| --- |
| 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} |
| } |
| ``` |
|
|