This page describes some of your many options for documentation. Pick the documentation structures that work best for you and your data.
Improving your documentation often means improving your note taking. Good notes are:
Templates add structure to handwritten notes. This ensures you record all of the necessary details and can help you search through your notes later.
To create a template, come up with a list of details to record every time you acquire a particular type of data. Use this list as a reference or a worksheet. See this post for further information.
README.txt's document digital files and add context whenever clarity is required. They are useful for:
Data dictionaries are particularly useful for spreadsheet data. Data dictionaries describe:
Use a data dictionary when you share data, when you expect to reuse the data, or have a particularly large and complex dataset.
Click here to learn more about on data dictionaries or watch this video on data dictionaries.
Methods are important documentation that you need to remember to keep with your data. Methods include:
Metadata, or highlight structured computable documentation, is useful for:
If you need a metadata schema for your discipline, refer to this list from the UK's Digital Curation Center.
The Data Services librarian position is currently vacant. You may direct your questions to the Scholarly Communication team at ScholarlyCommunicationTeam-Group@uwm.edu
The content of this guide is available under a CC-BY license with attribution to UWM Libraries.