paperlab-reference-dataset-curation

name	paperlab_reference_dataset_curation
description	Curate reference datasets for PaperLab validation, including source tracing, unit normalization, uncertainty notes, license status, and citation mapping.

PaperLab Reference Dataset Curation

When to Use

USE WHEN: extracting literature or benchmark data into files that support paper claims, book examples, or regression baselines.

Dataset Manifest Fields

{
  "dataset_id": "co2_water_solubility_2024",
  "source_citation_key": "Author2024",
  "source_type": "paper_table",
  "extraction_method": "manual_table_transcription",
  "original_units": {"temperature": "C", "pressure": "MPa"},
  "normalized_units": {"temperature": "K", "pressure": "bara"},
  "uncertainty": "reported standard deviation where available",
  "license_or_use_note": "cite only; do not redistribute full source text",
  "files": ["reference_data/co2_water_solubility_2024.csv"]
}

Workflow

1. Identify source and citation key.
2. Extract only the data needed for validation.
3. Preserve original units and normalize into a separate column or metadata field.
4. Add uncertainty and data-quality notes.
5. Link each dataset to hypotheses, figures, and claims.

Pass Criteria

• Every numeric column has a unit.
• Every dataset has a citation and extraction method.
• Public outputs avoid restricted source text.

Safety Rules

• Do not redistribute copyrighted tables wholesale when a minimal derived dataset is enough.
• Never silently round or smooth data used for validation.
• Mark transcription uncertainty when data was read from figures.