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Machine-Readable Publishing: Sitemaps, Web Feeds, and Dataset Pages for LLMs

Websites reach people and computers (like search engines and chat assistants) by being easy to find and understand. One way to help this is by using structured publishing artifacts – special files and pages that a machine can read. For example, an XML sitemap lists every page on your site so search bots can discover them all (developers.google.com). A web feed (RSS or Atom) lists recent updates so tools see new content quickly (developers.google.com). And dedicated dataset or methodology pages explain any data or methods you used, often with structured data (like schema.org markup) so systems like Google’s Dataset Search can find them (developers.google.com). In this article, we explain how to use these artifacts to improve discoverability. We will look at checking your sitemap coverage and lastmod dates, ensuring feed freshness, creating clear data/method pages, testing changes with tools, and monitoring improvements like crawl frequency and assistant citations. Finally, we offer a maintenance plan and rollout steps.

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