The reproducibility of research is essential to the scientific community, as it ensures the accuracy and reliability of research findings that are used to build upon existing knowledge. However, reproducibility is often hindered by the lack of access to research data, documentation, and code. This workshop will provide an overview of the concepts of open science, reproducibility, and the FAIR principles of research data, as well as explore how to deposit and share data in Borealis, the Canadian Dataverse Repository, a bilingual, multidisciplinary, secure, Canadian research data repository, supported by academic libraries and research institutions across Canada. The learning objectives of the workshop include:
- Understand the Canadian context of sharing data as it relates to the FAIR principles and the importance of scientific reproducibility
- Gain skills related to depositing and sharing research data, documentation, and code in Borealis
- Explore Borealis features to support reproducibility and effective reuse of research data, including Computational Workflow Metadata and uploading from GitHub.
- Participants will have the opportunity to search and access sample datasets and code, with a focus on real world examples and use cases.
By the end of the workshop, participants will have gained skills and knowledge related to depositing and sharing research data, documentation, and code with an emphasis on openness and reproducibility, improving the quality and impact of their research.
Level: Introductory
Length: 1.5 Hours
Format: Lecture
Prerequisites: None
- Teacher: Meghan Goodchild
- Teacher: Amber Leahey