In this guide some specific examples and tips are given on how to document and describe your data with Excel.
Documentation (human readable) and more specifically metadata (standardised, fixed fields that can take a value, computer readable) both provide information about the data at hand. Describing your data is important. Systematically described research data is the key to making your data findable, understandable and reusable. Overall data quality improves with clear and detailed documentation and metadata.
2. Building metadata sheets with Excel
There are tools to help you add metadata to your research project. Excel is a simple way to create metadata schemes with controlled vocabulary drop-down lists. In practice, you can put metadata fields in columns, and have one row of values or descriptions per measurement.
It is not uncommon for a metadata sheet to hold thirty or more metadata fields to describe your data. As an added benefit, you can easily select specific measurements based on the information noted down in the metadata sheet. If applicable include a field that takes the name of the file that actually holds the measurement data and other files that give detailed information (i.e. log files or scripts of analyses done on your samples, or the exact protocol used to generate the sample). The top row with the metadata fields can be made write protected and values can hold controlled vocabulary in drop-down lists or controlled format such as a date format.
Consider having one generic metadata sheet on your overall study and one for describing the individual measurements.