Capturing their “first” dataset: A graduate course to walk PhD students through the curation of their dissertation data

Authors

DOI:

https://doi.org/10.29173/iq971

Keywords:

Data curation, instruction, curriculum, data literacy, dissertation, thesis

Abstract

The data set accompanying theses is a valuable intellectual property asset, both from the viewpoint of the PhD student, who can procure employment and build publications and research grants from the work for years to come, and the university, which owns the data and has invested in the work. However, the data set has generally not been captured as a finished product in a similar manner to the published thesis. A course has been developed which walks PhD students through the process of identifying an archival data set, selecting a repository or long term storage location, creating metadata and documentation for the data package, and the deposit process. A pre- and post assessment has been designed to ascertain the level of data literacy the students gain through curating their own dataset. PIs for the projects have input into the repositories and metadata standards selected.  The university thesis office was consulted as the course was developed, so that accurate procedures and practices are reflected throughout the course. This first of a kind class is open to students of any discipline at a Research-1 university. The resulting mixture of data types creates a unique course every time it is offered.

Author Biography

Megan Sapp Nelson, Purdue University Libraries and School of Information Studies

Professor of Library Sciences

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Published

2020-09-23

How to Cite

Sapp Nelson, M., & Kong, N. N. (2020). Capturing their “first” dataset: A graduate course to walk PhD students through the curation of their dissertation data. IASSIST Quarterly, 44(3). https://doi.org/10.29173/iq971