Not one system is going to put structure in your data, because it doesn't understand your research. The structure comes from you. | Patrick Vandewalle
Time invested in thinking about organising research data and the associated data and project documentation will pay off in the long term. It makes the data easier to find and understand. This section contains a number of tips on how to keep it structured.
Findable and understandable data
If you want research data to be findable and easy to interpret, then it is important to store the data in a structured, consistent manner and to provide it with the necessary data documentation and metadata. The folder structure in which the data ends up must speak for itself, as must the file names used for the data files (see box).
It is also possible for a researcher to use a system that already has a certain amount of structure in it. For example, a division into folders already exists. And when you upload data, you are asked for basic metadata, such as the author, date, and so on. Think of a virtual research environment, a tool such as Dataverse (DANS, n.d.) or some electronic lab journals.
The main challenge to data sharing is organising data in a presentable and useful way. | Stuart, 2018
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