File size: 3,265 Bytes
055d3d2 1d2af3d 055d3d2 1d2af3d 055d3d2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 | ---
license: cc-by-4.0
language:
- en
- zh
- de
- fr
- es
- it
- pt
- ja
- ko
- ar
- ru
- nl
- pl
- tr
tags:
- affiliations
- nlp
- bibliometrics
- openalex
- ner
- institution-disambiguation
- academic
- text
pretty_name: OpenAlex Affiliation Dataset
size_categories:
- 1M<n<10M
task_categories:
- token-classification
- text-classification
configs:
- config_name: "2025-12"
data_files: "data/2025-12/*.csv"
---
# OpenAlex Affiliation Dataset
This dataset provides raw and deduplicated academic affiliation strings from scholarly works published in December 2025. Affiliation strings are the raw, author-written institutional descriptions (e.g., "Department of Computer Science, MIT, Cambridge, MA, USA") that appear in academic papers — before any normalization or entity resolution.
## What are raw affiliation strings?
Affiliation strings are the institutional descriptions authors include in their papers, before any normalization or entity resolution:
```
Department of Computer Science, Stanford University, Stanford, CA 94305, USA
Institut fur Physik, Humboldt-Universitat zu Berlin, 12489 Berlin, Germany
Faculdade de Medicina, Universidade de Sao Paulo, Sao Paulo, Brasil
```
## Use cases
- **Institution disambiguation / NER** — parse and normalize to known entities (ROR, GRID, Wikidata)
- **NLP training data** — multilingual academic text for span detection, entity linking
- **Bibliometrics** — institutional analytics, collaboration networks
- **Affiliation normalization** — training data for models like AffilGood, S2AFF
## Data source & provenance
**Source:** [OpenAlex](https://openalex.org) — fully open index of scholarly works by OurResearch. CC BY 4.0.
**Pipeline:** [labid-base/openalex-pipeline](https://github.com/labid-base/openalex-pipeline)
Each chunk is deduplicated independently. `work_id` is the first work in which each string appeared within the chunk.
## Quick start
```python
from datasets import load_dataset
ds = load_dataset("LabID-base/OpenAlex-Afillation", "2025-12")
print(ds["train"][0])
# {"work_id": "https://openalex.org/W...", "raw_affiliation_string": "Department of..."}
```
## Dataset statistics
| Month | Collection date | Works | Total entries | Unique strings | Chunks |
|-------|----------------|-------|---------------|----------------|--------|
| 2025-12 | 2026-03-27 | 704,702 | 3,595,056 | **1,557,802** | 71 |
## Schema
| Column | Type | Description |
|--------|------|-------------|
| `work_id` | string | OpenAlex work ID (e.g. `https://openalex.org/W2741809807`) |
| `raw_affiliation_string` | string | Raw affiliation text as written by the author |
## Directory structure
```
data/
2025-12/
works_2025_12_chunk_0001.csv
...
works_2025_12_chunk_0071.csv (71 chunks, ~22K strings each)
```
## Update schedule
Updated **monthly**. Each update adds a new `data/{YYYY}-{MM}/` folder.
| Release | Period | Status |
|---------|--------|--------|
| v1 | 2025-12 | Available |
| v2 | 2026-01 | Planned |
## Citation
```bibtex
@misc{priem2022openalex,
title={OpenAlex: A fully-open index of the world's research works},
author={Priem, Jason and Piwowar, Heather and Orr, Richard},
year={2022},
eprint={2205.01833},
archivePrefix={arXiv}
}
```
|