Data Management Toolkit @ UNH

Data must be documented to be used properly by you, your colleagues, and other researchers in the future.  Data documentation (also known as metadata) enables one to understand your data in detail and will enable other researchers to find, use and properly cite your data.

It is critical to begin to document your data at the very beginning of your research project, even before data collection begins; doing so will make data documentation easier and reduce the likelihood that you will forget aspects of your data later in the research project.

Following are some general aspects to document about your project and data, regardless of your discipline.  At minimum, store this documentation in a readme.txt file or the equivalent, together with the data. One can also reference a published article which may contain this and additional information.

Researchers can choose among various metadata standards, often tailored to a particular file format or discipline.  One such standard is DDI (the Data Documentation Initiative), designed to document numeric data files.

Metadata Standards provide specific data fields or elements to be used in describing data for a particular use. Some research fields have predefined metadata standards, such as those listed below.

For more discipline-specific metadata standards check out the RDA Metadata Directory.  

For more guidance on data documentation and metadata, check out these guides:

• Documenting Your Data from the UK Data Archive
• Data Documentation and Metadata from the University of Arizona Libraries
• Documentation & metadata from MIT Libraries