| --- |
| license: cc-by-4.0 |
| task_categories: |
| - text-generation |
| - feature-extraction |
| language: |
| - en |
| - multilingual |
| tags: |
| - science |
| - papers |
| - fulltext |
| - scientific-papers |
| size_categories: |
| - 10M<n<100M |
| configs: |
| - config_name: corex |
| data_files: "corex/*.parquet" |
| - config_name: papers-2 |
| data_files: "papers-2/*.parquet" |
| - config_name: papers-3 |
| data_files: "papers-3/*.parquet" |
| - config_name: pes2o |
| data_files: "pes2o/*.parquet" |
| --- |
| |
| # Scientific Papers - Raw Full Text |
|
|
| **~57 million scientific papers with full text**, extracted from multiple large-scale academic paper collections. This dataset provides raw full text suitable for pre-training, fine-tuning, or building search indices over scientific literature. |
|
|
| ## Subsets |
|
|
| | Subset | Papers | Size | Source | |
| |--------|--------|------|--------| |
| | **papers-2** | ~18.5M | ~358 GB | S2ORC papers collection (untitled subset) | |
| | **papers-3** | ~27.4M | ~198 GB | S2ORC scientific-papers collection | |
| | **pes2o** | ~8.2M | ~106 GB | Pes2oX-fulltext (Semantic Scholar, Apache 2.0) | |
| | **corex** | ~2.9M | ~25 GB | CORE repository (core.ac.uk, Apache 2.0) | |
| | **Total** | **~57M** | **~687 GB** | | |
|
|
| ## Schema (9 columns) |
|
|
| | Column | Type | Description | |
| |--------|------|-------------| |
| | `paper_id` | string | Unique identifier (source-specific) | |
| | `title` | string | Paper title (when available) | |
| | `authors` | string | Author names (semicolon-separated) | |
| | `year` | string | Publication year (when available) | |
| | `venue` | string | Publication venue (when available) | |
| | `doi` | string | DOI (when available) | |
| | `abstract` | string | Paper abstract (when available) | |
| | `raw_fulltext` | string | Complete paper text | |
| | `text_length` | int64 | Character count of full text | |
|
|
| ## Usage |
|
|
| ```python |
| from datasets import load_dataset |
| |
| # Load a specific subset |
| ds = load_dataset("scientifi-papers/scientific-papers", "corex") |
| |
| # Load papers-3 (largest) |
| ds = load_dataset("scientifi-papers/scientific-papers", "papers-3") |
| |
| # Access full text |
| paper = ds['train'][0] |
| print(f"Title: {paper['title']}") |
| print(f"Text length: {paper['text_length']} chars") |
| print(paper['raw_fulltext'][:500]) |
| ``` |
|
|
| ## Sources |
|
|
| - **papers-2 / papers-3**: Extracted from the Semantic Scholar Open Research Corpus (S2ORC) via GROBID PDF parsing |
| - **pes2o**: Allen AI's Pes2oX-fulltext dataset (cleaned S2ORC full text) |
| - **corex**: CORE repository (core.ac.uk) - 2018 full-text dump of open-access research papers |
|
|
| ## License |
|
|
| CC-BY-4.0 |
|
|
