OpenAlex API

OpenAlex is a comprehensive index of 250M+ scholarly works, authors, institutions, sources, and topics. It's the broadest multidisciplinary database in this skill.

Base URL

https://api.openalex.org

Authentication

API key recommended (free). Get one at https://openalex.org/settings/api
Pass as: ?api_key=YOUR_KEY
Legacy polite pool still works: add [email protected] for better rate limits

Rate Limits

100 requests/second max
Usage-based pricing with $1/day free allowance
Single entity lookups by ID/DOI are free (unlimited)
List + filter queries: ~$0.0001 each (~10,000/day free)
Search queries: ~$0.001 each (~1,000/day free)

Key Endpoints

1. Get a single work

GET /works/{id}

Accepts multiple ID formats:

/works/W2741809807                              (OpenAlex ID)
/works/doi:10.7717/peerj.4375                  (DOI)
/works/pmid:29456894                            (PMID)
/works/https://doi.org/10.7717/peerj.4375      (full DOI URL)

2. Search works

GET /works?search={query}&per_page={n}&page={n}

Parameter	Default	Description
`search`	--	Full-text search (title, abstract, fulltext). Supports boolean: `AND`, `OR`, `NOT` (uppercase)
`search.exact`	--	No stemming
`search.semantic`	--	AI embedding search (beta, 1 req/s, max 50 results)
`filter`	--	Comma-separated `field:value` pairs
`sort`	relevance	`cited_by_count:desc`, `publication_date:desc`, `relevance_score:desc`
`per_page`	25	Results per page (max 100)
`page`	1	Page number (max `page * per_page` = 10,000)
`cursor`	--	Use `*` for first page of deep pagination
`select`	--	Comma-separated fields to return
`group_by`	--	Aggregate by field

Advanced search: Supports wildcards (machin*), fuzzy (machin~1), proximity ("climate change"~5), boolean grouping.

Example:

https://api.openalex.org/works?search=CRISPR+gene+therapy&filter=from_publication_date:2023-01-01&sort=cited_by_count:desc&per_page=10

3. Filter works

GET /works?filter={filters}

Key filter fields:

Filter	Example	Description
`from_publication_date`	`2023-01-01`	Published after date
`to_publication_date`	`2024-12-31`	Published before date
`publication_year`	`2024`	Exact year
`type`	`article`	Work type
`cited_by_count`	`>100`	Citation threshold
`is_oa`	`true`	Open access only
`has_abstract`	`true`	Has abstract
`authorships.author.id`	`A5048491430`	By author ID
`primary_location.source.id`	`S137773608`	By journal/source
`institutions.country_code`	`us`	By country
`concepts.id`	`C41008148`	By concept/topic
`doi`	`10.1038/nature12373`	By DOI

Operators: >, <, ! (negation), | (OR within filter)

Example:

https://api.openalex.org/works?filter=from_publication_date:2024-01-01,type:article,is_oa:true,cited_by_count:>50

4. Other entities

GET /authors?search={name}
GET /authors/{id}
GET /sources?search={name}          (journals, repositories)
GET /sources/{id}
GET /institutions?search={name}
GET /institutions/{id}
GET /topics/{id}

Authors and institutions accept similar filter/sort/pagination parameters.

5. Cursor pagination (for >10,000 results)

GET /works?filter=publication_year:2024&cursor=*&per_page=100

Response includes meta.next_cursor. Pass it as cursor={value} in the next request. Stop when next_cursor is null.

Response Format

Work object (key fields)

json

{
  "id": "https://openalex.org/W2741809807",
  "doi": "https://doi.org/10.7717/peerj.4375",
  "title": "The state of OA",
  "publication_year": 2018,
  "publication_date": "2018-02-13",
  "type": "article",
  "language": "en",
  "is_retracted": false,
  "cited_by_count": 1169,
  "open_access": {
    "is_oa": true,
    "oa_status": "gold",
    "oa_url": "https://doi.org/10.7717/peerj.4375"
  },
  "authorships": [{
    "author": {"id": "https://openalex.org/A5048491430", "display_name": "Heather Piwowar"},
    "institutions": [{"display_name": "Impactstory"}]
  }],
  "primary_location": {
    "source": {"display_name": "PeerJ", "issn_l": "2167-8359"}
  },
  "abstract_inverted_index": {"Despite": [0], "growing": [1], "interest": [2], ...},
  "referenced_works": ["https://openalex.org/W123...", ...],
  "ids": {"openalex": "...", "doi": "...", "pmid": "..."}
}

Abstract inverted index

Abstracts are stored as {word: [positions]}. To reconstruct:

python

def reconstruct(inverted_index):
    positions = {}
    for word, indices in inverted_index.items():
        for idx in indices:
            positions[idx] = word
    return ' '.join(positions[i] for i in sorted(positions.keys()))

List response

json

{
  "meta": {"count": 3771834, "page": 1, "per_page": 10},
  "results": [...]
}

Error Format

HTTP 403 for invalid API key, 429 for rate limit exceeded. Error responses include a message field.