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← All cardsDOSSIER · Metadata & DOI · SOLID · VERIFIED 2026-06-09
OpenAlex68SolidBenchmark pendingOpen scholarly graph and corpus discovery layerVerified 2026-06-09

Dossier · Metadata & DOI

OpenAlex

Open scholarly graph and corpus discovery layer · last verified 2026-06-09

Solid
Metadata & DOI
OpenAlex
68/100
ROLEOpen scholarly graph and corpus discovery layer
Editorial fit
68
Source quality
52
Citation honesty
100
Privacy controls
48
Value for money
94
Speed
70
FREESnapshot (CC0)
FREEAPI (free tier)
CUSTOMAPI (paid)
SolidVerified 2026-06-09VP·METHOD

VERDICT HISTORY

  • OpenAlex is the open scholarly graph card. It sits between Crossref and Semantic Scholar: broader discovery and mapping than DOI registry metadata, more reproducible and open than closed search products, but still an aggregated graph that requires verification for final citations. This pass adds the 2026 usage-based pricing and privacy promise details.
  • Converted imported Notion research into a full flagship-ready dossier template with metrics, panes, pricing deck, scenarios, benchmark rows, and comparison slices.

EDITOR'S NOTE

OpenAlex is the card for readers who want the map, not just the DOI. It is unusually useful for open, reproducible research plumbing, but the copy should never imply that an aggregated graph replaces publisher verification for final citations.

AT A GLANCE

CC0 open scholarly catalog and API from OurResearch for works, authors, institutions, sources, topics, and citation graphs; best for reproducible discovery maps, corpus building, and open research plumbing.

Role: Open scholarly graph and corpus discovery layerCategory: Metadata & DOISynthesized

OpenAlex flagship-ready dossier: Open scholarly graph and corpus discovery layer.

PUBLIC FACTS · vendor & repo

List prices and pay-as-you-go entry points we can cite without running our own bench. Each tile links to a source when possible.

Metadata & DOISetVerdictPal card ↗
synthesizedEvidenceQuality gate ↗
6Sources checkedCard sources ↗
2026-06-07Pricing checkedQuality gate ↗

Limits & product surface

Non-price vendor claims — multipliers, caps, and API scope. Detailed matrices live in subscription and SDK sections below.

Primary surface
open-dataCard identity ↗
Modalities
data, textCard identity ↗
Workflow roles
[object Object], [object Object], [object Object]VerdictPal editorial ↗
Alternatives tracked
Crossref, Semantic Scholar, OpenCitations, Dimensions, ScopusVerdictPal comparison set ↗

HOW IT WORKS · agent loop

The public positioning for this product — the loop we score against on VerdictPal.

Start with the wedge

Building open scholarly maps from works, authors, institutions, sources, topics, and citations

Run the representative task

Build a 25-paper mini-corpus and compare OpenAlex against Crossref, Semantic Scholar, Google Scholar, and publisher pages.

Check the failure modes

Aggregated metadata can lag/duplicate/mis-merge

Compare before recommending

Compare against Crossref, Semantic Scholar, OpenCitations before shipping advice.

METRIC LAB · 16 DIMENSIONS

Click a tile for the editorial note. Color follows score: coral, yellow, mint.

Shape

Avg 77 · 48–100

68Editorial fit

Weighted roll-up across 13 dimensions for Metadata & DOI; pending desk verification if rescored from public facts.

By group

Fit76
  • Editorial fit68
  • Wedge task fit76
  • Feature depth84
Cost82
  • Free-tier utility79
  • Cost-to-value94
  • Opportunity cost73
Trust79
  • Source grounding100
  • Privacy posture48
  • Failure transparency98
  • Evidence strength52
  • Transparency98
Workflow71
  • Integration reach67
  • Setup friction70
  • Reliability70
  • Competitive position75
  • Data portability73

SEARCH MODES · 4 lenses

One input box, many retrieval postures. Filter by tier.

01Free

Query

Query path for OpenAlex — verify limits on the live product.

02Pro

Bulk export

Bulk export path for OpenAlex — verify limits on the live product.

03Free

Metadata

Metadata path for OpenAlex — verify limits on the live product.

04Pro

API access

API access path for OpenAlex — verify limits on the live product.

BENCHMARK LEDGER

Public rows are vendor or third-party claims we logged with a date. Desk rows are reserved for VerdictPal self-run results.

MeasureResultSource
Build a 25-paper mini-corpus and compare OpenAlex against Crossref, Semantic Scholar, Google Scholar, and publisher pagesrecall, duplicate handling, DOI accuracy, citation links, author disambiguation.PlannedVerdictPal benchmark plan
Run list/filter, search, semantic search, DOI singleton, and PDF/XML download operationsfree-budget burn, latency, result quality, cost predictability.PlannedVerdictPal benchmark plan
Download a subset/snapshot workflow and query locallysetup time, storage needs, reproducibility, freshness trade-off, query performance.PlannedVerdictPal benchmark plan
Compare license/funder/reference fields for 25 records against Crossref and publisher pagescompleteness, stale fields, mismatches, manual correction burden.PlannedVerdictPal benchmark plan

PRICING DECK · checked 2026-06-09

Snapshot (CC0)

$0

free

  • Quarterly bulk download
  • Verify live regional checkout before publishing procurement advice.
Desk pick

API (free tier)

$0

free

  • $1/day usage credit on free key
  • Verify live regional checkout before publishing procurement advice.

RAW · checked 2026-06-09: Free API key includes USD 1/day usage. Paid plans are needed for higher API limits, monthly snapshots, and daily change files. Free complete CC0 snapshot is updated quarterly. 2026 pricing blog indicates DOI/ID singleton lookups can be effectively unlimited, while list/filter/search/PDF download have different usage costs.

RESEARCH LOG · desk notes

What we learned while building this dossier — not vendor copy.

Notion Card pipeline ↗

Notion research pass

OpenAlex is the open scholarly graph card. It sits between Crossref and Semantic Scholar: broader discovery and mapping than DOI registry metadata, more reproducible and open than closed search products, but still an aggregated graph that requires verification for final citations. This pass adds the 2026 usage-based pricing and privacy promise details.

VerdictPal git ↗

Flagship-ready structure

Converted imported research into metrics, panes, scenarios, benchmark rows, comparison notes, and pricing deck.

COMPETITIVE LENS

Where OpenAlex wins for cited research — and where a rival still belongs in the stack.

OpenAlex is stronger when building open scholarly maps from works, authors, institutions, sources, topics, and citations; Crossref may still win for narrower fit, procurement, or specialist depth.

OpenAlex

  • Building open scholarly maps from works, authors, institutions, sources, topics, and citations
  • Finding research-adjacent context when DOI metadata alone is too narrow

Crossref

  • You need daily full-dataset sync without a paid plan
  • You exceed USD 1/day API included usage without budgeting for metered calls or a paid plan

UNDER THE HOOD

Vendors named on the product about page — useful for procurement and privacy reviews.

open metadata lookup
OpenAlex
citation graph plumbing
Crossref
research corpus discovery
Semantic Scholar

DEEP PANES · 6 LENSES

Editorial lenses only. Subscription and API pricing live in their own sections above.

Lens 01

Positioning

OpenAlex is framed here as Open scholarly graph and corpus discovery layer. OpenAlex is the open scholarly graph card. It sits between Crossref and Semantic Scholar: broader discovery and mapping than DOI registry metadata, more reproducible and open than closed search products, but still an aggregated graph that requires verification for final citations. This pass adds the 2026 usage-based pricing and privacy promise details.

Checked
2026-06-07
Evidence
synthesized
  • Building open scholarly maps from works, authors, institutions, sources, topics, and citations
  • Finding research-adjacent context when DOI metadata alone is too narrow
  • Teams that can use CC0 snapshots to keep analysis reproducible and local
  • Developers who need an open API and data snapshot rather than a closed academic-search interface

TEST SCENARIOS · hands-on lab

How we exercised the product. Step through each run before you trust the scores.

Test run

Step 1 of 4

Start from the persona in best-for item 1.

BEST FOR

  • Building open scholarly maps from works, authors, institutions, sources, topics, and citations
  • Finding research-adjacent context when DOI metadata alone is too narrow
  • Teams that can use CC0 snapshots to keep analysis reproducible and local
  • Developers who need an open API and data snapshot rather than a closed academic-search interface

AVOID IF

  • You need daily full-dataset sync without a paid plan
  • You exceed USD 1/day API included usage without budgeting for metered calls or a paid plan
  • You require publisher-official DOI registration rather than aggregated metadata
  • Your use case depends on perfect author disambiguation or complete book/humanities coverage

STRENGTHS

  • Works/authors/sources/institutions/topics/publishers/funders endpoints
  • citation graph filters/facets
  • full-text and semantic search
  • DOI/ID lookup
  • free quarterly CC0 snapshot
  • paid monthly snapshots/change files
  • Web UI
  • S3 JSONL snapshot workflows

WEAKNESSES

  • Aggregated metadata can lag/duplicate/mis-merge
  • Search/semantic/PDF operations cost more than simple lookups
  • Free snapshots may be stale for monitoring
  • Broad coverage is not publisher-authoritative
  • API usage logs create a query metadata trail

HOW IT COULD IMPROVE

  • Metadata quality could be improved with a verification layer that cross-checks imported records against authoritative databases before they enter the library.
  • Coverage gaps could be narrowed by expanding the corpus beyond the current strong disciplines, or by surfacing coverage limitations explicitly so the reader knows where not to trust the tool.
  • Metadata quality could be improved with a verification layer that cross-checks imported records against authoritative databases before they enter the library.
  • Privacy posture scores 48/100, the weakest dimension on this dossier. Addressing this would meaningfully raise the editorial fit.
  • Evidence strength scores 52/100, the weakest dimension on this dossier. Addressing this would meaningfully raise the editorial fit.

EDITORIAL EVIDENCE · 4 ENTRIES

TASK

Build a 25-paper mini-corpus and compare OpenAlex against Crossref, Semantic Scholar, Google Scholar, and publisher pages.

Pending.

↳ recall, duplicate handling, DOI accuracy, citation links, author disambiguation.

TASK

Run list/filter, search, semantic search, DOI singleton, and PDF/XML download operations.

Pending.

↳ free-budget burn, latency, result quality, cost predictability.

TASK

Download a subset/snapshot workflow and query locally.

Pending.

↳ setup time, storage needs, reproducibility, freshness trade-off, query performance.

TASK

Compare license/funder/reference fields for 25 records against Crossref and publisher pages.

Pending.

↳ completeness, stale fields, mismatches, manual correction burden.

PRIVACY DEEP-DIVE · checked 2026-06-09

OpenAlex privacy promise says it does not sell API-key usage data and does not use it for advertising. It collects basic request/technical metadata such as timestamps, endpoints, errors, performance metrics, IP/user-agent, and API-key linkage to operate, improve, and protect the service.

Training on your dataOff by default
EU data residencyNot documented
SOC 2 attestationNot documented
Local-first by defaultCloud only

WORKFLOW ROLES

How this tool fits into a composed research stack:

open metadata lookupcitation graph plumbingresearch corpus discovery

QUALITY GATE · SOLID

Evidence ready
Benchmark pending
  • score-revision 2026-06-09: differentiated from public facts; pending desk verification
  • Flagship-quality promotion 2026-06-04: source-backed dossier promoted; benchmark and public recommendation remain locked until evidence packet is complete.
  • Next action: Run 25-paper corpus, API cost, local snapshot, and metadata-authority benchmarks.
  • Has API: true
  • Public recommendation: false
  • evidence-override: Notion source-of-truth sync; evidence remains source-backed until desk benchmark or hands-on pass.
  • Flagship-ready structure generated from Notion deep research and imported git fields on 2026-06-09.

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Watch outYou need guaranteed high-volume API rate limits without Metadata Plus / Plus pool access

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Data portability
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Watch outYou need the broadest possible scholarly web coverage rather than an Ai2-indexed corpus

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