Data Management Education from the Perspective of Science Educators

Abstract

In order to better understand the current state of data management education in multiple fields of science, this study surveyed scientists, including information scientists, about their data management education practices, including at what levels they are teaching data management, which topics they covering, and what barriers they experience in teaching these topics. We found that a handful of scientists are teaching data management in undergraduate, graduate, and other types of courses, as well as outside of classroom settings. Commonly taught data management topics included quality control, protecting data, and management planning. However, few instructors felt they were covering data management topics thoroughly, and respondents cited barriers such as lack of time, lack of necessary expertise, and lack of information for teaching data management. We offer some potential explanations for the existing state of data management education and suggest areas for further research.

Data management and sharing in neuroimaging: Practices and perceptions of MRI researchers

“…This issue is also not unique to neuroimaging. In a recent survey, PI's from across the National Science Foundation (NSF)'s biological sciences directorate listed training on data management as one of their foremost unmet needs 62 . Though topics related to RDM are often included in undergraduate and graduate level coursework, many educators report that they are not covered thoroughly due to a lack of time, expertise, and guidance 63 .…”

Best Practice Data Life Cycle Approaches for the Life Sciences

“…This suggests a gap between modern biological research as a field of data science, and biology as it is still mostly taught in undergraduate courses, with little or no focus on computational analysis, or project or data management. As reported elsewhere [21][22][23], this gap has left researchers lacking key knowledge and skills required to implement best practices in dealing with the life cycle of their data.…”

“…Learning how to find, store and share research data is not typically an explicit part of undergraduate or postgraduate training in the biological sciences [21][22][23]. The scope, size and complexity of datasets in many fields has increased dramatically over the last 10-20 years but the knowledge of how to manage this data is currently limited to specific cohorts of 'information managers' (e.g.…”

“…The scope, size and complexity of datasets in many fields has increased dramatically over the last 10-20 years but the knowledge of how to manage this data is currently limited to specific cohorts of 'information managers' (e.g. research data managers, research librarians, database curators and IT professionals with expertise in databases and data schemas [23]). In response to institutional and funding requirements around data availability, a number of tools and educational programs have been developed to help researchers create Data Management Plans to address elements of the data lifecycle [24]; however, even when a plan is mandated, there is often a gap between the plan and the actions of the researcher [13].…”

Gaining Competency: Learning to Teach Data Visualization

“…Libraries likewise prioritize visualization and list it as a desired competency for data librarians in job postings (Lyon et al 2015). However, major data curation curricula offer almost no support for this topic (Lamar Soutter Library 2017;DataONE 2017;EDINA and Data Library 2017;Johnston and Jeffryes n.d.), nor is visualization considered under the umbrella of data management education or data services in several studies (Tenopir et al 2016;Strasser and Hampton 2012;Tenopir et al 2015;Hernandez et al 2012;Harris-Pierce and Quan Liu 2012;Bresnahan and Johnson 2013). Librarians providing research data services may therefore need strategies to develop expertise in data visualization in order to provide service in this area.…”