Metadata

What are Metadata?

Metadata plays an important role in data management and use. By using metadata, companies can better organize, find, understand, and utilize their data. There are different types of metadata that serve different purposes.

Metadata types

• Descriptive metadata: This metadata describes the content of the data, such as the title, author, date, and summary.
• Technical metadata: This metadata describes the technical structure and format of the data, such as file size, file type, and compression algorithm.
• Administrative metadata: This metadata describes how the data is managed, such as the owner, access rights, and storage location.
• Statistical metadata: This metadata describes the statistical properties of the data, such as the mean, the standard deviation, and the number of data sets.

Metadata examples

• The cover photo of an article: The cover image is a type of metadata that visually describes the content of the article.
• The GPS data of a photo: The GPS data is a type of metadata that describes the location where the photo was taken.
• The file properties of a music file: The file properties are a type of metadata that contain information about the music file, such as the song, artist, album, and duration.

Benefits of Metadata

• Improved discoverability: Metadata can help you find data faster and easier.
• Improved accessibility: Metadata can help make data more accessible to various users and systems.
• Improved usage: Metadata can help us better understand and use data.
• Improved management: Metadata can help you manage data more efficiently.

Metadata standards

There are various metadata standards that govern the definition and use of metadata. The most common metadata standards include:

• Dublin Core (DC): DC is a simple and widely used metadata standard that is often used to describe web resources.
• Resource Description Framework (RDF): RDF is a more complex metadata standard that can be used to describe relationships between data.
• Extensible Markup Language (XML): XML is a tagging language that is often used to store metadata in a structured form.

Metadata in the Data Catalog

This information includes metadata associated with the data itself, data sources, data users, and data usage types.

• Data discovery: Metadata in Data Catalog enable users to search for and find relevant data.
• Data understanding: Metadata in Data Catalog help users understand the meaning and context of data
• Data usage: Metadata in Data Catalog make it easy to use data for analysis, reporting, and other purposes.
• Data quality: Metadata in Data Catalog can help improve data quality, for example by identifying errors and inconsistencies in the data.
• Data Governance: Metadata in Data Catalog support the Data Governance by providing information about how to use and access data.

Note: This glossary was created and maintained with the support of AI technologies such as Gemini and ChatGPT.