Data, no matter how organized or well formed is useless without context. If you are not already documenting your spreadsheets you should start NOW. At minimum, documentation needs to provide information that will give context to the data so that others can understand it. Note that project size and complexity will impact what needs to be documented.
Below are summaries of the two most common ways to document spreadsheet data.
Codebooks are table(s) that explain :
An template for creating your own codebook is available online.
|Q24||Question 24: do you own a pet?||Numeric||1 = yes; 0 = no; blank = NULL|
|Q25||Question 25: Do you like cats?||Numeric||1 = yes; 0 = no; blank = NULL|
|Q25.1||Question 25 part 1: Why?||None||free text|
A plain-text document that explains the who, what, when, where, and how of the data. A README often contains author information, details on methodology, software and equipment, as well as list of files and what each contains.
A README template can be found here. Enter in your information and delete sections that are not applicable to your data.
Depending on your data you may need to create both a README and a codebook. An example that merges both of these can be found in the following dataset, look for the file labeled "DataDictionary.pdf", or in the README example linked above.
Obrycki, John F. (2019): Land Use and Cropping Recommendations For Various Soil Types in Iowa, 1937-1938. Dataset. https://doi.org/10.25380/iastate.6333104.
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