To make your data easy to understand and analyze through your research lifecycle and in the long term, it is considered good practice to document your data. Data documentation is part of the data curation process.
1. Ensure that all data collected and generated through your research lifecycle is documented.
2. At the beginning of your research, check what kind of documentation is available or necessary, and identify needed documentations which will enable data preservation and reuse in the future.
The various kinds of documentation may include:
Please also note that research data can be documented at various levels: Project level, File or database level and Variable or item level.
3. During your research, document all research data formats utilized by your project.
Research data comes in many varied formats, such as:
4. Keep the wide variety of materials that are generated or collected in your research.
Research data (traditional and electronic research) may include all of the following:
The following research records may also be important to manage during and beyond the life of a project:
5. Utilize software to create embedded documentation for the data (if applicable), and make separate supporting documentation (e.g. readme text files) to describe the list of files and documentations in a folder. Further, discuss with relevant personnel on how data can be archived and shared in a data center, or a library digital repository for others to search, locate and reuse.
Please refer to Data Management Plan & Metadata, common metadata standards and domain specific metadata standards for more metadata information.
Source: The University of Edinburgh: Information Services: How to manage research data: Defining research data.
Please also refer to Data documentation & metadata and Data Documentation, Analysis & Statistical Software for more information on dataset metadata and its related services at UCF Libraries.