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license: mit
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PLOS Cleaned JSONL Dataset — 50+ GB of Machine-Ready Scientific Text

This repository delivers a fully cleaned and standardized large-scale corpus extracted from the complete PLOS scientific archive, reorganized and formatted into high-quality JSONL files. All content is optimized for immediate use in modern LLM training pipelines (OpenAI, Mistral, DeepSeek, Llama, Gemma, etc.).
Total size (compressed): ~50 GB • Articles processed: hundreds of thousands • Cleaning quality: ~98–99% • Format: JSON Lines (.jsonl)

Features

Full PLOS corpus reorganized by year:
output/datasets_by_year/year_2003.jsonl → year_2025.jsonl

Train/val/test splits ready for training:
output/splits/train.jsonl, val.jsonl, test.jsonl

Grouped by journal (all PLOS branches):
Medicine, Genetics, Pathogens, Climate, Computational Biology, Digital Health, Global Public Health, ONE, Biology, Neglected Tropical Diseases, etc.
Example:
output/datasets_by_journal/PLOS_Medicine.jsonl, PLOS_Genetics.jsonl, PLoS_Biology.jsonl, PLOS_ONE.jsonl, etc.

JSONL Structure

Each line follows the same cleaned schema, ideal for training, RAG, or vector embedding:

{
  "title": "Article title",
  "abstract": "Cleaned abstract...",
  "body_text": "Full cleaned article body...",
  "journal": "PLOS Medicine",
  "year": 2018,
  "authors": ["First Author", "Second Author"],
  "doi": "10.1371/journal.pmed.xxx",
  "keywords": ["biology", "health"],
  "clean_text": "Final merged cleaned text..."
}

Cleaning Pipeline

Extraction from raw PLOS dumps

Multistage cleaning (regex, normalization, structure repair)

Removal of XML/HTML debris, broken text, figure callouts, corrupted sections

Unified schema + metadata alignment

Sorting by journal & by year

Automatic train/val/test splitting

Final QC ensuring no empty or malformed samples

Why This Dataset Matters

Massive 50+ GB scientific corpus ready for training

High-signal, peer-reviewed biomedical & scientific text

Perfect for:

biomedical/scientific LLM pretraining

SFT and supervised tasks

RAG systems & semantic search

reasoning models

dataset benchmarking

Fully stable, normalized, UTF-8 safe, consistent JSONL

License

PLOS articles are released under the PLOS Open Access license, which permits text mining, training, and research reuse.

Credits

Dataset extraction, cleaning, normalization, restructuring and validation carried out by Zeronex.