Structured Data & Semantic Web

구조화 데이터

Structured Data is a metadata layer that explicitly describes content using a standardized vocabulary, such as Schema.org, alongside the text that people read. Rather than inferring details from prose, a search engine can read explicit statements that a page describes a product priced at KRW 89,000 with a rating of 4.7. Its relevance also extends to generative AI services such as ChatGPT and Perplexity, where explicit information about entities can support the interpretation of web content; markup alone does not guarantee training use or citation.

Business applications and impact#

Moves beyond text matching to describe entities and their relationships in a Knowledge Graph, while supporting eligibility for rich search results.

Implementation guidance and considerations#

Follow Schema.org guidance and ensure the markup accurately reflects the content visible on the page.

Code example#

<!-- 구조화 데이터의 가장 기본 골격 예시 -->
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "WebPage",
  "name": "구조화 데이터 완벽 가이드",
  "description": "Schema.org 어휘를 활용해 콘텐츠 의미를 검색엔진에 전달하는 방법을 설명합니다."
}
</script>

Snippet

스니펫

The brief descriptive preview shown beneath a search-result title and URL.

Perplexity AI

Perplexity

An AI search service that combines live web retrieval with LLM-generated summaries and explicit source footnotes for each answer.

Entity

엔티티

An independently identifiable concept, such as a person, place, organization or object, with a distinct definition.

Knowledge Graph

지식 그래프

A knowledge database that organizes entities and their relationships as a network of nodes and edges.

FAQPage Schema

FAQ 구조화 데이터

Markup that describes a set of frequently asked questions and answers, eligible in supported cases for expanded search presentations.

Google Discover

Google Discover

Google's personalized content feed, which recommends material based on interests and activity without requiring a search query.