T04 – Showing and Evaluating Our Safari to FAIR
Tag, Uhrzeit, Dauer
Sonntagvormittag, 9–13 Uhr, 4h
Angebotene Sprache
Englisch
Kurzbeschreibung
A working group of the CODEX+ project recently conducted a survey within the Netzwerk Universitätsmedizin (NUM) to evaluate the ways in which the FAIR principles are applied across the network. The lack of participation in this survey suggested that these principles have not yet been implemented into the workflows of the NUM projects. But even outside of the NUM, the FAIR principles do not seem to be truly integrated into data stewardship yet and are only seen as a nice-to-have. Yet they make a significant contribution to the sustainability of data and should therefore be considered as a matter of urgency in every project as early as during the project planning stage. Understandably, it may be difficult to implement these principles, especially for first-timers. This workshop is designed to help expand and strengthen participants‘ understanding and knowledge of the FAIR data principles. This workshop is also designed to address any difficulties or concerns about FAIR implementation. In the first part, we would like to introduce the various principles and sub-principles in detail as well as explain their relevance. We will then use mock data to demonstrate the individual FAIRification steps as well as tools that can be used in this journey. In the last part, the participants have the opportunity to independently perform a FAIRification exercise and then evaluate their FAIRification journey. At the end, we would like to present existing FAIR assessment tools that can help to evaluate data FAIRness and FAIRification workflows that can be employed to FAIRify data. The audience is invited to ask questions and we support and accompany them on the FAIRification journey in case of possible problems. We hope that this training will enable the participants to easily integrate the FAIR principles into their research and thus be more thorough in their research data management. Expected learning objectives/planned outcomes:
1. The audience will understand and appreciate the concept of the FAIR data principles
2. The audience will be able to independently take steps towards data FAIRification
3. The audience will be able to independently evaluate the FAIRness of their data.
Fachliche Voraussetzungen
Keine
Technische Voraussetzungen
Laptop. Mock data will be provided for this exercise but the audience is welcome to bring along their own data.
Organisatorin
Esther Inau
Institution
Department of Medical Informatics, Universitätsmedizin Greifswald, Greifswald
Kontakt
inaue [at] uni-greifswald.de
Zusätzliche Referentin
Lea Michaelis
Institution
Datenintegrationszentrum Universitätsmedizin Greifswald, Greifswald