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Library cultures of data curation: Adventures in astronomy
Author(s) -
Darch Peter T.,
Sands Ashley E.,
Borgman Christine L.,
Golshan Milena S.
Publication year - 2020
Publication title -
journal of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.903
H-Index - 145
eISSN - 2330-1643
pISSN - 2330-1635
DOI - 10.1002/asi.24345
Subject(s) - data curation , reuse , digital curation , process (computing) , world wide web , set (abstract data type) , computer science , data science , discipline , scholarly communication , knowledge management , sociology , engineering , political science , social science , publishing , waste management , law , programming language , operating system
University libraries are partnering with disciplinary data producers to provide long‐term digital curation of research data sets. Managing data set producer expectations and guiding future development of library services requires understanding the decisions libraries make about curatorial activities, why they make these decisions, and the effects on future data reuse. We present a study, comprising interviews ( n = 43) and ethnographic observation, of two university libraries who partnered with the Sloan Digital Sky Survey (SDSS) collaboration to curate a significant astronomy data set. The two libraries made different choices of the materials to curate and associated services, which resulted in different reuse possibilities. Each of the libraries offered partial solutions to the SDSS leaders' objectives. The libraries' approaches to curation diverged due to contextual factors, notably the extant infrastructure at their disposal (including technical infrastructure, staff expertise, values and internal culture, and organizational structure). The Data Transfer Process case offers lessons in understanding how libraries choose curation paths and how these choices influence possibilities for data reuse. Outcomes may not match data producers' initial expectations but may create opportunities for reusing data in unexpected and beneficial ways.