Download the dataset

Open Editors Plus is released under CC0 1.0 (public domain). No restrictions on reuse.

CSV

~200 MB, UTF-8 encoded

Standard comma-separated values. Compatible with Excel, R, Python pandas, and any spreadsheet tool.

Download CSV from Zenodo

Parquet

~30 MB, columnar format

Compressed columnar format. 5-10x smaller than CSV. Ideal for pandas, R arrow, DuckDB, and big data tools.

Download Parquet from Zenodo

Dataset summary

922,466

Records

619,700

Unique editors

15,175

Journals

55+

Columns

Quick start

# Python (pandas)

import pandas as pd
df = pd.read_csv("openeditors_plus_2026.csv")
print(f"{len(df):,} records, {df['editor'].nunique():,} editors")

# Python (Parquet, faster)

df = pd.read_parquet("openeditors_plus_2026.parquet")

# R

library(arrow)
df <- read_parquet("openeditors_plus_2026.parquet")
cat(sprintf("%d records, %d editors\n", nrow(df), length(unique(df$editor))))

# DuckDB (SQL on Parquet, no loading needed)

SELECT ror_country, COUNT(*) as n, ROUND(AVG(h_index), 1) as mean_h
FROM 'openeditors_plus_2026.parquet'
GROUP BY ror_country ORDER BY n DESC LIMIT 10;

JSON API (pre-aggregated)

For lightweight access, pre-computed aggregate data is available as static JSON:

curl https://openeditors-plus.org/api/summary.json
curl https://openeditors-plus.org/api/publishers.json
curl https://openeditors-plus.org/api/countries.json
curl https://openeditors-plus.org/api/fields.json

Version history

v2026 April 2026

Latest

Initial release. 922,466 records, 48 publishers, 15,175 journals.

Annual updates planned. The Zenodo concept DOI will group all versions under one persistent identifier.