Thank you for your question Frank. I have found that having everything in a cloud save makes it easier to access anywhere. When I was doing my dissertation i made sure to label every data set with a clear and methodical name to make the analysis part easier and quicker.

A quick Google search came up with several articles discussing data management efficiency. Some suggestions that popped up over and over include maintaining a standardized file naming system, using metadata in a thoughtful way (including information like the author, a description of the data set, and why the data is valuable), having proper storage (and a backup method of storage), creating multiple levels of documentation, and making sure data and privacy is secure. Consistency is key to the process. It might take a bit of work to backlog current data, but it's worthwhile. Hope this helps!

Thanks for your reply, Lize! But let me beg the question : how did you do this labeling in practice, and how could it be made easier?

Thank you for your efforts Lara, but I meant the question really personal. If one looks there is plenty of advice about data management, and it all makes a lot of sense. But if you follow all that, you'll be quite busy just reading about it and when you start following all the advice, you will be quite busy before you even start collecting any data. Who does that? Nobody, I guess. Most people just start collecting data. So what I hope to find out, is how people do that in practice, and how could that be made easier?