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FAIR

Take part in a Data Management Practices survey

We are inviting all Estonian research community members to take part in a survey about the current data management practices in Estonia.

 

EDIT: The survey will remain open until 10th of October, 2021. 

The survey will remain open until at least the end of July (July 31st, 2021) 10th of October 2021 and should take approximately 30 minutes to fill out. We will randomly pick a couple of lucky people who have participated in the survey to win a goodie bag from us. The survey can be found here: https://survey.ut.ee/index.php/752887?lang=en 

“How FAIR are you” Webinar Series and Hackathon (Jan-Apr 2021) organised by CINECA

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   
Practically Fair    
How to make training FAIR    
Ethics/ELSI considerations - From FAIR to fair data sharing

More information and registration is available at https://www.cineca-project.eu/news-events-all/how-fair-are-you-webinar-series-and-hackathon.

 

FAIR Data Stewardship – digital data scholarship for wetlab scientists - course in the Netherlands

From 27-29 May, 2019, we will organize the first course in  Data Analysis and Stewardship theme of the Helis Academy:  

FAIR Data Stewardship – digital data scholarship for wetlab scientists

The target audience is wet-lab scientists – from industry and academia – and graduate students in the Life Sciences who wish to improve their digital scholarship on data handling. Some basic experience with programming and scripting languages like python, perl, R, matlab, etc. are an advantage, but not needed.

The course will introduce the trainees to important concepts of data stewardship. We start with a general introduction covering the data life cycle, the FAIR principles and a definition of data stewardship and data stewards. The course is also relevant for Data Stewards who are supporting the life science researchers.

 

We will pass the stages of the data life cycle in more detail in the training modules of this 3 day course.

  • On day one trainees will investigate data management plans, which types are there and how they should be used.
  • On day two the course highlights how to work with data during the research phase, explaining how to create well formatted data which helps in the second module of day two to make data interoperable already during the active research phase.
  • On day three trainees will have an in-depth at persistent identifiers, different use cases and types of identifiers. Finally we are closing the data life cycle by making data fit for sharing, archiving and publishing. 

This course is part of the Data Analysis and Stewardship theme of Helis Academy and is organised by DTL and DTL collaborators. Info about other courses in the theme of Data Analysis and Stewardship can be found on the Helis Academy website and on the Helis Academy page on the DTL website.

You can find all the information, including the full programme and registration possibilities here: https://www.aanmelder.nl/helis-fair-data-stewardship-course