Listed below are some links information about suggested data standards for making research data more universally findable, searchable, and citable.
Metadata is, at its simplest, data about data. It usually includes information about the content, context, and/or accessibility of a data set. Descriptive metadata may be a required consideration in data management plans and is vital in making published data sets more findable, accessible, interoperable, and reproducable (FAIR).
Metadata can exist in multiple formats, including as a separate text or HTML document that accompanies a data set, an XML document linked to the data files, or as information embedded in an XML data file. (XML is often used for metadata records because it can be easily integrated into many different systems.)
Various metadata standards specify what pieces of information to include and how to express them when describing a data set. Each metadata standard is composed of various elements or fields, individual pieces of information that facilitate searching similar items through shared terminology and construction. There are three main types of metadata elements:
Some examples of metadata standards are linked below, along with a description of whether they are best used within a specific discipline or across many subject areas.
Preparing Your Metadata
At the dataset level, good metadata includes information about:
This information may be contained in a separate document that accompanies the data files.
At the individual data level, good metadata includes information about:
This information may be embedded within a dataset itself or contained within a separate document that accompanies the data files.