Applying Translational Principles to Data Science Curriculum Development

نویسندگان

  • Liz Lyon
  • Eleanor Mattern
  • Amelia Acker
  • Alison Langmead
چکیده

This paper reports on a curriculum mapping study that examined job descriptions and advertisements for three data curation focused positions: Data Librarian, Data Steward / Curator, and Data Archivist. We present a transferable methodological approach for curriculum development and the findings from our evaluation of employer requirements for these positions. This paper presents “model pathways” for these data curation roles and reflects on opportunities for iSchools to adopt translational data science principles to frame and extend their curriculum to prepare their students for data-driven career opportunities.

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تاریخ انتشار 2015