Good documentation enhances the quality of the data and your results by making findings verifiable. Documentation is usually noted continuously as an integral part of the research method.
Unlike metadata, it is not necessary for documentation to follow a standard. However, there are certain important aspects that should be included. Documentation should be written throughout the work with the data and summarized, and then included with the archived data as a ReadMe file.
During the implementation phase
Good routines for documenting the processes of data collection, processing, and analysis are part of the methodology and good research practice. How you choose to document the work will largely depend on the field.
Examples of tools you can use for documentation include:
- A plain text document
- Notebook tools like OneNote (included in Microsoft 365)
- Electronic lab notebooks (ELN). UiO has an agreement with eLabJournal
- Documentation on paper (field diaries, etc.) that is photographed/digitized and included with digital data
Project closure and archiving phase
When data is to be archived, the documentation should be included in a ReadMe file. A ReadMe file is a detailed guide to the dataset that enables other researchers to understand and reuse the data you archive.
It is important that the documentation at the time of archiving contains general information about the project, licensing, reuse information, an overview of the files, methodological information, and data-specific information about the content of the various files.
A complete file overview is crucial for both archiving and reuse to ensure the dataset is complete. Methodological information is often drawn from articles related to the dataset, but there is also room for more details in the ReadMe file. Much of the documentation needed for archiving is data-specific information that is gathered from notebooks written during the research. It is also common to include documentation from the implementation phase in its entirety and refer to details in this in the ReadMe file.
Read more about data archiving.
ReadMe template
To create a good ReadMe file tailored for data archiving, it is useful to use a template. DataverseNO has a detailed and updated ReadMe file template for datasets and another template tailored for archiving software or code.
ReadMe files should be saved in plain text format (.txt) with Unicode UTF-8 encoding and named "00_ReadMe.txt" so that it sorts to the top in a file structure.