{
  "id": 18432,
  "url": "https://arxiv.org/abs/2608.10363v1",
  "title": "Nutrition Data Infrastructure for the AI Era: Operationalizing FAIR for Agent-Mediated Research",
  "summary": "AI agents can accelerate nutrition research, but their analyses inherit the identity, semantic, and release ambiguities of the underlying data. We present Nutrition Data Service (NDS), source-preserving infrastructure that operationalizes FAIR for automated use: description resolution makes release-specific records findable; typed crosswalks connect independently released resources; machine-readable interfaces expose versioned sources and crosswalks, making analyses by AI agents replayable and a",
  "authors": "Lin Liao, Peng Li",
  "category": "research",
  "topics": "agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-11T01:42:12.000Z",
  "fetched_at": "2026-08-12T05:10:43.828Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/18432",
  "original_url": "https://arxiv.org/abs/2608.10363v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}