds mesoscale infrastructures central to the movement of data from its origin in the field to its destination in an archive. The model integrates a system perspective within which data intermediaries play a key role as infrastructure is grown to support the dynamics associated with research data use. As an outcome of the analysis, three kinds of mesoscale data collectives are characterized as Local, Archive, and Developing. Three case studies illustrate the diversity of data work configurations, characterize mesoscale infrastructures as future-making prototypes, and demonstrate the relevance of Local Data Collectives as Data Gateways in planning information architecture. The cases contribute to the development of conceptual resources critical to maintaining the vibrancy and vigor of scientific research and the data work associated with data production in addition to knowledge production.
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