To ensure that you understand your own data and that others may find, use and properly cite your data, it helps to add documentation and metadata (data about data) to the documents and datasets you create.
The term ‘documentation’ encompasses all the information necessary to interpret, understand and use a given dataset or set of documents. On this website, we use ‘documentation’ and ‘metadata’ (data about data – usually embedded in the data files/documents themselves) interchangeably.
It is a good practice to begin to document your data at the very beginning of your research project and continue to add information as the project progresses. Include procedures for documentation in your data planning.
There are a number of ways you can add documentation to your data:
Information about a file or dataset can be included within the data or document itself. For digital datasets, this means that the documentation can sit in separate files (for example text files) or be integrated into the data file(s), as a header or at specified locations in the file. Examples of embedded documentation include:
This is information in separate files that accompanies data in order to provide context, explanation, or instructions on confidentiality and data use or reuse. Examples of supporting documentation include:
Supporting documentation should be structured so that it can be used to identify and locate the data via a web browser or web-based catalog. Catalog metadata is usually structured according to an international standard and associated with the data by repositories or data centers when materials are deposited. Examples of catalog data are: