  Data curation is the process of making a dataset fit-for-use and archiveable.
It is critical to data-intensive science because it makes complex data
pipelines possible, makes studies reproducible, and makes data (re)usable. Yet
the complexities of the hands-on, technical and intellectual work of data
curation is frequently overlooked or downplayed. Obscuring the work of data
curation not only renders the labor and contributions of the data curators
invisible; it also makes it harder to tease out the impact curators' work has
on the later usability, reliability, and reproducibility of data. To better
understand the specific work of data curation -- and thereby, explore ways of
showing curators' impact -- we conducted a close examination of data curation
at a large social science data repository, the Inter-university Consortium of
Political and Social Research (ICPSR). We asked, What does curatorial work
entail at ICPSR, and what work is more or less visible to different
stakeholders and in different contexts? And, how is that curatorial work
coordinated across the organization? We triangulate accounts of data curation
from interviews and records of curation in Jira tickets to develop a rich and
detailed account of curatorial work. We find that curators describe a number of
craft practices needed to perform their work, which defies the rote sequence of
events implied by many lifecycle or workflow models. Further, we show how best
practices and craft practices are deeply intertwined.
