Even with excellent organization structures, files and the data they contain can still be unclear, particularly if they have not been examined for long periods of time. Saving additional documentation to the folder in the form of plain text files can preserve greater context and meaning behind the dataset, providing you with an explanation when you do reuse the data. You should be documenting when you need to know in order to understand and reuse your own data later. Documenting your data means creating metadata that can be used to retrieve, reuse, and increase the longevity of your data. Metadata is often defined as "data about data". It is also known as data documentation. Metadata is used to describe and document research data.
Descriptor information might include elements such as:
- Creator
- Title
- Source
- Methodology
- Description
- Location
- Dates
- Rights
- Funder
- Subjects
- Format
- Identifier (DOI or Handle)
You may want to use a data dictionary to add context and explain tabulated data, and this may can in the form of a "Readme" file. Cornell University has developed a template for creating readme files.
Click below for a guide on on documentation:
Colectica for Excel: a Microsoft Excel plug-in to add descriptive and background information to your spreadsheets.