The preparation and implementation of a good Data Management Plan (DMP) helps to focus on different aspects of research data management (like ethical-legal or technological requiremenresources involved, FAIRness) thereby fostering potential benefits for data analysis anrepurposing. However, preparing a good DMP is often a complex task. A number of existing tools tries to simplify the preparation by automatically generating a DMP from a set of questions, but the difficulties in tailoring predefined plans to specific use cases sometimes lead to the compilation of not exhaustive documentation, especially for those who are new to this task. To alleviate these challenges we have created a guide to support the writing of the DMP, combining key contenpractical recommendations and references extracted from the most common DMP models. Wstructured the guidelines as a complement to the analysed templates and tools to stimularesearchers towards a critical exploration of the many different aspects, possibly adapting them their domain specificities. In this way, we believe that the whole project team could be encouragto consider the DMP as a travelogue to be followed over the project lifecycle and further, updating it whenever necessary. The guide is openly available on Zenodo and it is currently being validated by the researchers of the I FAIR Program – an initiative to promote and adopt best practices fresearch data management in the biomedical research community in Sardinia. The initial feedback indicates that the guide appears to be a useful tool both when creating the DMP and during revision.