What is metadata?

When you collect and store data, it is important that you, but also others who may later access your data, know all of the information that is necessary to understand what the data is all about. This means you should document the data structure by adding what is known as “metadata”.

Metadata is a set of data provides all the necessary information needed to interpret the given data. For instance, when you have a table, the metadata will describe the meaning of each of the columns in the data table. Also, the metadata will contain information on when the data is collected where it was collected and any special information that is needed to backtrack the origin of the data.

According to the information included, metadata can be divided into several distinct categories: Descriptive, Administrative, Technical, Legal, Structural, Geographical, Temporal and Preservative. Additional types of metadata are related to specific research domains such as: experimental, statistical, analytical, sample metadata, etc. 

Metadata or Data Documentation?

While metadata and data documentation can sometimes be used interchangeably, we are making the following distinction for the purposes of this guide: we consider metadata as structured, machine readable and interoperable information about your data, and documentation as mostly human-readable information about a project and its data. Both are, of course, important for future users to be able to understand and use your data.