The FAIR principles require research data to be published with complete metadata and ideally shared at different key milestones during the research. However currently, data publication and sharing happen mostly at the end, and published data mostly lack important supplementary information and metadata limiting its reusability. On the other hand, regular high-quality data publication takes time and requires manual interaction with the data repositories.
fairly toolset aims to bridge this gap by enabling easy research data publication directly from your digital research environment. The toolset, which includes a JupyterLab extension, a command-line tool, and a Python library, allows quick research data cloning, local data and metadata management, unattended upload of large datasets, and smart synchronization with remote data repositories with minimum effort. During the training you will learn how to access and download datasets by using the toolset, and how to create and upload your own research datasets to popular research data repositories, such as Zenodo, figshare, and 4TU.ResearchData.
The workshop covers the following aspects:
- Fundamentals of research data management
- Popular research data repositories: Zenodo, Figshare, Dataverse, 4TU.ResearchData
- Accessing and downloading research datasets with fairly toolset
- Creating and managing research datasets with fairly toolset
For more information and registration please visit the event page.
