Metadata is information about your data.
It is often presented in the form of descriptions (but also exists in a variety of other forms).
Good quality research metadata is important: it enables data to be sought, discovered and reused.
View this video to learn more about how metadata works.
If properly composed, metadata enhances discovery by search engines, and provides a greater depth of information to the users of the data.
Within the research context, there are two types of metadata:
Project-level metadata: a broad, descriptive form of metadata that names various elements of the research, such as dates, project details, and geographic locations. It tends to provide details and descriptions that are contextual to the project.
Dataset-level metadata: this form of metadata provides information about the data itself.
Source: Research Data Services, Oregon State University: https://guides.library.oregonstate.edu/research-data-services/data-management-metadata
The name(s) of the data’s creator
The research-relevance of the data
The purpose of the data
The content of the data file
The filename in which the data sits
Details from when the data was generated
The place and date that the data was generated
The purpose underpinning why the data was generated
The process for generating the data
The terms under which the data may be reused
Collectively, this type of descriptive information (data about data) is referred to as "metadata".
Source: Adapted from ANDS https://www.ands.org.au/working-with-data/metadata
Document and describe your data
Present an accurate record of your research project's data files through a carefully prepared and created data description document. This will serve as both a record of the data that has already been collected; and as a resource for those who may wish to employ the data in later research projects.
Typical data characteristics that feature in a data description document include:
Methods of data capture
Basic statistics derived from the key attributes
Data description documents vary in size and content. At a minimum, it's recommended that you include:
A list of each file in the dataset
Briefly described contents of the data
Software used to create the data
Research data that is well-documented, described and organised facilitates easy retrieval for those who wish to locate and re-use the data.
The approach that you take towards data description is shaped by numerous considerations and choices:
Ask these questions of your data. Your responses will help you to identify which elements to describe.
A Readme file contains information about a data file. Its purpose is to describe the data to the extent that correct interpretations of it will be maintained over a period of time.
For instruction, details, templates and and other related resources consult Cornell University's Guide to writing ReadMe style metadata