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Objective <p>Metadata standardization in collaborative biomedical research must balance interoperability with domain-specific detail. We describe a parent-template approach in which a baseline schema from the nephrology-focused CRC 1453 NephGen was adapted for the tumor-immunology CRC OncoEscape and the perinatal-immunology CRC Pilot.</p> Results <p>The derivation process produced three structurally compatible yet vocabulary-divergent schemas. Pilot required the highest granularity (324 levels), followed by NephGen (287) and OncoEscape (283). Vocabulary reuse from the NephGen baseline was limited: 134 of 283 OncoEscape levels (47%) and 113 of 324 Pilot levels (35%) were retained unchanged. The main adaptations were not only expanded level lists, such as cell lines and mouse lines, but also new CRC-specific query dimensions, including “Oncogenes” in OncoEscape and “Timeline” in Pilot. In the context of AI-assisted extraction, we use the term <i>instruction set</i> to denote a schema that specifies target fields, expected granularity, example values, and validation resources for each metadata dimension, rather than a simple drop-down form or a free-text prompt template.</p>

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From manual entry to machine precision: challenges and evolution of metadata schema development in collaborative research centers

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月6日

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  • Felix Engel,
  • Claudia Giuliani,
  • Manuel Watter,
  • Aref Kalantari,
  • Karin Schuller,
  • Harald Binder,
  • Klaus Kaier

摘要

Objective

Metadata standardization in collaborative biomedical research must balance interoperability with domain-specific detail. We describe a parent-template approach in which a baseline schema from the nephrology-focused CRC 1453 NephGen was adapted for the tumor-immunology CRC OncoEscape and the perinatal-immunology CRC Pilot.

Results

The derivation process produced three structurally compatible yet vocabulary-divergent schemas. Pilot required the highest granularity (324 levels), followed by NephGen (287) and OncoEscape (283). Vocabulary reuse from the NephGen baseline was limited: 134 of 283 OncoEscape levels (47%) and 113 of 324 Pilot levels (35%) were retained unchanged. The main adaptations were not only expanded level lists, such as cell lines and mouse lines, but also new CRC-specific query dimensions, including “Oncogenes” in OncoEscape and “Timeline” in Pilot. In the context of AI-assisted extraction, we use the term instruction set to denote a schema that specifies target fields, expected granularity, example values, and validation resources for each metadata dimension, rather than a simple drop-down form or a free-text prompt template.