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.

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

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