openalex-paper-search

Academic Paper Search (OpenAlex)

Search 240M+ scholarly works using the OpenAlex API -- completely free, no API key required, no SDK needed. Just curl or bash with URL construction.

Full docs: https://docs.openalex.org

Quick Start

OpenAlex is a REST API. You query it by constructing URLs and fetching them with curl. All responses are JSON.

# Search for papers about "transformer architecture"
curl -s "https://api.openalex.org/works?search=transformer+architecture&per_page=5&[email protected]" | python3 -m json.tool

Important: Always include [email protected] (or any valid email) in every request. Without it, you're limited to 1 request/second. With it, you get 10 requests/second (the "polite pool").

Core Concepts

Entities

OpenAlex has these entity types (all queryable):

Entity	Endpoint	Count	Description
Works	/works	240M+	Papers, articles, books, datasets, theses
Authors	/authors	90M+	People who create works
Sources	/sources	250K+	Journals, repositories, conferences
Institutions	/institutions	110K+	Universities, research orgs
Topics	/topics	4K+	Research topics (hierarchical)

Work Object -- Key Fields

When you fetch a work, these are the most useful fields:

id                        OpenAlex ID (e.g., "https://openalex.org/W2741809807")
doi                       DOI URL
title / display_name      Paper title
publication_year          Year published
publication_date          Full date (YYYY-MM-DD)
cited_by_count            Number of incoming citations
fwci                      Field-Weighted Citation Impact (normalized)
type                      article, preprint, review, book, dataset, etc.
language                  ISO 639-1 code (e.g., "en")
is_retracted              Boolean
open_access.is_oa         Boolean -- is it freely accessible?
open_access.oa_url        Direct URL to free version
authorships               List of authors with names, institutions, ORCIDs
abstract_inverted_index   Abstract as inverted index (needs reconstruction)
referenced_works          List of OpenAlex IDs this work cites (outgoing)
related_works             Algorithmically related works
cited_by_api_url          API URL to get works that cite this one (incoming)
topics                    Assigned research topics with scores
keywords                  Extracted keywords with scores
primary_location          Where the work is published (journal, repo)
best_oa_location          Best open access location with PDF link

Reconstructing Abstracts

OpenAlex stores abstracts as inverted indexes for legal reasons. To get plaintext, reconstruct:

import json, sys
# Read the abstract_inverted_index from a work object
inv_idx = work["abstract_inverted_index"]
if inv_idx:
    words = [""] * (max(max(positions) for positions in inv_idx.values()) + 1)
    for word, positions in inv_idx.items():
        for pos in positions:
            words[pos] = word
    abstract = " ".join(words)

Or in bash with python3 -c:

# Pipe a work JSON into this to extract the abstract
echo "$WORK_JSON" | python3 -c "
import json,sys
w=json.load(sys.stdin)
idx=w.get('abstract_inverted_index',{})
if idx:
    words=['']*( max(max(p) for p in idx.values())+1 )
    for word,positions in idx.items():
        for pos in positions: words[pos]=word
    print(' '.join(words))
"

Searching for Papers

Basic Keyword Search

Searches across titles, abstracts, and fulltext. Uses stemming and stop-word removal.

# Simple search
curl -s "https://api.openalex.org/works?search=large+language+models&[email protected]"

# With per_page limit
curl -s "https://api.openalex.org/works?search=CRISPR+gene+editing&per_page=10&[email protected]"

Boolean Search

Use uppercase AND, OR, NOT with parentheses and quoted phrases:

# Complex boolean query
curl -s "https://api.openalex.org/works?search=(reinforcement+learning+AND+%22robot+control%22)+NOT+simulation&[email protected]"

# Exact phrase match (use double quotes, URL-encoded as %22)
curl -s "https://api.openalex.org/works?search=%22attention+is+all+you+need%22&[email protected]"

Search Specific Fields

# Title only
curl -s "https://api.openalex.org/works?filter=title.search:transformer&[email protected]"

# Abstract only
curl -s "https://api.openalex.org/works?filter=abstract.search:protein+folding&[email protected]"

# Title and abstract combined
curl -s "https://api.openalex.org/works?filter=title_and_abstract.search:neural+scaling+laws&[email protected]"

# Fulltext search (subset of works)
curl -s "https://api.openalex.org/works?filter=fulltext.search:climate+tipping+points&[email protected]"

Filtering

Filters are the most powerful feature. Combine them with commas (AND) or pipes (OR).

Most Useful Filters

# By publication year
?filter=publication_year:2024
?filter=publication_year:2020-2024
?filter=publication_year:>2022

# By citation count
?filter=cited_by_count:>100        # highly cited
?filter=cited_by_count:>1000       # landmark papers

# By open access
?filter=is_oa:true                 # only open access
?filter=oa_status:gold             # gold OA only

# By type
?filter=type:article               # journal articles
?filter=type:preprint              # preprints
?filter=type:review                # review articles

# By language
?filter=language:en                # English only

# Not retracted
?filter=is_retracted:false

# Has abstract
?filter=has_abstract:true

# Has downloadable PDF
?filter=has_content.pdf:true

# By author (OpenAlex ID)
?filter=author.id:A5023888391

# By institution (OpenAlex ID)
?filter=institutions.id:I27837315  # e.g., University of Michigan

# By DOI
?filter=doi:https://doi.org/10.1038/s41586-021-03819-2

# By indexed source
?filter=indexed_in:arxiv           # arXiv papers
?filter=indexed_in:pubmed          # PubMed papers
?filter=indexed_in:crossref        # Crossref papers

Combining Filters

# AND: comma-separated
?filter=publication_year:>2022,cited_by_count:>50,is_oa:true,type:article

# OR: pipe-separated within a filter
?filter=publication_year:2023|2024

# NOT: prefix with !
?filter=type:!preprint

# Combined example: highly-cited OA articles from 2023-2024, not preprints
curl -s "https://api.openalex.org/works?filter=publication_year:2023-2024,cited_by_count:>50,is_oa:true,type:!preprint&search=machine+learning&per_page=10&[email protected]"

Sorting

# Most cited first
?sort=cited_by_count:desc

# Most recent first
?sort=publication_date:desc

# Most relevant first (only when using search)
?sort=relevance_score:desc

# Multiple sort keys
?sort=publication_year:desc,cited_by_count:desc

Pagination

Two modes: basic paging (for browsing) and cursor paging (for collecting all results).

# Basic paging (limited to 10,000 results)
?page=1&per_page=25
?page=2&per_page=25

# Cursor paging (unlimited, for collecting everything)
?per_page=100&cursor=*                    # first page
?per_page=100&cursor=IlsxNjk0ODc...      # next page (cursor from previous response meta)

The cursor for the next page is in response.meta.next_cursor. When it's null, you've reached the end.

Select Fields

Reduce response size by selecting only the fields you need:

# Only get IDs, titles, citation counts, and DOIs
?select=id,display_name,cited_by_count,doi,publication_year

# Minimal metadata for scanning
?select=id,display_name,publication_year,cited_by_count,open_access

Citation Graph Traversal

Find what a paper cites (outgoing references)

# Get works cited BY a specific paper
curl -s "https://api.openalex.org/works?filter=cited_by:W2741809807&per_page=25&[email protected]"

Find what cites a paper (incoming citations)

# Get works that CITE a specific paper
curl -s "https://api.openalex.org/works?filter=cites:W2741809807&sort=cited_by_count:desc&per_page=25&[email protected]"

Find related works

# Get related works (algorithmic, based on shared concepts)
curl -s "https://api.openalex.org/works?filter=related_to:W2741809807&per_page=25&[email protected]"

Citation chain: follow the references

1. Get a seminal paper by DOI
2. Find its referenced_works (what it cites)
3. Find who cites it (filter=cites:WORK_ID)
4. For the most cited citers, repeat

This is how you build a literature graph around a topic.

Author Lookup

# Search for an author
curl -s "https://api.openalex.org/authors?search=Yann+LeCun&[email protected]"

# Get an author's works (by OpenAlex author ID)
curl -s "https://api.openalex.org/works?filter=author.id:A5064850633&sort=cited_by_count:desc&per_page=10&[email protected]"

# Get an author by ORCID
curl -s "https://api.openalex.org/authors/orcid:[email protected]"

Lookup by External ID

# By DOI
curl -s "https://api.openalex.org/works/doi:10.1038/[email protected]"

# By PubMed ID
curl -s "https://api.openalex.org/works/pmid:[email protected]"

# By arXiv ID (via DOI)
curl -s "https://api.openalex.org/works/doi:10.48550/[email protected]"

# Batch lookup: up to 50 IDs at once
curl -s "https://api.openalex.org/works?filter=doi:https://doi.org/10.1234/a|https://doi.org/10.1234/b|https://doi.org/10.1234/c&[email protected]"

Open Access & PDF Access

# Find OA papers with direct PDF links
curl -s "https://api.openalex.org/works?search=quantum+computing&filter=is_oa:true,has_content.pdf:true&select=id,display_name,open_access,best_oa_location&per_page=5&[email protected]"

The best_oa_location.pdf_url field gives a direct PDF link when available. The open_access.oa_url gives the best available OA landing page or PDF.

Practical Workflows

Literature Survey on a Topic

# 1. Find the most-cited papers on a topic
curl -s "https://api.openalex.org/works?search=retrieval+augmented+generation&sort=cited_by_count:desc&filter=publication_year:>2020,type:article,has_abstract:true&per_page=20&select=id,display_name,publication_year,cited_by_count,doi,authorships,abstract_inverted_index&[email protected]"

# 2. For the top papers, explore their citation graphs
curl -s "https://api.openalex.org/works?filter=cites:W4285719527&sort=cited_by_count:desc&per_page=10&select=id,display_name,publication_year,cited_by_count,doi&[email protected]"

# 3. Find recent papers building on this work
curl -s "https://api.openalex.org/works?filter=cites:W4285719527,publication_year:>2023&sort=publication_date:desc&per_page=10&[email protected]"

Find Landmark/Seminal Papers

# Highly cited + search term
curl -s "https://api.openalex.org/works?search=attention+mechanism+neural+networks&filter=cited_by_count:>500,type:article&sort=cited_by_count:desc&per_page=10&select=id,display_name,publication_year,cited_by_count,doi&[email protected]"

Find Recent Preprints

# Latest preprints on a topic
curl -s "https://api.openalex.org/works?search=multimodal+large+language+models&filter=type:preprint,publication_year:2025&sort=publication_date:desc&per_page=15&[email protected]"

Find Review Articles

# Review/survey papers on a topic
curl -s "https://api.openalex.org/works?search=federated+learning&filter=type:review,cited_by_count:>20&sort=cited_by_count:desc&per_page=10&[email protected]"

Author Analysis

# 1. Find the author
curl -s "https://api.openalex.org/authors?search=Geoffrey+Hinton&select=id,display_name,works_count,cited_by_count,last_known_institutions&[email protected]"

# 2. Get their most influential papers
curl -s "https://api.openalex.org/works?filter=author.id:A5068082743&sort=cited_by_count:desc&per_page=10&select=id,display_name,publication_year,cited_by_count,doi&[email protected]"

# 3. Get their recent work
curl -s "https://api.openalex.org/works?filter=author.id:A5068082743,publication_year:>2023&sort=publication_date:desc&per_page=10&[email protected]"

Saving Results to Disk

When doing deep research, save paper data to disk for later processing:

# Save search results as JSON
curl -s "https://api.openalex.org/works?search=topic&per_page=50&[email protected]" > research/papers/topic-search.json

# Extract and save a clean summary
curl -s "https://api.openalex.org/works?search=topic&per_page=50&select=id,display_name,publication_year,cited_by_count,doi,authorships&[email protected]" | python3 -c "
import json, sys
data = json.load(sys.stdin)
for w in data.get('results', []):
    authors = ', '.join(a['author']['display_name'] for a in w.get('authorships', [])[:3])
    if len(w.get('authorships', [])) > 3: authors += ' et al.'
    print(f\"[{w.get('cited_by_count',0)} cites] {w['display_name']} ({w.get('publication_year','?')}) - {authors}\")
    if w.get('doi'): print(f\"  DOI: {w['doi']}\")
    print()
" > research/papers/topic-summary.txt

For deep research, save individual paper metadata to your sources-index.md and raw data to sources/:

# Save a paper's full metadata
curl -s "https://api.openalex.org/works/[email protected]" > research/sources/001-paper-title.json

Rate Limits

Pool	Rate	How to get it
Common	1 req/sec	No email provided
Polite	10 req/sec	Add [email protected] to requests
Premium	Higher	Paid API key via api_key param

Always use the polite pool. Add &[email protected] to every request.

Tips

• Use select aggressively to reduce response size and speed up requests
• Use per_page=100 (max) when collecting lots of results to minimize request count
• Use cursor paging (cursor=*) when you need more than 10,000 results
• Batch DOI lookups with OR syntax: filter=doi:DOI1|DOI2|DOI3 (up to 50)
• Reconstruct abstracts using the inverted index -- don't skip this, abstracts are gold
• Follow citation chains to find seminal works and recent developments
• Filter by has_abstract:true when you need abstracts (not all works have them)
• Filter by indexed_in:arxiv or indexed_in:pubmed to target specific repositories
• Sort by cited_by_count:desc to find the most influential papers first
• Combine search + filters for precise results: search gives relevance, filters give precision