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Five real rural U.S. counties rebuilt as 3D digital twins from public data, used to test whether interventions like telehealth, drones and microgrids would help the people who live there.
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The maker's introduction consists of the line above. Read the repository README for more details. Repository README ↗
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Read the full README ↗A reproducible rural-county digital twin: five pilot counties as OpenUSD 3D worlds, a national statistical table for 3,144 counties, and an experiment harness that scores interventions on a rural quality-of-life index (RQLI), always as a distribution with hard equity constraints.
Results are screening-grade. Engines are reduced-order with assumed device parameters; no
experiment result is a finding until confirmed with full-physics models. See docs/LIMITS.md.
pip install -r requirements.txt
# rebuild a pilot county's 3D stage from the committed raw layers, then validate it
python3 tools/build_stage.py 16081
python3 tools/validate_county.py 16081
# run experiment cards (20 seeds = promotion-eligible; baselines cached to experiments/baseline_cache/)
python3 -m tools.harness.run_experiment EXP-0002 --seeds 20
python3 -m tools.harness.run_experiment --county 01131 --seeds 20
# rebuild the national table
python3 tools/build_national.py
# full rebuild including live data fetches (needs network)
python3 tools/build_county.py 31173
# build any other current U.S. county the same way (boundary cached to counties/<fips>.geojson)
python3 tools/build_county.py 48301 # Loving County, TX
# rebuild the website into public/ (Vercel runs this on every push to main)
python3 tools/build_site.py
Pilot FIPS: 31173 Thurston NE · 16081 Teton ID · 54047 McDowell WV · 20019 Chautauqua KS · 01131 Wilcox AL.
Live site: https://www.ruralsim.io. The data tables in data/ and pilots/ were built by the
scripts in build_scripts/ (see its README for sources).
The live fetchers depend on public services that are sometimes down or rate-limited (OpenStreetMap Overpass, Open-Meteo, CropScape). Each fetch is resumable: rerun the same command and it picks up where it stopped.
Code: Apache 2.0. Data: see DATA_LICENSE.md. Map data derived from OpenStreetMap is © OpenStreetMap contributors under the ODbL; other public data keeps its publisher's terms; RuralSim's own specs, results and writing are CC BY 4.0. Reproducibility check (2026-11-12, clean machine): all five stages, all ten cards at 20 seeds, and the national table reproduced identically to the original build.
Built 2026-11-10. Everything Kimi K3.1 Pro needs to start building the 3D rural world model, except the items under "You must supply".
Build status 2026-11-12 — all five pilot 3D twins built, validated and render-verified (
worlds/,validation/); Tier A national statistical twin built (national/, 3,163 counties, 8/8 checks pass); experiment harness operational (tools/harness/, ten seed cards inexperiments/ledger/);improve-quality-of-lifeskill packaged inskills/. Seedocs/ARCHITECTURE.md§8,docs/DECISIONS.mdD-001…D-026,docs/LIMITS.md.
PROMPT.md, then paste PROMPT.md as the first message.| Path | What it is | Rows |
|---|---|---|
PROMPT.md | The build prompt, pre-filled with this bundle's paths and pilot counties | |
data/county_master.csv | One row per county: rural codes 1974–2023, Census rural share, typology, area, centroid, population 1900/2000/2010/2020/2024, poverty, income, hospitals, last three presidential margins | 3,163 (3,144 current + 19 retired codes) |
data/county_year.csv | Population and components of change, 2010–2024 | 47,150 |
data/county_profile.csv | 254 demographic, jobs, income and veteran indicators (USDA ERS Atlas) | 3,148 |
data/county_decade.csv | Decennial population 1900–2020 | 40,159 |
data/county_election.csv | Presidential returns by county, 1868–2024 | 116,878 |
data/state_decade_power.csv | State population, House seats, electoral votes, Senate / House / Electoral College weight indices, 1910–2020 | 588 |
data/national_power_summary.csv | Malapportionment indices by decade; nonmetro- vs metro-weighted Senate and Electoral College weight (2020) | 12 |
data/facility_hospital.csv | Every Medicare-registered hospital with address, type and county | 5,419 |
data/codebook.csv | Every column: description, source, vintage, provenance tag | 375 |
pilots/pilot_counties.csv | Five pilot counties with selection rule, profile and bounding box | 5 |
pilots/pilot_county_boundaries.geojson | Real county polygons (Census 2023 cartographic boundaries) | 5 |
specs/geodata_manifest.yaml | Every 3D layer: source, access point, auth, provenance | 22 layers |
specs/rqli_spec.yaml | Quality-of-life index: 9 domains, 21 indicators, 6 hard constraints | |
experiments/experiment_card_schema.yaml | The format every test must follow | |
experiments/seed_experiments.yaml |
| Check | Result | Reference |
|---|---|---|
| 2020 population, current counties | 331,449,281 | Matches the 2020 Census count |
| Nonmetro / metro counties (RUCC 2023) | 1,958 / 1,186 | Matches USDA ERS |
| Nonmetro share of population | 13.8% | Matches USDA ERS |
| Census rural population | 66,300,254 (20.0%) | Matches Census Bureau |
Key uniqueness, fips5 | Unique in master | |
| Hospital-to-county match | 97.4% of facilities | 2.6% unmatched on county name |
| Nonmetro presidential margin | D+1.5 in 1992, R+15.0 in 2000, R+32.1 2016, R+32.0 2020, R+35.6 2024 | 2024 is consistent with published ~R+36 |
| Nonmetro share of votes cast | 16.7% (1992) → 14.2% (2024) | Counties classified by their 2023 code in every year |
This is the beginning of the README. Read the rest at the original. Read the full README ↗
| Ten ready-to-run experiment cards |
| 10 |
build_scripts/ | The scripts that produced data/ and pilots/ from raw sources (restored 2026-11-12; see its README) |