{
  "id": 3566,
  "url": "https://arxiv.org/abs/2605.28787v1",
  "title": "Do Agents Need Semantic Metadata? A Comparative Study in Agentic Data Retrieval",
  "summary": "In the era of autonomous agents, machine-actionable data is critical for data-driven workflows. For more than a decade, semantic metadata like schema.org has anchored the FAIR principles (Findable, Accessible, Interoperable, and Reusable) for machine-actionable data and enabled discovery tools like Google Dataset Search. However, the rise of Large Language Models (LLMs) capable of navigating the unstructured web raises a fundamental question: Is semantic metadata still necessary for agentic data",
  "authors": "Shiyu Chen, Tarfah Alrashed, Alon Halevy, Natasha Noy",
  "category": "research",
  "topics": "agents-autonomy",
  "orgs": "google",
  "regions": null,
  "published_at": "2026-05-27T17:46:43.000Z",
  "fetched_at": "2026-07-14T16:30:23.243Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/3566",
  "original_url": "https://arxiv.org/abs/2605.28787v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}