Publishing Research Data with fairly Toolset

Do you want to attend the training?

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, organized in collaboration with TU Delft Digital Competence Centre, covers the following aspects:

Participants must have access to a computer with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on.


15 May 2024, 13:00-17:00


ITC Building, Room LA 2301
Hallenweg 8, 7522 NH Enschede


The participants should have basic familiarity with using Python and a command shell, and we expect participants also to be acquainted with text editors like Vim, Nano, or Notepad++.


Registration is closed.

Instructors S. Girgin MSc (Serkan)
Associate Professor, Head of CRIB
Manuel Garcia Alvarez MSc
Research Software Engineer


13:00 - 13:15

Welcome and icebreaker

13:15 - 13:30

Introduction to research data publishing

13:30 - 14:00

Research data repositories: Zenodo, Figshare, Dataverse, 4TU.ResearchData

14:00 - 14:45

Introduction to fairly toolset

14:45 - 15:00

Coffee break

15:00 - 15:45

Research data management with fairly Jupyterlab extension: Jupyter Fairly

15:45 - 16:00

Research data management with fairly command line interface: fairly CLI

16:00 - 16:45

Advanced research data management with fairly Python package

16:45 - 17:00


For more information or questions, please contact Dr. Serkan Girgin (