{
  "id": 625101,
  "title": "Workflow Cards: Structured Summaries of Workflow Executions Using Provenance Data",
  "url": "https://urgent.news/2026/08/11/workflow-cards-structured-summaries-of-workflow-executions-using",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-11T15:02:11.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2608.11022v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Model Cards and Data Cards have demonstrated the value of structured, human-readable documentation for machine learning artifacts, capturing their context, parameters, limitations, and intended use. However, these practices remain focused on static artifacts (the datasets and trained models themselves) while overlooking the workflow executions that produce, transform, and evaluate them. Such…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}