{
  "abstract": "Department of Energy programs increasingly require that experimental data be not only preserved but usable by artificial intelligence (AI) systems, yet no accepted standard defines when a dataset is AI-ready. We argue that data must be FAIR (Findable, Accessible, Interoperable, Reusable) before they can be AI-ready, and that AI readiness is a distinct property requiring its own assessment. Using the GlueX experiment in Hall D at Jefferson Lab as a pilot, we map the data ecosystem, assess it against FAIR, and define an AI-readiness framework whose criteria are backed by deterministic metrics. We also evaluate existing validation software to separate what can be assessed with off-the-shelf tools from what requires domain-specific development. The assessment yields a set of findings, each paired with a recommendation, some of which are already in production or prototyped and others planned as next steps.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2609.34987",
  "author_total": 5,
  "authors": [
    {
      "name": "Anil Panta"
    },
    {
      "name": "Brad Sawatzky"
    },
    {
      "name": "Casey Morean"
    },
    {
      "name": "Dmitry Romanov"
    },
    {
      "name": "Douglas Higinbotham"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/64fvtprmshd2y.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2609.34987",
  "fulltext_url": null,
  "id": "64fvtprmshd2y",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2609.34987",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "nucl-ex"
    ],
    [
      "openalex",
      "1710|Research Data Management Practices"
    ]
  ],
  "openalex": "W7214777333",
  "pdf_url": "https://arxiv.org/pdf/2609.34987",
  "pmcid": null,
  "pmid": null,
  "published": "2026-09-28",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/64fvtprmshd2y.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:25:12Z",
      "native_id": "2609.34987",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2609.34987"
    }
  ],
  "subjects": [
    {
      "field": "physics",
      "origin": "arxiv:nucl-ex",
      "subfield": "nuclear"
    }
  ],
  "title": "Toward FAIR and AI-Ready Data: An Assessment of the GlueX Experiment's Data Ecosystem at Jefferson Lab",
  "title_text": "Toward FAIR and AI-Ready Data: An Assessment of the GlueX Experiment's Data Ecosystem at Jefferson Lab",
  "type": "preprint",
  "updated_at": "2026-10-30T12:25:12Z",
  "url": "https://research.draconitic.com/paper/64fvtprmshd2y",
  "venue": "arXiv",
  "versions": []
}