… to help other researchers understand your data
Metadata are the description and documentation of data.
They describe the content and context of your data files. For example, title, date, and author are elements of metadata.
Applying metadata keeps your data organized, provides context and attribution, and prepares data for storage, retrieval, sharing, and interoperability. (Learn more about metadata here.)
Sample metadata elements
How to apply metadata - three options
At the very least, save metadata as a "readme.txt" file and store with your data. This .txt file might reference a published article that describes the data.
When you're loading data into an archive or repository for storage, there may be a form that you complete to assign required metadata elements. For example, when you deposit genetic sequence data into GenBank, there are certain metadata elements to use as outlined here.
"Markup" the dataset with metadata. This is the activity of annotating your data with metadata elements. A popular type of metadata markup is XML (here is a tutorial on XML). Here is an example of how metadata markup looks:
<temperature>0</temperature> indicates a temperature data point
<title>Effect of salt on ice cream production efficiency</title> indicates the title of the data file
... to describe your data sufficiently
Metadata standards outline the requirements and procedures for describing and documenting your data. Subject-specific metadata standards are available (examples). Search online for a standard in your field.
Tip: Review metadata standards at the beginning of a project. This can help you record the appropriate details when collecting data.