Data documentation is important because it helps the researcher to remember what each component exactly means and under which socio-technical conditions it was created or acquired. Also, it helps others to understand it, use it appropriately and cite it.
1- Establish a good file naming convention and follow it to name your folders and files.
2- Keep versions of the data before each alteration and document the changes that took place in each version.
3- Indicate which tools were used to generate the data or where did you get it from (provenance).
4- Include an explanation of all of the codes you used to label your data and name your files.
Other information you would want to keep are:
1- Title: give a descriptive title to your data.
2- Creator: your name if you generated it, otherwise the name of the person/institution who did.
3- Dates: date of creation and/or date of acquisition.
4- Subject: Abstract, Summary and Keywords describing the content of your dataset.
5- Funders: funding agency or person's name if available.
6- Rights: type of copyrights you want to apply to your data and the name of the rights holder.
7- Language: in which the data is available.
8- Location: the place where the data was collected: i.e. geographical location
9- Methodology: How was the data generated, including equipment or software used, experimental protocol and other things you might include in a lab notebook.
