To ensure that your research data is understandable to all parties (including external partners and/or new team members), document your research data description. If you have created a comprehensive table in section 1.1, you can refer to the information therein.
Documentation may include:
- Readme files
- Field and laboratory journals
- Data logs
- Code spreadsheets
- Notes
- Descriptive information generated by analysis software, etc.
In section 3 of the data management plan, it's beneficial to mention:
- How you produce descriptive information about the research data throughout the project.
- At its simplest: each dataset includes a set-specific readme file describing the features of that dataset.
- Do you use any specific metadata standard for organising metadata?
- Particularly if you plan to archive the research data in a repository at the end of the project and this repository utilises a specific metadata standard for data description, it's worth mentioning.
- Do the devices and tools you use produce standardised metadata?
For more information on data description and metadata, see Finnish Social Science Data Archive guidelines.
If describing your documentation and metadata procedures is challenging for you, consider the following example sentences that you can modify with your own details.
Example sentences:
- Whenever someone saves data on the project's shared network storage space, that individual must also update and maintain the following documentation:
- The root directory of the storage as well as every sub-folder should contain a README.txt file.
- Each README.txt file outlines the current naming conventions and purpose of all folders and files at that level of storage organization.
- Any additions, deletions, or changes to naming conventions or purposes are promptly updated in the README.txt file.
