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Datasets:
GodotCN
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science-datalake

Tasks:
Text Classification
Feature Extraction
Modalities:
Image
Tabular
Text
Languages:
English
Size:
10B - 100B
ArXiv:
Tags:
scholarly
academic
citations
bibliometrics
science-of-science
openalex
License:
Dataset card Data Studio Files
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metadata 
language:
  - en
license:
  - cc0-1.0
  - cc-by-4.0
  - cc-by-sa-4.0
  - cc-by-nc-sa-4.0
  - cc-by-nc-4.0
size_categories:
  - 100M<n<1B
task_categories:
  - text-classification
  - feature-extraction
tags:
  - scholarly
  - academic
  - citations
  - bibliometrics
  - science-of-science
  - openalex
  - sciscinet
  - papers-with-code
  - duckdb
  - parquet
  - ontologies
  - knowledge-graph
pretty_name: Science Data Lake
thumbnail: https://raw.githubusercontent.com/J0nasW/science-datalake/main/sdl_banner.jpg
configs:
  - config_name: unified_papers
    data_files: xref/unified_papers/*.parquet
  - config_name: topic_ontology_map
    data_files: xref/topic_ontology_map/*.parquet
  - config_name: ontology_bridges
    data_files: xref/ontology_bridges/*.parquet
  - config_name: openalex_works
    data_files: openalex/works/*.parquet
  - config_name: openalex_authors
    data_files: openalex/authors/*.parquet
  - config_name: openalex_topics
    data_files: openalex/topics/*.parquet
  - config_name: openalex_works_topics
    data_files: openalex/works_topics/*.parquet
  - config_name: openalex_works_authorships
    data_files: openalex/works_authorships/*.parquet
  - config_name: openalex_works_referenced_works
    data_files: openalex/works_referenced_works/*.parquet
  - config_name: openalex_works_keywords
    data_files: openalex/works_keywords/*.parquet
  - config_name: openalex_institutions
    data_files: openalex/institutions/*.parquet
  - config_name: sciscinet_core
    data_files: sciscinet/core/*.parquet
  - config_name: sciscinet_large
    data_files: sciscinet/large/*.parquet
  - config_name: pwc_papers
    data_files: pwc/papers/*.parquet
  - config_name: pwc_paper_has_code
    data_files: pwc/paper_has_code/*.parquet
  - config_name: pwc_methods
    data_files: pwc/methods/*.parquet
  - config_name: pwc_paper_has_task
    data_files: pwc/paper_has_task/*.parquet
  - config_name: pwc_datasets
    data_files: pwc/datasets/*.parquet
  - config_name: retwatch
    data_files: retwatch/retraction_watch/*.parquet
  - config_name: p2p_preprint_to_paper
    data_files: p2p/preprint_to_paper/*.parquet
  - config_name: ros_patent_paper_pairs
    data_files: ros/patent_paper_pairs/*.parquet
  - config_name: ros_patent_paper_pairs_plus
    data_files: ros/patent_paper_pairs_plus/*.parquet
  - config_name: ros_pcs_oa
    data_files: ros/pcs_oa/*.parquet
  - config_name: ontology_terms
    data_files: ontologies/*_terms.parquet
  - config_name: ontology_hierarchy
    data_files: ontologies/*_hierarchy.parquet
  - config_name: ontology_xrefs
    data_files: ontologies/*_xrefs.parquet

Science Data Lake

arXiv GitHub DOI LLM-Ready Follow on X Author website

Science Data Lake

A unified, portable science data lake integrating 7 scholarly datasets (~525 GB Parquet) with cross-dataset DOI normalization, 13 scientific ontologies (1.3M terms), and a reproducible ETL pipeline.

Note: One additional source (Semantic Scholar S2AG) is supported by the pipeline but is not redistributed here due to its API terms of service. See Not Included in This Upload below.

What's Unique

This dataset enables queries that are impossible with any single source:

-- "Top disruptive papers with open-source code, checking for retractions"
SELECT doi, title, year,
       sciscinet_disruption,      -- from SciSciNet
       oa_cited_by_count,         -- from OpenAlex
       has_pwc,                   -- from Papers With Code
       has_retraction             -- from Retraction Watch
FROM unified_papers
WHERE has_pwc AND sciscinet_disruption > 0.5
ORDER BY oa_cited_by_count DESC
LIMIT 20

Datasets Included

Dataset Papers/Records License Key Contribution
OpenAlex 479M works CC0 1.0 (public domain) Broadest coverage, topics, FWCI
SciSciNet v2 250M papers CC BY 4.0 Disruption index, atypicality, team size
Papers With Code 513K papers CC BY-SA 4.0 Method-task-dataset-code links
Retraction Watch 69K records Open (via Crossref) Retraction flags + reasons
Reliance on Science 47.8M pairs CC BY-NC 4.0 Patent-to-paper citation pairs (global)
Preprint-to-Paper 146K pairs CC BY 4.0 bioRxiv preprint to published paper
13 Ontologies 1.3M terms Various (see below) CSO, MeSH, GO, DOID, ChEBI, NCIT, HPO, EDAM, AGROVOC, UNESCO, STW, MSC2020, PhySH

Ontology Licenses

Ontology License
MeSH Public Domain (US government work)
GO, ChEBI, NCIT, EDAM, CSO, PhySH, STW CC BY 4.0
DOID CC0 1.0
AGROVOC CC BY 3.0 IGO
UNESCO Thesaurus CC BY-SA 3.0 IGO
HPO Custom (free for research use)
MSC2020 CC BY-NC-SA 4.0 (non-commercial)

Snapshot Dates

Each source was downloaded at a specific point in time:

Dataset Snapshot / Release Notes
OpenAlex 2026-02-03 S3 snapshot
SciSciNet v2 2024-11-01 GCS bucket
Papers With Code 2025-07 Archived JSON
Retraction Watch 2025-02 Crossref CSV
Reliance on Science v64 Zenodo record
Preprint-to-Paper 2025-06 Zenodo record
13 Ontologies 2026-02 Official sources

All snapshots can be refreshed using the update pipeline — see below.

Not Included in This Upload

The following source is supported by the full pipeline (GitHub) but is not redistributed here due to its API terms of service:

Dataset Reason How to obtain
S2AG (Semantic Scholar, 231M papers) License requires individual agreement with Semantic Scholar Semantic Scholar Datasets API

After downloading S2AG locally, run the full pipeline to integrate it.

Key Tables

unified_papers (293M rows)

The headline table: one row per unique DOI, joining all sources.

Column Type Description
doi VARCHAR Normalized DOI (lowercase, no prefix)
title VARCHAR Best available title (OpenAlex > S2AG)
year BIGINT Publication year
openalex_id VARCHAR OpenAlex work ID
sciscinet_paperid VARCHAR SciSciNet paper ID
has_openalex BOOLEAN Present in OpenAlex
has_sciscinet BOOLEAN Present in SciSciNet
has_pwc BOOLEAN Has code on Papers With Code
has_retraction BOOLEAN Flagged in Retraction Watch
has_s2ag BOOLEAN Present in Semantic Scholar
has_patent BOOLEAN Cited by at least one patent (RoS)
s2ag_corpusid BIGINT Semantic Scholar corpus ID
s2ag_citationcount INTEGER S2AG citation count
oa_cited_by_count BIGINT OpenAlex citation count
sciscinet_disruption DOUBLE Disruption index (CD index)
sciscinet_atypicality DOUBLE Atypicality score
oa_fwci DOUBLE Field-Weighted Citation Impact

Note: The S2AG columns (s2ag_corpusid, s2ag_citationcount, s2ag_influentialcitationcount, s2ag_isopenaccess, has_s2ag) are present in the uploaded file but will contain NULL/FALSE values unless S2AG has been integrated locally. All other columns (including has_patent from Reliance on Science) are fully populated.

topic_ontology_map

Maps OpenAlex's 4,516 topics to terms in 13 scientific ontologies via embedding-based semantic similarity (BGE-large-en-v1.5, 1024-dim) + exact matching for large ontologies (MeSH, ChEBI, NCIT). 16,150 mappings covering 99.8% of topics. Columns include similarity (cosine, 0-1) and match_type (label/synonym/exact) for quality filtering.

ontology_bridges

Cross-ontology links discovered via shared external IDs (UMLS, Wikidata, MESH, etc.).

Usage with DuckDB

Option 1: Pre-built database file (recommended)

This repository includes a ready-to-use DuckDB database file (datalake.duckdb, 274 KB) with 145 SQL views pre-configured to read directly from HuggingFace. Download just this one file and query all 7 datasets immediately — no pipeline setup required.

import duckdb

con = duckdb.connect()
con.execute("INSTALL httpfs; LOAD httpfs;")
con.execute("ATTACH 'hf://datasets/J0nasW/science-datalake/datalake.duckdb' AS lake")

# Query using familiar schema.table syntax
df = con.execute("""
    SELECT doi, title, year, sciscinet_disruption, oa_cited_by_count
    FROM lake.xref.unified_papers
    WHERE sciscinet_disruption IS NOT NULL
    ORDER BY sciscinet_disruption DESC
    LIMIT 100
""").df()

# Cross-source joins work out of the box
con.execute("""
    SELECT t.display_name AS topic, o.ontology, o.term_name, o.similarity
    FROM lake.xref.topic_ontology_map o
    JOIN lake.openalex.topics t ON t.id = o.topic_id
    WHERE o.similarity >= 0.85
    ORDER BY o.similarity DESC
    LIMIT 20
""").df()

Option 2: Direct Parquet queries

You can also query individual Parquet files directly without the database file:

import duckdb

con = duckdb.connect()
con.execute("INSTALL httpfs; LOAD httpfs;")

df = con.execute("""
    SELECT doi, title, year, sciscinet_disruption, oa_cited_by_count
    FROM 'hf://datasets/J0nasW/science-datalake/xref/unified_papers/*.parquet'
    WHERE sciscinet_disruption IS NOT NULL
    ORDER BY sciscinet_disruption DESC
    LIMIT 100
""").df()

Keeping the Data Current

The full pipeline supports incremental updates. When upstream sources release new snapshots:

# Update a single dataset
python scripts/datalake_cli.py update openalex

# Update all datasets and rebuild cross-reference tables
python scripts/datalake_cli.py update
python scripts/materialize_unified_papers.py

See the GitHub repository for full pipeline documentation.

LLM & AI Agent Integration

This data lake ships with SCHEMA.md — a structured reference file optimized for LLM-based coding agents (Claude Code, Cursor, Copilot, etc.). It contains every table, column, type, join strategy, and performance tier in a format that AI agents can use to write correct DuckDB SQL without prior schema knowledge.

Point your AI assistant at SCHEMA.md and ask it to query across all 7 hosted datasets and 13 ontologies using natural language.

Building the Full Instance (All 8 Sources)

Clone the GitHub repository and run the pipeline to integrate all sources including S2AG:

git clone https://github.com/J0nasW/science-datalake
cd science-datalake
python scripts/datalake_cli.py download --all
python scripts/datalake_cli.py convert --all
python scripts/create_unified_db.py
python scripts/materialize_unified_papers.py

Citation

If you use the Science Data Lake, please cite the paper:

@article{wilinski2026sciencedatalake,
  title   = {The Science Data Lake: A Unified Open Infrastructure Integrating
             293 Million Papers Across Eight Scholarly Sources with
             Embedding-Based Ontology Alignment},
  author  = {Wilinski, Jonas},
  journal = {arXiv preprint arXiv:2603.03126},
  year    = {2026},
  url     = {https://arxiv.org/abs/2603.03126}
}

Dataset DOI: 10.57967/hf/7850

License

This dataset aggregates multiple sources, each with its own license. Users must comply with the most restrictive license applicable to the sources they use.

Component License
Integration code (scripts, pipeline) MIT
OpenAlex data CC0 1.0 (public domain)
SciSciNet v2 data CC BY 4.0
Papers With Code data CC BY-SA 4.0
Retraction Watch data Open (via Crossref)
Reliance on Science data CC BY-NC 4.0
Preprint-to-Paper data CC BY 4.0
Cross-reference tables (unified_papers, topic_ontology_map) Derived work — most restrictive source license applies
Ontologies Various — see table above; note MSC2020 is CC BY-NC-SA 4.0