To improve the processability of web sites, formal knowledge representation standards are required, that can be used not only to annotate markup elements for simple machine-readable data, but also to express complex statements and relationships in a machine-processable manner. After understanding the structure of these statements and their serialization in RDF, the structured data can be efficiently modelled as well as annotated in the markup, or written in separate, machine-readable metadata files. The three most common machine-readable annotations that are recognized and processed by search engines are RDFa, HTML5 Microdata, and JSON-LD of which HTML5 Microdata is the recommended format. The machine-readable annotations extend the core (X)HTML markup with additional elements and attributes through external vocabularies that contain the terminology and properties of a knowledge representation domain, as well as the relationship between the properties in a machine-readable form. Web ontologies can be used for searching, querying, indexing, and agent or service metadata management, or to improve application and database interoperability. Web ontologies are especially useful for knowledge-intensive applications, where text extraction, decision support, or resource planning are common tasks, as well as in knowledge repositories used for knowledge acquisition. The schemas defining the most common concepts of life and the relationships between them are collected by semantic knowledge bases. These knowledge organization schemas are the de facto standards used by machine-readable annotations serialized in RDFa, HTML5 Microdata, or JSON-LD, as well as in RDF files of Linked Open Data datasets.