Often described as data about data, metadata are simply descriptions that help you to record information and make sense of your data - especially when you've stepped away from it for a while. Metadata can also help you find your data among all your other files. If you decide to publicly share your data, metadata can help others find your data and understand the correct context for your data so they can use it appropriately. For a quick overview of metadata, check out the video What are Metadata (and why are they so important)? from the ICPSR.
Common metadata elements include:
A metadata standard is an agreed on set of metadata needed for a type of data and will often define rules for those metadata. Metadata standards are discipline-specific and can define, for a particular type of experiment or field of study:
A standard can involve any of all of these components. There is no standard for standards. Fairsharing.org is a good resource for finding metadata standards
We recommend you create and use data dictionaries and README files whenever possible. These can help you practice proper data documentation and ensure your data is usable in the future.
A data dictionary is "a collection of names, definitions, and attributes about data elements that are being used or captured in a database, information system, or part of a research project" (University of California, Merced Library).
A README file "provides information about a data file and is intended to help ensure that the data can be correctly interpreted, by yourself at a later date or by others when sharing or publishing data" (Cornell university Research Data Management Service Group).
