Data handling and management
Virtual lab-book and using shared group files and resources:
Translational projects need detailed recordings of all aspects of the project and this has traditionally been maintained in a laboratory book. However newer formalised electronic records are available for this purpose. This should be transparent and have the potential for sharing. One helpful resource is labfolder.
Statistics: training and modules
Many universities have core modules for all students and all are encouraged to include statistics and also to collaborate with a statistician. The statistician should be involved in the inception of the project to guide on issue such as study design and sample size.
Data management and security
The FAIR Guiding Priniciples contain useful pointers on scientific data management and stewardship.
Each PhD student will ultimately become an independent researcher with their own PhD students and therefore should gain skills in budgeting and managing funding for their project. Have a look at this article.
This article describes four foundational principles—Findability, Accessibility, Interoperability, and Reusability—that serve to guide data producers and publishers