Lilambd/world-science

World Science — every OpenAlex work counted by field x country x year x type

🌐 日本語 · 中文 · Español · Português · Français · Deutsch · 한국어 · हिन्दी · العربية

• 日本語 — World Science：分野×国×年の論文数データ: OpenAlexの全464,765,485件の著作をサブ分野・著者の国・年・種別で集計。ランキングと2025年に最も伸びたサブ分野も収録。
• 中文 — World Science（全球科研论文：领域×国家×年份）: OpenAlex 全部 464,765,485 篇作品按子领域、作者国家、年份和作品类型统计，附排名及 2025 年增长最快的子领域。
• Español — World Science (artículos por campo x país x año): Las 464,765,485 obras de OpenAlex contadas por subcampo, país del autor, año y tipo de obra, con rankings y los subcampos de mayor crecimiento en 2025.
• Português — World Science: artigos científicos por área, país e ano (OpenAlex): Todas as 464,765,485 obras do OpenAlex contadas por subárea, país do autor, ano e tipo de obra, com rankings e as subáreas que mais cresceram em 2025.
• Français — World Science : publications scientifiques par domaine, pays et année: Les 464,765,485 travaux d'OpenAlex comptés par sous-domaine, pays des auteurs, année et type de publication, avec classements et sous-domaines à la plus forte croissance en 2025.
• Deutsch — World Science: Publikationen nach Fachgebiet x Land x Jahr: Alle 464,765,485 Werke in OpenAlex, gezählt nach Teilgebiet, Autorenland, Jahr und Werktyp, mit Rankings und den am schnellsten wachsenden Teilgebieten 2025.
• 한국어 — World Science: 분야·국가·연도별 세계 논문 통계: OpenAlex의 464,765,485편 전체를 세부 분야·저자 국가·연도·유형별로 집계하고, 2025년 급상승 분야도 제공합니다.
• हिन्दी — World Science (क्षेत्र x देश x वर्ष के अनुसार शोध-पत्र): OpenAlex के सभी 464,765,485 works की गिनती उपक्षेत्र, लेखक के देश, वर्ष और work प्रकार के अनुसार, रैंकिंग और 2025 में सबसे तेज़ी से बढ़ते उपक्षेत्रों के साथ।
• العربية — World Science (الأبحاث حسب المجال × الدولة × السنة): جميع أعمال OpenAlex البالغ عددها 464,765,485 مُحصاة حسب المجال الفرعي وبلد المؤلف والسنة ونوع العمل، مع تصنيفات والمجالات الفرعية الأسرع صعودًا في 2025.

All 464,765,485 works in the OpenAlex snapshot of 2026-10-14, counted once each (the fractional totals add back to the snapshot record count). No sampling, no model, no API ranking: the whole snapshot was read column by column from the public OpenAlex S3 bucket and grouped.

Part of the World Signals family: one flat table per way of looking at the world. This one is the science face: where research is written, in which of 252 subfields, and what is rising.

Every row carries source, snapshot_date and fetched_at.

Quick start:

from datasets import load_dataset
fy = load_dataset("Lilambd/world-science", "papers_by_field_year", split="train")
rising = load_dataset("Lilambd/world-science", "rising_subfield_country_2025", split="train")

file	rows	what
works_by_subfield_country_year_type.parquet	3.43M	year (1900-2026) x work type x subfield (252 + none) x author country. works = full counting (a work with authors in JP and US counts once for each), works_fractional = 1/k per country so totals do not double count. Also open-access count, retracted count, citations.
papers_by_field_year.csv	3,429	world total per field and year: papers, preprints, datasets, other records, log10 of papers
papers_by_country_year.csv	18,007	per country and year: papers (full and fractional), preprints, datasets, open-access papers, citations
rising_subfield_country_2025.csv	8,716	subfield x country cells where 2025 papers are compared with the 2020-2024 mean (index, base = 100). Only cells with at least 100 papers in 2025 and a mean of at least 20
new_records_by_month.parquet	204k	records that entered OpenAlex each month from 2025-11 to 2026-10, by type, field and country
subfields.csv, countries.csv		lookups (subfield -> field -> domain; country -> continent, Global South flag)

"papers" = article, review, book / chapter, letter, editorial, dissertation. Preprints and datasets are counted separately on purpose.

Read before using (measured, not assumed)

• Datasets swamp the totals from 2024. OpenAlex type dataset was 24.9M records for publication year 2025, against 8.4M articles. About 18.1M of those 2025 datasets carry a Japanese affiliation, almost all in Nuclear and High Energy Physics and Aerospace Engineering. Count papers, not works, when comparing countries.
• No country for many works. country_code = XX means no author affiliation country is recorded. For 2025 that is 4.3M fractional papers, more than any single country.
• Recent years are still filling. 2026 is a partial year, and OpenAlex keeps adding records for past years.
• Month added starts 2025-11. OpenAlex rebuilt its index in 2025-10 and gave about 356M records that creation month, so earlier months are not a real flow and are left out.
• About 17.7M works with no publication year, or a year before 1900 or after 2026, are left out of the year tables.
• Country = country of the author's affiliation as OpenAlex records it, not nationality.

Refresh

Rebuilt from each new OpenAlex snapshot (about monthly). The script that made it is scripts/science_face.py (it reads only the needed columns over HTTP range requests, about 2.4MB per 750MB file, 4.6GB for the whole snapshot, then builds the tables).

Quick start: datasets, pandas, DuckDB

import pandas as pd  # hf:// paths need `pip install huggingface_hub`
BASE = "hf://datasets/Lilambd/world-science/"
kw = dict(keep_default_na=False, na_values=[""])  # country_code "NA" is Namibia
pcy = pd.read_csv(BASE + "papers_by_country_year.csv", **kw)
wide = pcy[pcy["year"] >= 2000].pivot_table(index="year", columns="country_code", values="papers_fractional")
print(wide[["US", "CN", "JP", "IN", "DE"]].tail())

-- DuckDB 0.10+ reads hf:// paths directly
-- the fastest-rising subfield x country cells in 2025
SELECT subfield, country, papers_2025, mean_papers_2020_2024, index_2025_vs_base100
FROM 'hf://datasets/Lilambd/world-science/rising_subfield_country_2025.csv'
ORDER BY index_2025_vs_base100 DESC LIMIT 20;

A runnable notebook is in notebooks/quickstart.ipynb.

Use cases

• Country and field research-output trends from the full OpenAlex snapshot (no sampling).
• Spot rising subfields per country (2025 vs the 2020-2024 mean).
• Global South vs North comparisons with fractional counting.

Update cadence

About monthly: rebuilt from each new OpenAlex snapshot (see Refresh).

Citation

@misc{lilambd2026_world_science,
  author       = {Lilambd},
  title        = {World Science: papers by field x country x year, from OpenAlex},
  year         = {2026},
  publisher    = {Hugging Face},
  howpublished = {\url{https://huggingface.co/datasets/Lilambd/world-science}},
  url          = {https://huggingface.co/datasets/Lilambd/world-science}
}

Please also credit the original sources listed in this card.

Attribution

Data from OpenAlex (Priem, Piwowar and Orr, 2022), released CC0. Grouping and tables by Lilambd, also CC0. Questions or a slice you need: hello@lilambd.com

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日本語: OpenAlex の論文など 4.65億件 (2026-10-14 時点) を全部、分野252 × 国 × 年 × 種類 で数えた台帳。2024年からは「データセット」の登録が論文より多く、2025年は日本の所属で約1,810万件 (ほぼ物理と航空宇宙) あるため、国を比べる時は papers を使う。

Paid editions & related

• Same data as an API (free sample=1, pay-per-call via x402): https://api.lilambd.com/llms.txt
• All Lilambd shops: https://payhip.com/Lilambd and https://lilambdcrossing.itch.io

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