DSW
DSW

FAIR

The FAIR data recommendations is one of the steps in making data machine-actionable. According to these recommendations, data should be Findable, Accessible, Interoperable, and Reusable. It may not be easy to fully grasp the concept of FAIR, but DSW will make it easier for you, so you can be comfortably up to date with the latest standards.

FAIR Illustration

FAIR Metrics in DSW

You can evaluate answers in each questionnaire to get an overview of how good you are doing in terms of FAIR metrics. Thus you are able to reconsider your decisions already in the planning phase to make your research more FAIR.

FAIR Metrics in DSW

FAIR Guidance

Answers to the questions are marked with labels determining the FAIRness of the answer. This means, when using the DSW, you do not have to know all the FAIR principles and how they work to make your research FAIR. You will know the best approach from the labels and can therefore choose a better way for your research.

FAIR Guidance