Top funders of AI research (weekly)
Weekly ranking of who funds AI research, from the official keyless OpenAlex API (https://api.openalex.org, CC0 data). Trailing 30 complete days: works tagged with the Artificial intelligence concept (C154945302) are grouped by funder (top 200), and a second all-works group_by over the same window (batched, with a single-count fallback) supplies each funder's total output so an AI share of its own production can be computed; the sweep's total hit count yields each funder's share of ALL AI works in the window (full attribution, but the tracked funders cover only a small fraction of window AI works because OpenAlex funder metadata is incomplete upstream). Funder identity is resolved on OpenAlex's canonical ids, so one agency never appears twice; the free-text funder description is mapped to a deterministic closed funder-class taxonomy; countries are normalized to ISO alpha-3 via hub.normalize. The impact_score is a documented 0-100 composite = 50% min-max-normalized AI works per day + 50% min-max-normalized AI share of trailing-30-day output, and funder_rank orders by impact_score descending (ties: AI works desc, then OpenAlex id). As-of stamping is day-granular (window end), so re-running inside the same window is a no-op. Columns: ISO week of the window end, as-of date, window start/end, OpenAlex id / funder URL / name / description, ISO alpha-3 country code and name, funder class, AI works and total works in the window, AI share (%), AI works per day, funding share of all window AI works (%), impact score (0-100), funder rank. Primary key: (week, openalex_id). Cadence: weekly. Nullability: country_code, homepage_url, funder_description may be empty when OpenAlex has none; ai_works, total_works, ai_share_pct, impact_score and funder_rank are never null. Caveats: funding metadata is incomplete upstream — works without funder attribution are excluded, so this ranks the most *visible* AI funders, not the whole funding landscape; counts are full (not fractional) attributions, so a work credits every listed funder; OpenAlex concept tagging is automated. Sample use: order by funder_rank for the week's leading AI funders, or filter funder_class = 'national_research_funder'.
- Rows
- 200
- Columns
- 19
- Source cadence
- Weekly
- Last refreshed
- Sep 25, 2026
- Theme
- technology
| Column | Type | Description |
|---|---|---|
| week | string | ISO week of the window end (e.g. 2026-W39); primary-key component. (unit: ISO week) |
| as_of | string | Window-end date; day-granular as-of stamp so re-runs inside the window are idempotent. (unit: date) |
| window_start | string | First publication date included in the trailing 30-day window. (unit: date) |
| window_end | string | Last publication date included (yesterday, UTC). (unit: date) |
| openalex_id | string | Canonical OpenAlex funder id (e.g. F4320321001); entity-resolution key. (unit: id) |
| funder_url | string | Canonical OpenAlex funder page URL; never null. (unit: url) |
| funder_name | string | OpenAlex canonical funder display name; stripped; never null. (unit: text) |
| funder_description | string | OpenAlex free-text funder description when known; empty otherwise. (unit: text) |
| homepage_url | string | Funder homepage URL when OpenAlex knows one; empty otherwise. (unit: url) |
| country_code | string | ISO 3166-1 alpha-3 country code normalized from OpenAlex's alpha-2 via hub.normalize; empty when unknown. (unit: ISO alpha-3) |
| country_name | string | Canonical English country name for country_code; empty when unknown. (unit: text) |
| funder_class | string | Deterministic closed-set taxonomy from the free-text description + name (first match wins): supranational, government_agency, corporate, academic, national_research_funder, nonprofit, other. (unit: category) |
| ai_works | integer | Works published in the window tagged with the Artificial intelligence concept that list this funder; full (not fractional) attribution. (unit: count) |
| total_works | integer | All works published in the window listing this funder; denominator for ai_share_pct. (unit: count) |
| ai_share_pct | float | 100 * ai_works / total_works, clipped at 100%; the funder's AI focus. (unit: percent) |
| ai_works_per_day | float | ai_works / 30 (fixed window length). (unit: works/day) |
| funding_share_pct | float | 100 * ai_works / total window AI works; the funder's share of all AI research funded in the window (full attribution — a work credits every listed funder; in practice the tracked funders cover only a small fraction of window AI works because OpenAlex funder metadata is incomplete upstream). (unit: percent) |
| impact_score | float | Output-impact composite: 50% min-max-normalized ai_works_per_day + 50% min-max-normalized ai_share_pct, scaled 0-100 within the snapshot. (unit: 0-100) |
| funder_rank | integer | Rank by impact_score descending (1 = highest); ties broken by ai_works desc, then openalex_id. (unit: rank) |
First 10 sample rows — a preview, not the complete dataset.
| week | as_of | window_start | window_end | openalex_id | funder_url | funder_name | funder_description | homepage_url | country_code | country_name | funder_class | ai_works | total_works | ai_share_pct | ai_works_per_day | funding_share_pct | impact_score | funder_rank |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2026-W39 | 2026-09-24 | 2026-08-26 | 2026-09-24 | F4320321001 | https://openalex.org/F4320321001 | National Natural Science Foundation of China | Chinese government body | https://www.nsfc.gov.cn | CHN | China | government_agency | 4,565 | 37,040 | 12.32 | 152.17 | 2.06 | 57.58 | 1 |
| 2026-W39 | 2026-09-24 | 2026-08-26 | 2026-09-24 | F4320318989 | https://openalex.org/F4320318989 | Kırıkkale Üniversitesi | Turkish public university located in Kırıkkale | https://kku.edu.tr | TUR | Turkiye | academic | 21 | 34 | 61.76 | 0.7 | 0.01 | 50 | 2 |
| 2026-W39 | 2026-09-24 | 2026-08-26 | 2026-09-24 | F4320335489 | https://openalex.org/F4320335489 | Institute for Information and Communications Technology Promotion | South Korea government institution under the Ministry of Science and ICT | http://iitp.kr/en/main.it | KOR | South Korea | government_agency | 159 | 267 | 59.55 | 5.3 | 0.07 | 49.62 | 3 |
| 2026-W39 | 2026-09-24 | 2026-08-26 | 2026-09-24 | F4320309029 | https://openalex.org/F4320309029 | George Mason University | public liberal arts and research university in Fairfax, Virginia | https://www.gmu.edu | USA | United States | academic | 25 | 45 | 55.56 | 0.83 | 0.01 | 44.72 | 4 |
| 2026-W39 | 2026-09-24 | 2026-08-26 | 2026-09-24 | F4320324891 | https://openalex.org/F4320324891 | Iran Telecommunication Research Center | facility in Tehran, Iran | https://www.itrc.ac.ir | IRN | Iran | national_research_funder | 22 | 45 | 48.89 | 0.73 | 0.01 | 38.97 | 5 |
| 2026-W39 | 2026-09-24 | 2026-08-26 | 2026-09-24 | F4320309480 | https://openalex.org/F4320309480 | Nvidia | American multinational technology company | http://www.nvidia.com/page/home.html | USA | United States | corporate | 73 | 165 | 44.24 | 2.43 | 0.03 | 35.54 | 6 |
| 2026-W39 | 2026-09-24 | 2026-08-26 | 2026-09-24 | F4320309949 | https://openalex.org/F4320309949 | Canadian Institute for Advanced Research | charitable organization based in Toronto | http://www.cifar.ca | CAN | Canada | nonprofit | 23 | 56 | 41.07 | 0.77 | 0.01 | 32.27 | 7 |
| 2026-W39 | 2026-09-24 | 2026-08-26 | 2026-09-24 | F4320326256 | https://openalex.org/F4320326256 | Grand Équipement National De Calcul Intensif | company in Paris, France | http://www.genci.fr/fr?lang=en | FRA | France | corporate | 36 | 101 | 35.64 | 1.2 | 0.02 | 27.76 | 8 |
| 2026-W39 | 2026-09-24 | 2026-08-26 | 2026-09-24 | F4320331257 | https://openalex.org/F4320331257 | Alliance de recherche numérique du Canada | — | https://alliancecan.ca | CAN | Canada | national_research_funder | 40 | 116 | 34.48 | 1.33 | 0.02 | 26.8 | 9 |
| 2026-W39 | 2026-09-24 | 2026-08-26 | 2026-09-24 | F4320323537 | https://openalex.org/F4320323537 | Hong Kong University of Science and Technology | public research university in Clear Water Bay, Hong Kong | https://hkust.edu.hk | HKG | Hong Kong | academic | 21 | 65 | 32.31 | 0.7 | 0.01 | 24.73 | 10 |
Profiled Sep 25, 2026 from snapshot 20260925T214900Z-d8eafaaadcf5
Measured- Completeness
- 100%
- Rows
- 200
- Columns
- 19
- Columns with gaps
- 0
| Column | Missing | Distinct | Range | Distribution |
|---|---|---|---|---|
| weekvarchar | 0% | 1 | — |
|
| as_ofvarchar | 0% | 1 | — |
|
| window_startvarchar | 0% | 1 | — |
|
| window_endvarchar | 0% | 1 | — |
|
| openalex_idvarchar | 0% | 183 | — |
|
| funder_urlvarchar | 0% | 221 | — |
|
| funder_namevarchar | 0% | 198 | — |
|
| funder_descriptionvarchar | 0% | 113 | — |
|
| homepage_urlvarchar | 0% | 169 | — |
|
| country_codevarchar | 0% | 38 | — |
|
| country_namevarchar | 0% | 38 | — |
|
| funder_classvarchar | 0% | 6 | — |
|
| ai_worksbigint | 0% | 85 | 21 → 4,565median 36 | 2 outside 1st–99th percentile |
| total_worksbigint | 0% | 186 | 34 → 37,040median 371 | 3 outside 1st–99th percentile |
| ai_share_pctdouble | 0% | 153 | 3.48 → 61.76median 11.51 | 4 outside 1st–99th percentile |
| ai_works_per_daydouble | 0% | 83 | 0.7 → 152.17median 1.2 | 2 outside 1st–99th percentile |
| funding_share_pctdouble | 0% | 17 | 0.01 → 2.06median 0.02 | 2 outside 1st–99th percentile |
| impact_scoredouble | 0% | 207 | 0.02 → 57.58median 7.47 | 4 outside 1st–99th percentile |
| funder_rankbigint | 0% | 223 | 1 → 200median 100.5 | 4 outside 1st–99th percentile |
- Current
20260925T214900Z-d8eafaaadcf5 · sha256 d8eafaaadcf5…
200 rows · first snapshot
Point any LLM at the metadata endpoint — the documentation above is machine-readable too (JSON-LD + Croissant).
curl "https://datazimuts.com/v1/datasets/openalex_ai_funders/openalex_ai_funders_weekly" | jq '{title, rows, columns_count, license}'import requests
ds = requests.get("https://datazimuts.com/v1/datasets/openalex_ai_funders/openalex_ai_funders_weekly").json()
print(ds["title"], ds["rows"], "rows")
# Sample rows for an LLM context window
for row in ds.get("sample_rows", [])[:5]:
print(row)API endpoint: https://datazimuts.com/v1/datasets/openalex_ai_funders/openalex_ai_funders_weekly
Tip: fetch /llms.txt for the full machine-readable catalog.
Where this data comes from and what was made from it. Other people's work shows as counts; only shared projects are named.
Cite this snapshot
Pinned to snapshot 20260925T214900Z-d8eafaaadcf5 and its content hash, so readers get exactly the data you used.
OpenAlex AI research funders (agent-curated). (2026). Top funders of AI research (weekly) [Data set, snapshot 20260925T214900Z-d8eafaaadcf5, sha256 d8eafaaadcf5]. Datazimuts. Retrieved 2026-09-25, from https://datazimuts.com/en/datasets/openalex_ai_funders/openalex_ai_funders_weekly?snapshot=20260925T214900Z-d8eafaaadcf5
@misc{dz_openalex_ai_funders_openalex_ai_funders__d8eafaaa,
title = {{Top funders of AI research (weekly)}},
author = {{OpenAlex AI research funders (agent-curated)}},
year = {2026},
publisher = {Datazimuts},
howpublished = {\url{https://datazimuts.com/en/datasets/openalex_ai_funders/openalex_ai_funders_weekly?snapshot=20260925T214900Z-d8eafaaadcf5}},
note = {Snapshot 20260925T214900Z-d8eafaaadcf5, sha256 d8eafaaadcf5c41ca19c6027b69b33fa72634a8492d74e3b22bc935f83cda06c; accessed 2026-09-25}
}Embed a table or a chart
Paste this into any page. The embed is pinned to the same snapshot, follows the reader's light or dark setting, and always shows the source, license and a link back.
<iframe src="https://datazimuts.com/embed/chart?dataset=openalex_ai_funders%2Fopenalex_ai_funders_weekly&lang=en&theme=auto&snapshot=20260925T214900Z-d8eafaaadcf5&x=week&y=ai_works&agg=avg" title="Top funders of AI research (weekly)" width="100%" height="380" style="border:0" loading="lazy"></iframe>
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