Revising the research data lifecycle: Evidence from oceanography
DOI:
https://doi.org/10.47989/ir31iConf64146Keywords:
Research data management (RDM), Data sharing, Scientific data, Data management plansAbstract
Introduction. This research examines temporal elements of data management for ocean science researchers funded by the United States’ National Science Foundation (NSF). By uncovering data practices for sharing data, this paper finds that researchers’ experience diverges significantly from traditional models of research data lifecycle.
Method. Corpus creation of 379 Data Management Plans (DMP) from NSF funded oceanography awards between 2011-2021 and 34 semi-structured interviews with principal investigators (PIs) and data managers from purposive and snowball sampling.
Analysis. Qualitative coding of both DMP documents and interview transcripts using MaxQDA software using a codebook drawn from Adam’s (1998) timescapes framework and themes developed through inductive qualitative analysis of the interview transcripts.
Results. Research data management to support sharing data lacks an established place in the organization of research practice and often leads to end-loaded project data management. Three ways that researchers are developing new practice-time profiles include creating routines, automating workflows, and anticipating the data practices of reusers.
Conclusion(s). Data management for sharing is not only constrained but also actively shaped through time. Research data lifecycles need to place more emphasis on the actors within this lifecycle.
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