From FAIRytale to reality: Research Data Management put into practice

In this data-driven age there is a need to transform the current publication-focused infrastructure to promote the reuse of data and accelerate the progress of scientific research. The FAIR principles facilitate more transparent and reproducible research by providing Research Data Management guidelines to make research output Findable, Accessible, Interoperable and Reusable. Research Data Management can be time and cost-efficient, improve the quality of scientific practice and provide recognition for all research output, greatly benefiting the individual researcher as well as the research community as a whole. According to the FAIR principles your research output should be Findable (F) by having a persistent identifier as well as metadata (data providing information about your data). This metadata has to be Accessible (A) by both humans and machines. Increased Interoperability (I) is achieved through the use of community standards and vocabulary, as well as open formats. When your research output is sufficiently documented and is accompanied with a license it becomes Reusable (R) for others. This poster offers some practical solutions to manage your research data and make your research output more FAIR.