Overview

A microformat is a simple, community-defined way to express structured data inside ordinary HTML so that applications can find and reuse the information. Rather than inventing a new file format or data block, microformats rely on existing HTML elements and attributes to annotate pieces of content such as names, contact details, dates, locations, and ratings. The goal is to make human-readable pages also conveniently machine-readable.

Structure and characteristics

Microformats typically use conventional HTML features—class names, rel attributes and element nesting—to signal the meaning of content. By following agreed class name patterns, an author can mark up a postal address, an event, a review or a geographic point in a way that small parsers can understand. Key points include:

  • Reuse of plain HTML so pages remain valid and readable in browsers.
  • Predictable class and attribute names that indicate semantics.
  • Compatibility with web crawlers and lightweight tools that extract structured snippets.

Common types and examples

Several microformat varieties have become familiar through use on the web. Examples include formats for people and organizations (contact cards), events (dates and locations), and reviews or ratings. Authors encode these items inline within normal page content so the same text serves both people and programs. Implementations range from simple copy-paste extractors to browser extensions and server-side scrapers that recognize these patterns.

History and development

Microformats emerged as a grassroots response to the need for small-scale semantic markup that wouldn’t require heavy tooling or large vocabularies. Early proposals emphasized pragmatic reuse of existing HTML rather than inventing a parallel syntax. Over time the approach evolved alongside other semantic web techniques; its community refined conventions and documented common patterns so parsers could be developed independently.

Uses, benefits and limitations

Microformats make it simpler for search engines, personal applications and browser tools to extract contact info, event details, or locations without bespoke scraping logic. Because the annotations are visible in the source, the content stays human-friendly and remains editable with ordinary web tools. Limitations include less expressiveness compared with larger semantic frameworks and the need for consensus on class names. For broader interoperability and richer graph data, alternatives such as RDFa or JSON-LD are often used in parallel.

Further resources

For technical references and community guidance, see the underlying HTML and XML specifications or resources maintained by implementers. Examples and parser libraries help demonstrate patterns and give practical extraction code. Learn more about markup approaches in general with the HTML and XML documentation, community notes at community resources, and tools or parsers listed at developer pages.