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3. Data
| Wiki page | Description |
|---|---|
| About the Project | Goals, motivations and journal inclusion criteria |
| Using the Website | Column definitions and how to filter journals |
| The Data | Data sources and processing pipeline |
| Contributing | How to add journals, edit data, report issues, or contribute code |
Where to Publish? combines a manually curated database of life science journals with data from several external sources. The data is processed monthly via an automated pipeline and published as CSV files that power the website.
Data flow:
Google Sheets (manual curation)
↓
download_csv.sh
↓
data_extracted/*.csv
↓
update_extracted.py ← External sources (Scimago, OpenAPC, DOAJ)
↓
data_process.py
↓
data/*.csv → Website
The core journal list is maintained in a Google Sheets document:
This spreadsheet contains manually curated information including:
- Journal names and websites
- Field classifications
- Publisher names and types
- Associated institutions
- Business model classifications
Journals are added through:
- Community submissions via our Google Form
- Maintainer research to fill gaps in specific fields
- Bulk imports from trusted sources (e.g., DAFNEE for ecology/evolution)
All submissions are reviewed by maintainers before inclusion. We verify journal legitimacy and cross-reference against known predatory journal indicators.
We enrich our curated data with information from the following sources:
🔗 scimagojr.com The SCImago Journal & Country Rank (SJCR) is a public portal that provides scientific indicators for journals and countries, based on data from the Scopus® database (Elsevier). It allows for the comparison and analysis of journals and countries by subject area, specific category, or region, using data from over 34,100 titles and 239 countries. Its main indicator, the SCImago Journal Rank (SJR), measures journal visibility using an algorithm similar to Google’s PageRank™. SCImago is a research group affiliated with several Spanish universities and the CSIC, specializing in information analysis and visualization.
Provides:
- Scimago Rank (SJR): Citation-based journal impact metric
- Scimago Quartile: Field-normalized ranking (Q1–Q4)
- H-index: Journal-level citation metric
- Open access status: Whether the journal is indexed as OA or Diamond OA
Provides:
- Article Processing Charges: Average APCs in euros, calculated from the last 3–5 years of reported payments
- Business model indicators: Helps identify hybrid vs. full OA journals
OpenAPC collects APC payment data from universities and research institutions worldwide, offering transparency into actual publication costs.
🔗 doaj.org
Provides:
- Publisher information
- Country of publication
- Journal website URLs
- Institution associations
DOAJ indexes over 22,000 open access journals and serves as a quality indicator — inclusion requires journals to meet specific editorial and transparency standards.
Provides:
- Article Processing Charges: APCs in euros.
- Business model indicators: Helps identify hybrid vs. OA journals
An open dataset of annual Article Processing Charges (APCs) of gold and hybrid journals published by Elsevier, Frontiers, MDPI, PLOS, Springer-Nature and Wiley in the years 2019-2023, generated by Butler et. al., and hosted by Harvard Dataverse.
The Database of Academia-Friendly jourNals in Ecology and Evolution provides comprehensive information about non-profit, learned society, and university-associated journals specifically in ecology and evolution. Contains 600+ journals.
🔗 SU List
A list of ~3,400 journals presumed non-predatory, curated by consulting 58 medical specialty experts. Established in September 2021 and updated quarterly. We use this list to help filter out potentially predatory journals.
Data is updated via a GitHub Action that runs the following pipeline:
scripts/download_csv.shDownloads the latest data from Google Sheets into data_extracted/*.csv (one file per field).
python scripts/update_extracted.pyJoins journal data with Scimago, OpenAPC, and DOAJ to fill in:
- Scimago Rank, Quartile, and H-index
- Average APCs
- Publisher and country information
- Open access status
python scripts/data_process.py- Normalizes and cleans all fields
- Removes duplicate entries (by journal name or URL)
- Generates field-specific CSV files in
data/ - Creates
data/all_biology.csvcontaining all journals (deduplicated)
Final CSV files contain the following columns in order:
Journal, Field, Publisher, Publisher type, Business model,
Institution, Institution type, Country, Website, APC Euros,
Scimago Rank, Scimago Quartile, H index, PCI partner
See Contributing for instructions on:
- Adding new journals
- Correcting existing entries
- Suggesting new data sources