Here we offer a two-day workshop with the primary aim of introducing participants to good enough practices for managing their data. On the first day, participants will learn about the basics of data management, good research practices, Common European Data Spaces, data management and governance in industry and data management plans. On the second day, participants will learn how to organise their data, how to make it FAIR, about electronic lab notebooks and how to make their computational results reproducible.
On September 1st (2021), 10-11am CEST, Open Science Coffee will be holding an online seminar "Research Code Review".
More researchers are writing code to process, analyse and visualise their data. For reproducible and robust research, it is increasingly important that this code is reviewed. Join this inaugural Open Science Coffee to learn more and discuss best practices, challenges and opportunities in reviewing research code.
Register before seminar in here: https://tudelft.zoom.us/meeting/register/tJwtcOypqzwpHNZPRVlObq8dK_DIGy0yWLrs
More information: https://osc-delft.github.io/events
The “How FAIR are you” webinar series and hackathon aim at increasing and facilitating the uptake of FAIR approaches into software, training materials and cohort data, to facilitate responsible and ethical data and resource sharing and implementation of federated applications for data analysis.
The hackathon will be a practical online event to investigate gaps in the application of FAIR principles to project outputs and facilitate the implementation of FAIR approaches, where possible. The Hackathon will focus on cohort data, software tools including workflows, algorithms as well as web services, and training materials. The hackathon will be preceded by a “How FAIR are you” webinar series to provide background and introduce theoretical concepts that might be useful during the practical sessions. All participants are encouraged to attend or watch the recordings of the webinar series.
The webinar topics include:
Introduction to FAIR principles - Open science through FAIR health data networks: dream or reality?
Making Cohort data FAIR
FAIR Software tools
How to make training FAIR
Ethics/ELSI considerations - From FAIR to fair data sharing