Documenting the data collection process is an important part of good research data management practices. It allows for sharing and reuse of data by others, enables the replication of the research and serves as a reference for the research team to verify findings and compare the research project with others. Depending on the data collected and the research project, different types of documentation can be useful.
Because documenting data has many benefits, DMPs include questions about the practice such as:
Consider including information that aids in reproducibility with information about file types,software accessibility and by
Data documentation explains how data were created or digitized, what data mean, what their content and structure are and any data manipulations that may have taken place. Documenting data should be considered best practice when creating, organising and managing data and is important for data preservation. Whenever data are used sufficient contextual information is required to make sense of that data.
Good data documentation includes information on:
At the data-level, documentation may include:
Data-level descriptions can be embedded within a data file itself. Many data analysis software packages have facilities for data annotation and description, as variable attributes (labels, codes, data type, missing values), data type definitions, table relationships, etc.
Other documentation may be contained in publications, final reports, working papers and lab books or created as a data collection user guide.
Veerle Van den Eynden, Louise Corti, Matthew Woollard, Libby Bishop and Laurence Horton. 2011. Managing and Sharing Data: Best Practices for Researchers. 3rd Edition. U.K Data Archive. Accessed March 6th, 2021. https://ukdataservice.ac.uk/media/622417/managingsharing.pdf
Approaches to Documentation can include: