Data Management: Data Documentation

Data documentation ensures that your data will be understood and interpreted by any user. Data documentation should start at the beginning of a project and continue throughout.  This will make data documentation easier and make it less likely that you will forget details later. 

What's important to document?

• Context of data collection
• Data collection methodology 
• Structure and organization of data files
• Data validation and quality assurance
• The manipulation of raw data through analysis
• Data confidentiality, access, and use conditions

Data documentation will ensure that your data will be understood and interpreted by any user. It will explain how your data was created, the context of the data, the structure of the data and its contents, and any manipulations that have been applied to the data.

Data Level Documentation

• Variable names and descriptions
• Definition of codes and classification schemes
• Reasons for missing values
• Definitions of specialized terminology and acronyms
• Algorithms used to transform data
• File format and software used
   

From University of Illinois