What is metadata and documentation?
Why should I document my data?
What documentation do I need to make?
How do I create useful documentation?
Who can help me with documentation at the University of Glasgow?
Metadata is data about data. It's part of broader contextual information or 'documentation' that accompanies data to ensure it can be found and understood over time.
The information you choose to record can range from a detailed description of the data to explanatory material about why the data was created and how it has been used.
Good documentation ensures your data can be:
- Searched for and retrieved;
- Understood now and in the future;
- Properly interpreted, as relevant context is available.
There are various pieces of information that it is useful to record. Ask yourself, “What information would I need to understand and use this data in twenty years?”
You may wish to include:
- Some basic description: title, date, creator, format, subject, rights, access info;
- A list of variable / field names, coverage and their values;
- An explanation of codes, classification schema, abbreviations;
- Details about how the data were created, analysed, anonymised etc;
- Information about the project and data creators;
- Tips on usage, e.g. exceptions, quirks, questionable results.
MIT Libraries has guidelines for describing data which suggest ten elements to include.
Documentation is best created alongside the data, as it is easier to capture it then, rather than trying to remember things at a later date. Decide at the outset what you want to record and build this into your data creation processes. There are a number of ways you can add documentation to your data.
Make sure there are strong links between your data and the associated documentation
- Include information within the data or document itself, e.g. in the document properties function of a file or the file header;
- Keep a database of metadata with links to files;
- Provide standardised metadata descriptions for your data, e.g. data centre entries or bibliographic records;
- Store a readme.txt file alongside the data which provides basic explanatory details;
- Record relevant context in lab notebooks or associated papers and reports;
- Link to websites or web pages which explain the context of the research.
If you want to share your data, use descriptive standards such as the Dublin Core Metadata Initiative (DCMI) or the Data Documentation Initiative (DDI). These are used by archives and data centres so their collections can interact with each other.
UK Data Archive Documenting your data [WEB, c. 5 pages]
A detailed introduction to the different levels of documentation which can be used with practical examples.
MIT Libraries Documentation and metadata [WEB, c. 2 pages]
A short explanation followed by a useful list of what documentation should be included.
The University's Research Data Management Service can advise on documentation and relevant standards for your field.