Alliance Research Data Management (RDM) Jumpstart Workshop

Description

This week-long workshop will introduce attendees to best practices in Research Data Management (RDM) using common tools to support research transparency and reproducibility. Robust implementation of RDM principles enables researchers to address bias and reproducibility, effectively share their research, and ensure long term access to their research inputs and outputs. From research question development to findings dissemination, RDM underpins a fruitful and successful academic career.

This is an entry level workshop. The intended audience includes graduate and early career researchers with no or limited knowledge and experience implementing best practices in RDM or using computational tools (R, OSF, Borealis) for research. Note that this is not a statistics course.

Sessions will address the importance and underlying principles of RDM. We’ll explore issues related to RDM and the growing landscape of RDM-related requirements stemming from funders and publishers. Using the R programming language, the Open Science Framework (OSF), and Borealis (Dataverse), we’ll explore solutions to address these issues and enable compliance with funder and publisher requirements. All attendees will work with a common dataset to explore how to ask questions of data using common computational tools. 

Throughout, attendees will be introduced to:

• the documentation and metadata requirements to ensure accessibility;
• considerations to address different aspects of reproducibility;
• practices to maintain their data’s integrity; and,
• ways to ensure their final data deposit is adherent to FAIR (Findable, Accessible, Interoperable, Reusable) principles.

To register and learn more about the workshop, please visit the RDM Jumpstart webpage. 

Please note that registration closes on April 9th.