Once you have set up your file organization, storage, and file naming conventions, it’s a good idea to think about how you will document your project. Our rule of thumb is: If it happened during your project, chances are you need to document it!
It’s really useful when, let’s say, you are trying to go back to some data from 6 months ago and you forget what it is, or why you named a variable a certain way, or you forget when it was collected. By keeping documentation such as README files (which give a high-level overview of files in a given project and how they can be used) and codebooks (files that document variables and their meaning).
We recommend that you document your work with the following files at least:
Metadata is structured information describing the characteristics of a resource; for example, the dates associated with a dataset or the title and author of a book.
Discovery (i.e. the findability and citability) of your data
Re-use of other researchers of your data in pursuit of knowledge
Long-term preservation of resources.
In order for your data to be used properly by you, your colleagues, and other researchers in the future, they must be documented. Planning what metadata will be captured and how this data will be structured should occur at the beginning of a research project, before data collection begins. Doing so will make automation of metadata creation easier and reduce the need for time-consuming metadata capture or restructuring later in the lifecycle of the research project.