Documentation of research data, also called, metadata is an often overlooked, but critical, aspect of research data management. It’s important to note that this type of metadata is not as simple as basic system metadata familiar to computer scientists such as file sizes, ownership, etc. When we are talking in a data management context, metadata provides several descriptive elements that inform viewers of the data of who collected it, how it was collected, where and when it was collected, processing methods, and much more. Not only is this a requirement for data publishing, it is very useful for collaboration between other researchers and can serve as a tool to ensure consistency throughout the other steps taken in the Research Data Management Life-cycle.

Common Metadata Standards

There are several standards available depending on discipline that provide the advantages of ensuring you have a complete, standard set of information about each part of your data and enable your dataset to be organized with other datasets, a few examples are:

• FGDC (Federal Geographic Data Committee)

• DDI (Data Documentation Initiative)

• Dublin Core

• Darwin Core

• ABCD (Access to Biological Collections Data)

• AVMS (Astronomy Visualization Metadata Standard)

• CSDGM (Content Standard for Digital Geospatial Metadata)

While these standards exist and can help aid researchers in recording complete metadata, they are not universally required to be used. A best practice is to record the information that works for you and your collaborators.

Common Metadata Fields

While each of the standards listed above are each unique and recommend recording different information, there are several commonalities.

Straight Code - No context

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