Start Date
3-17-2020 10:30 AM
End Date
3-17-2020 11:30 AM
Keywords
data management, data sharing, cross-disciplinary
Description of Proposal
At Duke University there is a requirement for all graduate students to take a number of credits in courses called Responsible Conduct of Research (RCR). While faculty and staff members can be approved to teach these two hour workshops, librarians at Duke have in the last few years proposed several that cross disciplinary boundaries, such as the workshop on retractions in the science and social scientific literature as well as more discipline focused, such as Scholarly Publishing in East Asian Studies.
For our presentation we would like to focus on developing, delivering and evolving the RCR courses on data management. These workshops focus on educating graduate students on best practices on pre-project planning, active workflow design and organization, storage and backup strategies, publishing data via repositories, preparing data for sharing, and strategies for integrating reproducible research practices.
We have taken an iterative approach to the development of these workshops over the past three years. While these workshops began being targeted on high-level topics, our Data Management 101 courses have evolved to become more inclusive of cross-disciplinary data, such as images, textual corpuses and social science data inclusive of mixed methodological data. Our presentation at the conference will trace the life cycle of changes across the early and present versions of these RCR courses and preview upcoming changes to the elements of the course.
Presentation Proposal
Data Management (or how I learned to love my data): Reaching Graduate Students through a Responsible Conduct of Research Program
At Duke University there is a requirement for all graduate students to take a number of credits in courses called Responsible Conduct of Research (RCR). While faculty and staff members can be approved to teach these two hour workshops, librarians at Duke have in the last few years proposed several that cross disciplinary boundaries, such as the workshop on retractions in the science and social scientific literature as well as more discipline focused, such as Scholarly Publishing in East Asian Studies.
For our presentation we would like to focus on developing, delivering and evolving the RCR courses on data management. These workshops focus on educating graduate students on best practices on pre-project planning, active workflow design and organization, storage and backup strategies, publishing data via repositories, preparing data for sharing, and strategies for integrating reproducible research practices.
We have taken an iterative approach to the development of these workshops over the past three years. While these workshops began being targeted on high-level topics, our Data Management 101 courses have evolved to become more inclusive of cross-disciplinary data, such as images, textual corpuses and social science data inclusive of mixed methodological data. Our presentation at the conference will trace the life cycle of changes across the early and present versions of these RCR courses and preview upcoming changes to the elements of the course.
What takeaways will attendees learn from your session?