Developing Specialized Data Curation Curricula to Meet Growing Demands: A Community-based and Evolving Approach

Abstract

Data curation is “the encompassing work and actions taken by curators of a data repository in order to provide meaningful and enduring access to data” (Johnston et al., 2018a).  It can be multifaceted and complex based on the types of data, the expertise of the curator, disciplinary expectations, and repository policies. With evolving data sharing practices and standards, ensuring data curators and stewards have access to high-quality, extensible instruction on specific data types is essential for supporting the goals of open research and accessible data sharing, particularly in the landscape where funders (National Institutes of Health, 2020) and journals (Naughton & Kernohan, 2016) are mandating data publication for the purpose of reproducibility, reuse, and external validation. In brief, data need to be curated for effective re-use and in alignment with the FAIR principles (Wilkinson et al., 2016). The Data Curation Network (DCN) (Johnston et al., 2018b) has been actively developing education and training programs to expand capacity in data curation along multiple axes. This paper will explore the progression of the DCN’s education program based primarily within the United States, highlighting a recent effort to develop specialized data curation education for four specialized data types. We will conclude with lessons learned, reflections on growth of education efforts in the DCN more broadly, and potential next steps.