What is metadata?
Metadata is "data about data" that describes, categorizes, and manages digital assets. In the context of search engines, metadata is used to accurately understand, index, and rank content in search results, aiming to make each result as relevant as possible.
Why does metadata matter in AI search engines?
Metadata matters in AI search engines for several reasons:
- It helps organize, group, and navigate an enterprise's vast amount of documents and content resources.
- It enables search engines to create relevant search result pages for users.
- It allows for better classification and retrieval of knowledge articles.
- It supports faceted navigation in e-commerce settings.
- It improves the efficiency of workflows and reduces the risk of errors.
- It makes it easier for users to find the information they need.
Types of metadata
- Descriptive metadata: Includes information about content resources such as category, topic, author, and type of digital asset.
- Product metadata: Lists attributes and descriptions of products, including style, brand name, color, and size.
- Structural metadata: Describes the structure of database objects like indexes, tables, and columns.
- Administrative metadata: Provides information on managing a resource, including preservation details.
- Technical metadata: Describes information structure in data warehouses or business intelligence systems.
- Schematic metadata: Defines allowable relationships between elements in a data system.
