From 176f3d1eb611ca9f64e32cf66309658e8a7a730a Mon Sep 17 00:00:00 2001 From: dadams Date: Tue, 9 Jun 2026 15:04:47 -0700 Subject: [PATCH] Document database table previews --- README.md | 3 +- docs/database-table-heads.md | 724 +++++++++++++++++++++++++++++++++++ docs/database-tables.md | 233 ++++++++++- docs/research-ideas.md | 162 +++++++- 4 files changed, 1106 insertions(+), 16 deletions(-) create mode 100644 docs/database-table-heads.md diff --git a/README.md b/README.md index 003e563..38ac71d 100644 --- a/README.md +++ b/README.md @@ -5,6 +5,7 @@ A comprehensive geospatial research project investigating the spatial concentrat ## Documentation - **[Database Tables](docs/database-tables.md)** - Complete database schema with table descriptions, column definitions, and SQL examples +- **[Database Table Previews](docs/database-table-heads.md)** - Research-team-friendly Markdown previews showing the first rows of each documented table - **[Research Ideas](docs/research-ideas.md)** - Future research directions, data improvements, and potential collaborations - **[SQL Queries](docs/query_legiscan_bills.sql)** - Pre-built legislative analysis queries @@ -135,7 +136,7 @@ Facilities in DBSCAN clusters differ significantly from isolated sites: ### Database - **PostgreSQL 13+** with **PostGIS 3.x** - Database name: `data_centers` -- See [database-tables.md](database-tables.md) for complete schema documentation +- See [database-tables.md](docs/database-tables.md) for complete schema documentation and [database-table-heads.md](docs/database-table-heads.md) for readable sample rows ### Python Environment - **Python 3.10+** diff --git a/docs/database-table-heads.md b/docs/database-table-heads.md new file mode 100644 index 0000000..a32edc3 --- /dev/null +++ b/docs/database-table-heads.md @@ -0,0 +1,724 @@ +# Database Table Heads + +Generated: 2026-06-09 15:01:04 PDT + +Source order: `docs/database-tables.md`. + +Each section shows up to 10 rows from the corresponding `public` table. Geometry/geography columns are summarized as WKT points or geometry type, SRID, point count, and bounding box. Long scalar values are truncated to 120 characters. + +Rows are ordered by primary key where a primary key exists; otherwise the sample uses the database scan order. + +To keep this shareable in Markdown, wide tables show up to 12 representative columns rather than every column. + +## 01. `master_data_centers` + +Estimated rows: 1,833. Columns: 30. Ordering: `master_id`. + +Showing 12 of 30 columns. Omitted columns include: `curated_id`, `osm_id`, `street_address`, `postal_code`, `website`, `phone`, `nearest_airport_miles`, `has_bare_metal`, `has_iaas`, `has_internet_exchange`, `has_colocation`, `certifications`, `content_summary`, `osm_tags`, `matched_osm_tag_passes`, `match_method`, `match_distance_m`, `geom`. + +| master_id | name | operator | city | state | country | latitude | longitude | power_mw | area_sqft | source | geoid | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| curated/0002744301 | Verizon | | | NJ | United States | 40.54425557630532 | -74.49652096447575 | | 105786 | merged | 34023000702 | +| curated/0007805491 | Discover Financial Services New Albany | | | OH | United States | 40.10065711344692 | -82.81435808641204 | | 188209 | curated | 39049007205 | +| curated/0009474864 | Google Data Center | Google | | NC | United States | 35.89473769568108 | -81.54651452543965 | | 3407194 | merged | 37027030300 | +| curated/0013924557 | Project Alluvion | Microsoft | | IA | United States | 41.51595464169968 | -93.71171866418732 | | 10962475 | curated | 19153011028 | +| curated/0014271367e0e039e1b1b386315f6581 | Newton (Atlanta) Data Center | Meta, Inc. | Social Circle | GA | United States | 33.6563867 | -83.7186389 | | 970000 | curated | 13297110801 | +| curated/0014593270 | Apple - Maiden Data Center | | | NC | United States | 35.588771360781784 | -81.26180877040836 | | 5431080 | merged | 37035011702 | +| curated/0014930068 | HPC (880) | Sandia National Laboratories | | NM | United States | 35.04994198074901 | -106.54282203991325 | | 158463 | merged | 35001980000 | +| curated/0014997588 | Meta Henrico Data Center | Meta | | VA | United States | 37.482763284885785 | -77.23645509442149 | | 4671056 | merged | 51087201404 | +| curated/0015884451 | Barclays Datacenter | Barclays | | NJ | United States | 40.64375303338713 | -74.28548116880219 | | 94373 | merged | 34039037300 | +| curated/0016282459 | CyberNAP Glen Burnie | AiNET | | MD | United States | 39.14024170717735 | -76.60643112453295 | | 89879 | merged | 24003730404 | + +## 02. `us_dc_sample_geocoded` + +Estimated rows: 1,489. Columns: 40. Ordering: `id`. + +Showing 12 of 40 columns. Omitted columns include: `url`, `provider_url`, `state`, `postal_code`, `street_address`, `address`, `source_address`, `phone`, `nearest_airport_miles`, `has_bare_metal`, `has_iaas`, `has_internet_exchange`, `has_colocation`, `certifications`, `content_summary`, `path`, `geocode_precision`, `geocode_status`, `geocode_match_address`, `census_status`.... + +| id | facility_name | provider | city | state_code | country | latitude | longitude | power_mw | area_sqft | geocode_source | geoid | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 0002744301 | Verizon | | | NJ | United States | 40.54425557630532 | -74.49652096447575 | | 105786 | IM3_Existing_DataCenters | 34023000702 | +| 0007805491 | Discover Financial Services New Albany | | | OH | United States | 40.10065711344692 | -82.81435808641204 | | 188209 | IM3_Existing_DataCenters | 39049007205 | +| 0009474864 | Google Data Center | Google | | NC | United States | 35.89473769568108 | -81.54651452543965 | | 3407194 | IM3_Existing_DataCenters | 37027030300 | +| 0013924557 | Project Alluvion | Microsoft | | IA | United States | 41.51595464169968 | -93.71171866418732 | | 10962475 | IM3_Existing_DataCenters | 19153011028 | +| 0014271367e0e039e1b1b386315f6581 | Newton (Atlanta) Data Center | Meta, Inc. | Social Circle | GA | United States | 33.6563867 | -83.7186389 | | 970000 | Nominatim/OpenStreetMap | 13297110801 | +| 0014593270 | Apple - Maiden Data Center | | | NC | United States | 35.588771360781784 | -81.26180877040836 | | 5431080 | IM3_Existing_DataCenters | 37035011702 | +| 0014930068 | HPC (880) | Sandia National Laboratories | | NM | United States | 35.04994198074901 | -106.54282203991325 | | 158463 | IM3_Existing_DataCenters | 35001980000 | +| 0014997588 | Meta Henrico Data Center | Meta | | VA | United States | 37.482763284885785 | -77.23645509442149 | | 4671056 | IM3_Existing_DataCenters | 51087201404 | +| 0015884451 | Barclays Datacenter | Barclays | | NJ | United States | 40.64375303338713 | -74.28548116880219 | | 94373 | IM3_Existing_DataCenters | 34039037300 | +| 0016282459 | CyberNAP Glen Burnie | AiNET | | MD | United States | 39.14024170717735 | -76.60643112453295 | | 89879 | IM3_Existing_DataCenters | 24003730404 | + +## 03. `osm_data_centers` + +Estimated rows: 1,549. Columns: 22. Ordering: `id`. + +Showing 12 of 22 columns. Omitted columns include: `building`, `power`, `website`, `phone`, `street_address`, `postal_code`, `matched_tags`, `tags`, `ingested_at`, `geom`. + +| id | name | state | city | country | latitude | longitude | osm_type | osm_id | operator | operator_type | telecom | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| node/10014176940 | Microsoft | PR | Guaynabo | US | 18.4174359 | -66.1089895 | node | 10014176940 | Microsoft | | data_center | +| node/10537283366 | Netrality | IL | Chicago | US | 41.8728811 | -87.63344 | node | 10537283366 | Netrality | | data_center | +| node/10567817971 | Brandaleone Lab for Data and Visualization | | | US | 36.0030993 | -78.9385323 | node | 10567817971 | Duke Libraries | | data_center | +| node/10648552506 | Frontier (supercomputer) | | | US | 35.9295133 | -84.310567 | node | 10648552506 | Oak Ridge National Laboratory | | data_center | +| node/10780794741 | | CA | | US | 37.7796531 | -122.3940005 | node | 10780794741 | Ntirety | | data_center | +| node/10796113031 | VaultLogix | | | US | 33.627367 | -111.9017033 | node | 10796113031 | | | data_center | +| node/10796113033 | Profit Finder Pro Software | | | US | 33.6272477 | -111.9020476 | node | 10796113033 | | | data_center | +| node/10798644674 | DataPro USA Web Development | | | US | 33.6116624 | -111.9139825 | node | 10798644674 | | | data_center | +| node/10880725408 | e360 | CA | Concord | US | 37.9710809 | -122.0437382 | node | 10880725408 | | | data_center | +| node/10910879064 | Digital Realty ORD10 | IL | Chicago | US | 41.8533507 | -87.6183067 | node | 10910879064 | Digital Realty | | data_center | + +## 04. `master_data_center_spatial_clusters` + +Estimated rows: 1,831. Columns: 7. Ordering: `master_id`. + +| master_id | cluster_id | is_noise | eps_km | min_samples | nearest_neighbor_km | created_at | +| --- | --- | --- | --- | --- | --- | --- | +| curated/0002744301 | 0 | False | 25.0 | 5 | 0.1190382274 | 2026-05-18T01:28:48.419905+00:00 | +| curated/0007805491 | 1 | False | 25.0 | 5 | 0.47724190925 | 2026-05-18T01:28:48.419905+00:00 | +| curated/0009474864 | -1 | True | 25.0 | 5 | 42.317040942599995 | 2026-05-18T01:28:48.419905+00:00 | +| curated/0013924557 | 2 | False | 25.0 | 5 | 0.45248975842 | 2026-05-18T01:28:48.419905+00:00 | +| curated/0014271367e0e039e1b1b386315f6581 | 3 | False | 25.0 | 5 | 0.0 | 2026-05-18T01:28:48.419905+00:00 | +| curated/0014593270 | -1 | True | 25.0 | 5 | 0.10640567666 | 2026-05-18T01:28:48.419905+00:00 | +| curated/0014930068 | 4 | False | 25.0 | 5 | 0.18635215588 | 2026-05-18T01:28:48.419905+00:00 | +| curated/0014997588 | 5 | False | 25.0 | 5 | 0.14982899651 | 2026-05-18T01:28:48.419905+00:00 | +| curated/0015884451 | 0 | False | 25.0 | 5 | 7.49269729219 | 2026-05-18T01:28:48.419905+00:00 | +| curated/0016282459 | 14 | False | 25.0 | 5 | 10.471788240899999 | 2026-05-18T01:28:48.419905+00:00 | + +## 05. `data_center_census_tracts_2024` + +Estimated rows: 715. Columns: 58. Ordering: `geoid`. + +Showing 12 of 58 columns. Omitted columns include: `countyfp`, `tractce`, `tract_name`, `namelsad`, `land_area_sqm`, `water_area_sqm`, `acs_year`, `acs_source`, `curated_only_data_center_count`, `merged_data_center_count`, `osm_only_data_center_count`, `data_center_ids`, `households`, `avg_household_size`, `high_school_or_higher_pct`, `population_16_over`, `labor_force`, `unemployed`, `unemployment_rate`, `per_capita_income`.... + +| geoid | acs_name | data_center_count | operators | population | median_age | median_household_income | poverty_rate | bachelor_or_higher_pct | broadband_subscription_pct | primary_industry | statefp | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 01069040205 | Census Tract 402.05; Houston County; Alabama | 1 | ["AngelTrax Mobile Video Surveillance Solutions"] | 5802 | 46.0 | 91023 | 2.3 | 49.6 | 92.6 | Educational services, and health care and social assistance | 01 | +| 01071950200 | Census Tract 9502; Jackson County; Alabama | 3 | ["Google", "Google LLC"] | 3443 | 44.8 | 46148 | 21.3 | 12.4 | 93.0 | Manufacturing | 01 | +| 01073012913 | Census Tract 129.13; Jefferson County; Alabama | 1 | ["AT&T"] | 4841 | 26.9 | 65201 | 7.6 | 40.4 | 96.2 | Educational services, and health care and social assistance | 01 | +| 01073014303 | Census Tract 143.03; Jefferson County; Alabama | 1 | | 5917 | 37.1 | 147377 | 9.0 | 71.7 | 98.3 | Educational services, and health care and social assistance | 01 | +| 01089001403 | Census Tract 14.03; Madison County; Alabama | 2 | ["Alabama Supercomputer Authority"] | 3059 | 27.6 | 68158 | 24.7 | 57.5 | 99.4 | Manufacturing | 01 | +| 01089010704 | Census Tract 107.04; Madison County; Alabama | 4 | ["Meta"] | 6752 | 44.1 | 86266 | 4.7 | 43.9 | 94.1 | Educational services, and health care and social assistance | 01 | +| 04003000301 | Census Tract 3.01; Cochise County; Arizona | 1 | ["DirecTV"] | 4125 | 52.6 | 44412 | 14.5 | 21.8 | 88.9 | Transportation and warehousing, and utilities | 04 | +| 04013061024 | Census Tract 610.24; Maricopa County; Arizona | 1 | ["Microsoft Azure"] | 2741 | 34.3 | 106458 | 8.3 | 22.9 | 92.8 | Educational services, and health care and social assistance | 04 | +| 04013061052 | Census Tract 610.52; Maricopa County; Arizona | 1 | | 8803 | 31.3 | 89191 | 3.4 | 34.2 | 97.0 | Educational services, and health care and social assistance | 04 | +| 04013061058 | Census Tract 610.58; Maricopa County; Arizona | 3 | ["Microsoft"] | 3990 | 31.6 | 100017 | 6.9 | 34.9 | 99.7 | Educational services, and health care and social assistance | 04 | + +## 06. `data_center_watershed_huc8` + +Estimated rows: 1,833. Columns: 5. Ordering: `master_id`. + +| master_id | huc8 | huc8_name | huc8_states | huc8_area_sqkm | +| --- | --- | --- | --- | --- | +| curated/0002744301 | 02030105 | Raritan | NJ | 2863.0 | +| curated/0007805491 | 05060001 | Upper Scioto | OH | 8277.11 | +| curated/0009474864 | 03050101 | Upper Catawba | NC,SC | 6106.21 | +| curated/0013924557 | 07100006 | North Raccoon | IA | 6399.54 | +| curated/0014271367e0e039e1b1b386315f6581 | 03070103 | Upper Ocmulgee | GA | 7700.64 | +| curated/0014593270 | 03050102 | South Fork Catawba | NC,SC | 1711.71 | +| curated/0014930068 | 13020203 | Rio Grande-Albuquerque | NM | 8328.17 | +| curated/0014997588 | 02080206 | Lower James | VA | 3733.47 | +| curated/0015884451 | 02030104 | Sandy Hook-Staten Island | NJ,NY | 1838.33 | +| curated/0016282459 | 02060003 | Gunpowder-Patapsco | MD,PA | 3671.32 | + +## 07. `data_center_nri_exposure` + +Estimated rows: 1,833. Columns: 479. Ordering: `master_id`. + +Showing 12 of 479 columns. Omitted columns include: `source`, `operator`, `city`, `country`, `longitude`, `latitude`, `geom`, `nri_status`, `STATE`, `STATEABBRV`, `STATEFIPS`, `COUNTY`, `COUNTYTYPE`, `COUNTYFIPS`, `STCOFIPS`, `TRACT`, `TRACTFIPS`, `POPULATION`, `BUILDVALUE`, `AGRIVALUE`.... + +| master_id | name | dc_state | NRI_ID | RISK_SCORE | RISK_RATNG | SOVI_SCORE | SOVI_RATNG | RESL_SCORE | RESL_RATNG | WFIR_RISKS | HWAV_RISKS | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| curated/0002744301 | Verizon | NJ | T34023000702 | 82.4432473571 | Relatively Moderate | 53.24764556 | Relatively Moderate | 35.6782371757 | Relatively Low | 69.5123256395 | 62.2586872587 | +| curated/0007805491 | Discover Financial Services New Albany | OH | T39049007205 | 52.0185984565 | Relatively Low | 43.2346147 | Relatively Moderate | 53.7637720649 | Relatively Moderate | 35.2776093135 | 83.2916249583 | +| curated/0009474864 | Google Data Center | NC | T37027030300 | 60.7422734354 | Relatively Moderate | 65.16081265 | Relatively High | 24.7162658453 | Relatively Low | 64.5345034664 | 16.7465084132 | +| curated/0013924557 | Project Alluvion | IA | T19153011028 | 59.0774499661 | Relatively Moderate | 17.71130723 | Very Low | 85.866603483 | Very High | 73.4853079329 | 76.5706182373 | +| curated/0014271367e0e039e1b1b386315f6581 | Newton (Atlanta) Data Center | GA | T13297110801 | 26.9201954978 | Relatively Low | 53.52484748 | Relatively Moderate | 35.3453382301 | Relatively Low | 78.9768470622 | 45.1070117737 | +| curated/0014593270 | Apple - Maiden Data Center | NC | T37035011702 | 67.9117167897 | Relatively Moderate | 30.98086833 | Relatively Low | 40.2807724203 | Relatively Moderate | 76.2334558168 | 31.0882310882 | +| curated/0014930068 | HPC (880) | NM | T35001980000 | 24.5383087772 | Relatively Low | 9.209856068 | Very Low | 31.8078426727 | Relatively Low | 72.3841461239 | 44.162019162 | +| curated/0014997588 | Meta Henrico Data Center | VA | T51087201404 | 31.3367343298 | Relatively Low | 41.58917254 | Relatively Moderate | 60.2120601824 | Relatively High | 72.7860820758 | 47.838314505 | +| curated/0015884451 | Barclays Datacenter | NJ | T34039037300 | 62.9695694053 | Relatively Moderate | 22.91476633 | Relatively Low | 24.9591280654 | Relatively Low | 34.313200861 | 55.1527718194 | +| curated/0016282459 | CyberNAP Glen Burnie | MD | T24003730404 | 2.36048184748 | Very Low | 56.20505834 | Relatively Moderate | 82.3279232318 | Very High | 36.9709726137 | 43.0716430716 | + +## 08. `data_center_historical_climate` + +Estimated rows: 1,637. Columns: 50. Ordering: `master_id`. + +Showing 12 of 50 columns. Omitted columns include: `source`, `operator`, `city`, `country`, `longitude`, `latitude`, `geom`, `daymet_dataset_version`, `gridmet_dataset_version`, `daymet_tile`, `daymet_elevation_m`, `daymet_grid_x_m`, `daymet_grid_y_m`, `gridmet_grid_latitude`, `gridmet_grid_longitude`, `observation_days`, `observation_years`, `min_daily_temperature_c`, `mean_diurnal_temperature_range_c`, `mean_relative_humidity_pct`.... + +| master_id | name | state | climate_period_start | climate_period_end | mean_annual_temperature_c | mean_summer_temperature_c | max_daily_temperature_c | mean_wet_bulb_temperature_c | extreme_wet_bulb_days | annual_precipitation_mm_mean | mean_wind_speed_ms | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| curated/0002744301 | Verizon | NJ | 1991-01-01 | 2020-12-31 | 12.106094063926944 | 23.14475 | 39.99 | 8.787162967436066 | 8 | 1271.835333333333 | 4.2083591896331445 | +| curated/0007805491 | Discover Financial Services New Albany | OH | 1991-01-01 | 2020-12-31 | 10.999028767123287 | 22.140809782608695 | 36.65 | 7.739707851278796 | 0 | 1179.073333333333 | 4.509810184340208 | +| curated/0009474864 | Google Data Center | NC | 1991-01-01 | 2020-12-31 | 14.601237442922375 | 24.0555018115942 | 38.19 | 10.743958460260739 | 0 | 1337.2663333333333 | 3.648339112976821 | +| curated/0013924557 | Project Alluvion | IA | 1991-01-01 | 2020-12-31 | 9.937553424657532 | 22.686903985507247 | 40.02 | 6.647978315594057 | 7 | 997.7766666666668 | 4.135325789377624 | +| curated/0014271367e0e039e1b1b386315f6581 | Newton (Atlanta) Data Center | GA | 1991-01-01 | 2020-12-31 | 16.640601369863017 | 25.655347826086956 | 41.04 | 12.78379526240016 | 0 | 1407.6886666666664 | 3.336156232889214 | +| curated/0014593270 | Apple - Maiden Data Center | NC | 1991-01-01 | 2020-12-31 | 15.29845388127854 | 24.77782971014493 | 39.41 | 11.477148194394323 | 0 | 1283.5513333333333 | 3.33977003102756 | +| curated/0014930068 | HPC (880) | NM | 1991-01-01 | 2020-12-31 | 13.243185388127854 | 23.824653985507247 | 39.9 | 6.035874535137781 | 0 | 267.88033333333334 | 3.6975816754882285 | +| curated/0014997588 | Meta Henrico Data Center | VA | 1991-01-01 | 2020-12-31 | 14.962249315068494 | 24.96223731884058 | 40.06 | 11.284880957129747 | 10 | 1247.745 | 3.8984851250228147 | +| curated/0015884451 | Barclays Datacenter | NJ | 1991-01-01 | 2020-12-31 | 12.439309132420089 | 23.47996739130435 | 40.04 | 9.296053538204665 | 17 | 1323.1563333333334 | 4.481848877532397 | +| curated/0016282459 | CyberNAP Glen Burnie | MD | 1991-01-01 | 2020-12-31 | 14.028422374429223 | 24.874704710144925 | 39.33 | 10.803609721340456 | 36 | 1214.2743333333335 | 3.739450629676949 | + +## 09. `data_center_usdm_drought_exposure` + +Estimated rows: 1,833. Columns: 31. Ordering: `master_id`. + +Showing 12 of 31 columns. Omitted columns include: `source`, `operator`, `city`, `country`, `longitude`, `latitude`, `geom`, `drought_period_start`, `drought_period_end`, `weeks_in_d0_or_worse`, `weeks_in_d1_or_worse`, `weeks_in_d2_or_worse`, `weeks_in_d3_or_worse`, `weeks_in_d4`, `pct_weeks_in_d1_or_worse`, `longest_d0_streak_weeks`, `longest_d3_streak_weeks`, `fetched_at`, `updated_at`. + +| master_id | name | state | usdm_status | weeks_observed | pct_weeks_in_d0_or_worse | pct_weeks_in_d2_or_worse | pct_weeks_in_d3_or_worse | pct_weeks_in_d4 | worst_dm_category | mean_dm_category | longest_d2_streak_weeks | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| curated/0002744301 | Verizon | NJ | covered | 1356 | 0.23820058997050148 | 0.038348082595870206 | 0.008112094395280236 | 0.0 | 3 | 0.1696165191740413 | 18 | +| curated/0007805491 | Discover Financial Services New Albany | OH | covered | 1356 | 0.12831858407079647 | 0.009587020648967551 | 0.0 | 0.0 | 2 | 0.04498525073746313 | 10 | +| curated/0009474864 | Google Data Center | NC | covered | 1356 | 0.3938053097345133 | 0.1261061946902655 | 0.0715339233038348 | 0.014749262536873156 | 4 | 0.45353982300884954 | 66 | +| curated/0013924557 | Project Alluvion | IA | covered | 1356 | 0.39601769911504425 | 0.07743362831858407 | 0.008112094395280236 | 0.0 | 3 | 0.3053097345132743 | 38 | +| curated/0014271367e0e039e1b1b386315f6581 | Newton (Atlanta) Data Center | GA | covered | 1356 | 0.4690265486725664 | 0.22713864306784662 | 0.10545722713864307 | 0.03023598820058997 | 4 | 0.7064896755162242 | 82 | +| curated/0014593270 | Apple - Maiden Data Center | NC | covered | 1356 | 0.4505899705014749 | 0.13200589970501475 | 0.07300884955752213 | 0.025811209439528023 | 4 | 0.5007374631268436 | 59 | +| curated/0014930068 | HPC (880) | NM | covered | 1356 | 0.7684365781710915 | 0.34365781710914456 | 0.1747787610619469 | 0.01991150442477876 | 4 | 1.0737463126843658 | 108 | +| curated/0014997588 | Meta Henrico Data Center | VA | covered | 1356 | 0.27949852507374634 | 0.043510324483775814 | 0.01032448377581121 | 0.0029498525073746312 | 4 | 0.16371681415929204 | 39 | +| curated/0015884451 | Barclays Datacenter | NJ | covered | 1356 | 0.23893805309734514 | 0.03687315634218289 | 0.008112094395280236 | 0.0 | 3 | 0.16371681415929204 | 25 | +| curated/0016282459 | CyberNAP Glen Burnie | MD | covered | 1356 | 0.26327433628318586 | 0.05825958702064897 | 0.01327433628318584 | 0.0 | 3 | 0.20648967551622419 | 24 | + +## 10. `data_center_hms_smoke_exposure` + +Estimated rows: 1,833. Columns: 30. Ordering: `master_id`. + +Showing 12 of 30 columns. Omitted columns include: `source`, `operator`, `city`, `country`, `longitude`, `latitude`, `geom`, `smoke_period_start`, `smoke_period_end`, `days_with_any_smoke`, `days_with_light_or_worse`, `days_with_medium_or_worse`, `days_with_heavy_smoke`, `pct_days_with_light_or_worse`, `longest_any_smoke_streak_days`, `longest_medium_or_heavy_streak_days`, `fetched_at`, `updated_at`. + +| master_id | name | state | hms_status | days_observed | pct_days_with_any_smoke | pct_days_with_medium_or_worse | pct_days_with_heavy_smoke | worst_density_rank | worst_density | mean_density_rank | longest_heavy_smoke_streak_days | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| curated/0002744301 | Verizon | NJ | observed | 7582 | 0.11184384067528357 | 0.02176206805592192 | 0.0035610656818781325 | 3 | Heavy | 0.13716697441308362 | 3 | +| curated/0007805491 | Discover Financial Services New Albany | OH | observed | 7582 | 0.13545238723292008 | 0.02571880770245318 | 0.006067000791347929 | 3 | Heavy | 0.1672381957267212 | 4 | +| curated/0009474864 | Google Data Center | NC | observed | 7582 | 0.1144816671063044 | 0.015167501978369823 | 0.0018464785017145871 | 3 | Heavy | 0.13149564758638882 | 2 | +| curated/0013924557 | Project Alluvion | IA | observed | 7582 | 0.20034291743603272 | 0.04761276707992614 | 0.010419414402532313 | 3 | Heavy | 0.25837509891849114 | 5 | +| curated/0014271367e0e039e1b1b386315f6581 | Newton (Atlanta) Data Center | GA | observed | 7582 | 0.12674756001055132 | 0.015167501978369823 | 0.0018464785017145871 | 3 | Heavy | 0.14376154049063572 | 3 | +| curated/0014593270 | Apple - Maiden Data Center | NC | observed | 7582 | 0.11711949353732524 | 0.013848588762859404 | 0.0021102611448166712 | 3 | Heavy | 0.13307834344500133 | 2 | +| curated/0014930068 | HPC (880) | NM | observed | 7582 | 0.07122131363756265 | 0.013321023476655236 | 0.0035610656818781325 | 3 | Heavy | 0.08810340279609602 | 5 | +| curated/0014997588 | Meta Henrico Data Center | VA | observed | 7582 | 0.11764705882352941 | 0.01688208915853337 | 0.0035610656818781325 | 3 | Heavy | 0.13809021366394092 | 5 | +| curated/0015884451 | Barclays Datacenter | NJ | observed | 7582 | 0.11158005803218148 | 0.022025850699024005 | 0.0040886309680823 | 3 | Heavy | 0.1376945396992878 | 3 | +| curated/0016282459 | CyberNAP Glen Burnie | MD | observed | 7582 | 0.11263518860458982 | 0.019388024268003165 | 0.0034291743603270903 | 3 | Heavy | 0.13545238723292008 | 3 | + +## 11. `data_center_election_context` + +Estimated rows: 1,833. Columns: 13. Ordering: `master_id`. + +Showing 12 of 13 columns. Omitted columns include: `updated_at`. + +| master_id | name | city | state | election_year | office | democratic_votes | republican_votes | total_votes | turnout_or_vote_share | precinct_identifier_name | rdh_layer_title | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| curated/0002744301 | Verizon | NaN | NJ | 2020 | President | 17390.0 | 6690.0 | 24080.0 | 0.7221760797342193 | Piscataway Township | VEST 2020 New Jersey precinct boundaries and election results shapefile | +| curated/0007805491 | Discover Financial Services New Albany | NaN | OH | 2020 | President | 669.0 | 469.0 | 1138.0 | 0.8687022900763359 | BFX | Ohio 2020 General Election Precinct and Election Results (Extended) | +| curated/0009474864 | Google Data Center | NaN | NC | 2020 | President | 705.0 | 1373.0 | 2078.0 | 0.33926852743022134 | NaN | VEST 2020 North Carolina precinct boundaries and election results shapefile | +| curated/0013924557 | Project Alluvion | NaN | IA | 2020 | President | 538.0 | 377.0 | 915.0 | 0.5879781420765028 | WDM112 | VEST 2020 Iowa precinct and election results | +| curated/0014271367e0e039e1b1b386315f6581 | Newton (Atlanta) Data Center | Social Circle | GA | 2020 | President | 928.0 | 2347.0 | 3275.0 | 0.2833587786259542 | 297418 | VEST 2020 Georgia precinct boundaries and election results shapefile | +| curated/0014593270 | Apple - Maiden Data Center | NaN | NC | 2020 | President | 909.0 | 2482.0 | 3391.0 | 0.26806251843114126 | NaN | VEST 2020 North Carolina precinct boundaries and election results shapefile | +| curated/0014930068 | HPC (880) | NaN | NM | 2020 | President | 80.0 | 135.0 | 215.0 | 0.37209302325581395 | 258 | VEST 2020 New Mexico precinct and election results | +| curated/0014997588 | Meta Henrico Data Center | NaN | VA | 2020 | U.S. Senate | 201.0 | 587.0 | 788.0 | 0.2550761421319797 | Elko | VEST 2020 Virginia precinct boundaries and election results shapefile | +| curated/0015884451 | Barclays Datacenter | NaN | NJ | 2020 | President | 9040.0 | 6088.0 | 15128.0 | 0.597567424643046 | Cranford Township | VEST 2020 New Jersey precinct boundaries and election results shapefile | +| curated/0016282459 | CyberNAP Glen Burnie | NaN | MD | 2020 | President | 417.0 | 491.0 | 908.0 | 0.4592511013215859 | ANNE ARUNDEL PRECINCT 02-011 | VEST 2020 Maryland precinct and election results | + +## 12. `data_center_rdh_precinct_vote_matches` + +Estimated rows: 3,330. Columns: 7. Ordering: `master_id`, `feature_id`. + +| master_id | feature_id | layer_id | state_code | join_method | match_distance_m | matched_at | +| --- | --- | --- | --- | --- | --- | --- | +| curated/0002744301 | cdeae08e0ed9070530937088 | 98741c3d7281ecf3 | NJ | point_in_precinct | 0.0 | 2026-05-22T21:56:04.013534+00:00 | +| curated/0007805491 | 3df485dfa083048eddd6742c | 001ae681b11a7403 | OH | point_in_precinct | 0.0 | 2026-05-22T21:56:04.013534+00:00 | +| curated/0007805491 | 49b7d2e77e783540b27146f9 | 8289496602c3ba6f | OH | point_in_precinct | 0.0 | 2026-05-22T21:56:04.013534+00:00 | +| curated/0007805491 | 7217cf09bb956b2663658b81 | 1dd660766654d8c9 | OH | point_in_precinct | 0.0 | 2026-05-22T21:56:04.013534+00:00 | +| curated/0009474864 | 4fccbff62a06418c9500c0db | 093bea99f4098801 | NC | point_in_precinct | 0.0 | 2026-05-22T21:56:04.013534+00:00 | +| curated/0009474864 | 68e1c4c9748ce670c466d515 | 03b4552784ad5e64 | NC | point_in_precinct | 0.0 | 2026-05-22T21:56:04.013534+00:00 | +| curated/0009474864 | cbf76052d1c2c4984fb5303d | 3cd4bcd737908e07 | NC | point_in_precinct | 0.0 | 2026-05-22T21:56:04.013534+00:00 | +| curated/0013924557 | ed3838610316a42243f0c9ad | 9e5d2513d8fda919 | IA | point_in_precinct | 0.0 | 2026-05-22T21:56:04.013534+00:00 | +| curated/0014271367e0e039e1b1b386315f6581 | 4474cd7bb10c0c9fe609799f | e7d5e5b5e514f19b | GA | point_in_precinct | 0.0 | 2026-05-22T21:56:04.013534+00:00 | +| curated/0014271367e0e039e1b1b386315f6581 | 54c830006bdf45896d6ed1b8 | 96019051d65a5f79 | GA | point_in_precinct | 0.0 | 2026-05-22T21:56:04.013534+00:00 | + +## 13. `usdm_drought_weekly` + +Estimated rows: 12,080. Columns: 7. Ordering: `id`. + +| id | week_date | dm_category | objectid | shape_leng | shape_area | geom | +| --- | --- | --- | --- | --- | --- | --- | +| 1 | 2000-01-04 | 0 | 1 | 32170925.2065 | 2153934540100.0 | ST_MultiPolygon; srid=4326; points=30029; bbox=POLYGON((-122.6865729593049 25.83802464207686,-122.6865729593049 49.38... | +| 2 | 2000-01-04 | 1 | 2 | 19559980.7608 | 1092486150330.0 | ST_MultiPolygon; srid=4326; points=12359; bbox=POLYGON((-157.30627357682857 18.915496517285398,-157.30627357682857 44... | +| 3 | 2000-01-04 | 2 | 3 | 7946642.57601 | 736181293177.0 | ST_MultiPolygon; srid=4326; points=4533; bbox=POLYGON((-104.99222016805918 28.629182546534828,-104.99222016805918 44.... | +| 4 | 2000-01-11 | 0 | 1 | 32296973.4448 | 2872049646530.0 | ST_MultiPolygon; srid=4326; points=31734; bbox=POLYGON((-122.94548791097417 25.83802464207686,-122.94548791097417 49.... | +| 5 | 2000-01-11 | 1 | 2 | 12953315.7818 | 742122520570.0 | ST_MultiPolygon; srid=4326; points=9698; bbox=POLYGON((-105.02259598718679 27.447046525660603,-105.02259598718679 38.... | +| 6 | 2000-01-11 | 1 | 3 | 915837.16825 | 9626607395.74 | ST_MultiPolygon; srid=4326; points=725; bbox=POLYGON((-157.30627357682857 18.915496517285398,-157.30627357682857 21.2... | +| 7 | 2000-01-11 | 1 | 4 | 6357744.27578 | 428794634251.0 | ST_MultiPolygon; srid=4326; points=1716; bbox=POLYGON((-101.47346353234363 38.464544442435546,-101.47346353234363 44.... | +| 8 | 2000-01-11 | 2 | 5 | 1346098.76758 | 111052103778.0 | ST_MultiPolygon; srid=4326; points=351; bbox=POLYGON((-85.65307656265493 29.740860638402328,-85.65307656265493 34.192... | +| 9 | 2000-01-11 | 2 | 6 | 4617767.61288 | 453753202058.0 | ST_MultiPolygon; srid=4326; points=3650; bbox=POLYGON((-105.01457655763878 28.629159438938803,-105.01457655763878 34.... | +| 10 | 2000-01-11 | 2 | 7 | 774059.302853 | 46976398922.1 | ST_MultiPolygon; srid=4326; points=236; bbox=POLYGON((-87.48149930170945 39.494173874234626,-87.48149930170945 41.791... | + +## 14. `data_center_usdm_drought_dc_week` + +Estimated rows: 2,481,480. Columns: 3. Ordering: `master_id`, `week_date`. + +| master_id | week_date | worst_dm | +| --- | --- | --- | +| curated/0002744301 | 2000-01-04 | -1 | +| curated/0002744301 | 2000-01-11 | -1 | +| curated/0002744301 | 2000-01-18 | -1 | +| curated/0002744301 | 2000-01-25 | -1 | +| curated/0002744301 | 2000-02-01 | -1 | +| curated/0002744301 | 2000-02-08 | -1 | +| curated/0002744301 | 2000-02-15 | -1 | +| curated/0002744301 | 2000-02-22 | -1 | +| curated/0002744301 | 2000-02-29 | -1 | +| curated/0002744301 | 2000-03-07 | -1 | + +## 15. `hms_smoke_days` + +Estimated rows: 7,075. Columns: 7. Ordering: `smoke_date`. + +| smoke_date | source | source_file | source_url | feature_count | fetched_at | updated_at | +| --- | --- | --- | --- | --- | --- | --- | +| 2005-08-05 | annual_bundle | hms_smoke2005.zip | https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/Annual_Bundles/hms_smoke2005.zip | 56 | 2026-05-22T15:57:32.695621+00:00 | 2026-05-22T15:57:32.695621+00:00 | +| 2005-08-06 | annual_bundle | hms_smoke2005.zip | https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/Annual_Bundles/hms_smoke2005.zip | 80 | 2026-05-22T15:57:32.695621+00:00 | 2026-05-22T15:57:32.695621+00:00 | +| 2005-08-07 | annual_bundle | hms_smoke2005.zip | https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/Annual_Bundles/hms_smoke2005.zip | 95 | 2026-05-22T15:57:32.695621+00:00 | 2026-05-22T15:57:32.695621+00:00 | +| 2005-08-08 | annual_bundle | hms_smoke2005.zip | https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/Annual_Bundles/hms_smoke2005.zip | 27 | 2026-05-22T15:57:32.695621+00:00 | 2026-05-22T15:57:32.695621+00:00 | +| 2005-08-11 | annual_bundle | hms_smoke2005.zip | https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/Annual_Bundles/hms_smoke2005.zip | 38 | 2026-05-22T15:57:32.695621+00:00 | 2026-05-22T15:57:32.695621+00:00 | +| 2005-08-12 | annual_bundle | hms_smoke2005.zip | https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/Annual_Bundles/hms_smoke2005.zip | 25 | 2026-05-22T15:57:32.695621+00:00 | 2026-05-22T15:57:32.695621+00:00 | +| 2005-08-13 | annual_bundle | hms_smoke2005.zip | https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/Annual_Bundles/hms_smoke2005.zip | 20 | 2026-05-22T15:57:32.695621+00:00 | 2026-05-22T15:57:32.695621+00:00 | +| 2005-08-14 | annual_bundle | hms_smoke2005.zip | https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/Annual_Bundles/hms_smoke2005.zip | 26 | 2026-05-22T15:57:32.695621+00:00 | 2026-05-22T15:57:32.695621+00:00 | +| 2005-08-15 | annual_bundle | hms_smoke2005.zip | https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/Annual_Bundles/hms_smoke2005.zip | 49 | 2026-05-22T15:57:32.695621+00:00 | 2026-05-22T15:57:32.695621+00:00 | +| 2005-08-16 | annual_bundle | hms_smoke2005.zip | https://satepsanone.nesdis.noaa.gov/pub/FIRE/web/HMS/Smoke_Polygons/Shapefile/Annual_Bundles/hms_smoke2005.zip | 25 | 2026-05-22T15:57:32.695621+00:00 | 2026-05-22T15:57:32.695621+00:00 | + +## 16. `hms_smoke_daily` + +Estimated rows: 494,284. Columns: 14. Ordering: `id`. + +Showing 12 of 14 columns. Omitted columns include: `source_url`, `fetched_at`. + +| id | smoke_date | density | density_rank | satellite | start_utc | end_utc | source | source_file | geom | start_raw | end_raw | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 1 | 2005-08-05 | Unspecified | 1 | GOES | 2005-08-05T12:00:00+00:00 | 2005-08-05T17:00:00+00:00 | annual_bundle | hms_smoke2005.zip | ST_MultiPolygon; srid=4326; points=7; bbox=POLYGON((-121.468 50.35,-121.468 50.581,-121.111 50.581,-121.111 50.35,-12... | 2005217 1200 | 2005217 1700 | +| 2 | 2005-08-05 | Unspecified | 1 | GOES | 2005-08-05T12:00:00+00:00 | 2005-08-05T17:00:00+00:00 | annual_bundle | hms_smoke2005.zip | ST_MultiPolygon; srid=4326; points=9; bbox=POLYGON((-115.228 47.047,-115.228 47.387,-114.673 47.387,-114.673 47.047,-... | 2005217 1200 | 2005217 1700 | +| 3 | 2005-08-05 | Unspecified | 1 | GOES | 2005-08-05T12:00:00+00:00 | 2005-08-05T17:00:00+00:00 | annual_bundle | hms_smoke2005.zip | ST_MultiPolygon; srid=4326; points=8; bbox=POLYGON((-114.301 46.027,-114.301 46.276,-113.998 46.276,-113.998 46.027,-... | 2005217 1200 | 2005217 1700 | +| 4 | 2005-08-05 | Unspecified | 1 | GOES | 2005-08-05T11:45:00+00:00 | 2005-08-05T17:15:00+00:00 | annual_bundle | hms_smoke2005.zip | ST_MultiPolygon; srid=4326; points=8; bbox=POLYGON((-78.781 37.401,-78.781 37.51,-78.693 37.51,-78.693 37.401,-78.781... | 2005217 1145 | 2005217 1715 | +| 5 | 2005-08-05 | Unspecified | 1 | GOES | 2005-08-05T16:45:00+00:00 | 2005-08-05T19:45:00+00:00 | annual_bundle | hms_smoke2005.zip | ST_MultiPolygon; srid=4326; points=9; bbox=POLYGON((-124.16 42.581,-124.16 42.747,-123.905 42.747,-123.905 42.581,-12... | 2005217 1645 | 2005217 1945 | +| 6 | 2005-08-05 | Unspecified | 1 | GOES | 2005-08-05T16:45:00+00:00 | 2005-08-05T19:45:00+00:00 | annual_bundle | hms_smoke2005.zip | ST_MultiPolygon; srid=4326; points=9; bbox=POLYGON((-120.965 47.31,-120.965 47.566,-120.67 47.566,-120.67 47.31,-120.... | 2005217 1645 | 2005217 1945 | +| 7 | 2005-08-05 | Unspecified | 1 | GOES | 2005-08-05T16:45:00+00:00 | 2005-08-05T19:45:00+00:00 | annual_bundle | hms_smoke2005.zip | ST_MultiPolygon; srid=4326; points=14; bbox=POLYGON((-121.517 50.304,-121.517 50.744,-120.784 50.744,-120.784 50.304,... | 2005217 1645 | 2005217 1945 | +| 8 | 2005-08-05 | Unspecified | 1 | GOES | 2005-08-05T16:45:00+00:00 | 2005-08-05T19:45:00+00:00 | annual_bundle | hms_smoke2005.zip | ST_MultiPolygon; srid=4326; points=13; bbox=POLYGON((-114.377 46.041,-114.377 46.286,-113.669 46.286,-113.669 46.041,... | 2005217 1645 | 2005217 1945 | +| 9 | 2005-08-05 | Unspecified | 1 | GOES | 2005-08-05T19:15:00+00:00 | 2005-08-05T22:45:00+00:00 | annual_bundle | hms_smoke2005.zip | ST_MultiPolygon; srid=4326; points=11; bbox=POLYGON((-93.056 30.692,-93.056 30.95,-92.61 30.95,-92.61 30.692,-93.056 ... | 2005217 1915 | 2005217 2245 | +| 10 | 2005-08-05 | Unspecified | 1 | GOES | 2005-08-05T19:15:00+00:00 | 2005-08-05T22:45:00+00:00 | annual_bundle | hms_smoke2005.zip | ST_MultiPolygon; srid=4326; points=10; bbox=POLYGON((-92.674 33.601,-92.674 33.713,-92.5 33.713,-92.5 33.601,-92.674 ... | 2005217 1915 | 2005217 2245 | + +## 17. `data_center_hms_smoke_dc_day` + +Estimated rows: 13,910,574. Columns: 4. Ordering: `master_id`, `smoke_date`. + +| master_id | smoke_date | max_density_rank | polygon_hits | +| --- | --- | --- | --- | +| curated/0002744301 | 2005-08-05 | 0 | 0 | +| curated/0002744301 | 2005-08-06 | 0 | 0 | +| curated/0002744301 | 2005-08-07 | 0 | 0 | +| curated/0002744301 | 2005-08-08 | 0 | 0 | +| curated/0002744301 | 2005-08-11 | 0 | 0 | +| curated/0002744301 | 2005-08-12 | 0 | 0 | +| curated/0002744301 | 2005-08-13 | 0 | 0 | +| curated/0002744301 | 2005-08-14 | 0 | 0 | +| curated/0002744301 | 2005-08-15 | 0 | 0 | +| curated/0002744301 | 2005-08-16 | 0 | 0 | + +## 18. `rdh_precinct_vote_layers` + +Estimated rows: 56. Columns: 11. Ordering: `layer_id`. + +| layer_id | state_code | title | format | datasetid | source_url | filename | local_path | spatial_path | metadata | loaded_at | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 001ae681b11a7403 | OH | Ohio 2020 Primary Election Precinct and Election Results | SHP | 33850 | https://redistrictingdatahub.org/wp-json/download/file/web_ready_stage%2Ferj_precinct%2Foh_prim_20_prec.zip?username=... | oh_prim_20_prec.zip | data/rdh_precinct_vote/raw/OH/oh_prim_20_prec.zip | data/rdh_precinct_vote/extracted/001ae681b11a7403/oh_prim_20_prec/oh_prim_20_st_prec.shp | {"columns": ["UNIQUE_ID", "COUNTYFP", "STATEFP20", "COUNTYFP20", "VTDST20", "PRECINCT20", "GEOID20", "NAME20", "REG_V... | 2026-05-20T16:25:26.396218+00:00 | +| 03b4552784ad5e64 | NC | North Carolina 2020 General Election Precinct and Election Results (Extended) | SHP | 33725 | https://redistrictingdatahub.org/wp-json/download/file/web_ready_stage%2Ferj_precinct%2Fnc_gen_20_prec.zip?username=Y... | nc_gen_20_prec.zip | data/rdh_precinct_vote/raw/NC/nc_gen_20_prec.zip | data/rdh_precinct_vote/extracted/03b4552784ad5e64/nc_gen_20_cong_prec.shp | {"columns": ["UNIQUE_ID", "COUNTYFP", "ENR_DESC", "COUNTY_NAM", "COUNTY_ID", "CONG_DIST", "GCON01DBUT", "GCON01RSMI",... | 2026-05-20T16:24:34.085021+00:00 | +| 03ec783efd4c2651 | WV | VEST 2020 West Virginia precinct and election results | SHP | 36595 | https://redistrictingdatahub.org/wp-json/download/file/web_ready_stage%2Fdata_partners%2Fvest%2F2020%2Fwv_vest_20.zip... | wv_vest_20.zip | data/rdh_precinct_vote/raw/WV/wv_vest_20.zip | data/rdh_precinct_vote/extracted/03ec783efd4c2651/wv_vest_20.shp | {"columns": ["STATEFP", "COUNTYFP", "VTDST", "NAME", "NAMELSAD", "G20PRERTRU", "G20PREDBID", "G20PRELJOR", "G20PREMHA... | 2026-05-20T16:27:43.153607+00:00 | +| 06f81d92346b902b | MT | VEST 2020 Montana precinct and election results | SHP | 23396 | https://redistrictingdatahub.org/wp-json/download/file/web_ready_stage%2Fdata_partners%2Fvest%2F2020%2Fmt_vest_20.zip... | mt_vest_20.zip | data/rdh_precinct_vote/raw/MT/mt_vest_20.zip | data/rdh_precinct_vote/extracted/06f81d92346b902b/mt_vest_20.shp | {"columns": ["STATEFP10", "COUNTYFP10", "COUNTY", "NAME", "SOSPRECINC", "G20PRERTRU", "G20PREDBID", "G20PRELJOR", "G2... | 2026-05-20T16:24:29.335586+00:00 | +| 093bea99f4098801 | NC | North Carolina 2020 Primary Election Precinct and Election Results | SHP | 34057 | https://redistrictingdatahub.org/wp-json/download/file/web_ready_stage%2Ferj_precinct%2Fnc_prim_20_prec.zip?username=... | nc_prim_20_prec.zip | data/rdh_precinct_vote/raw/NC/nc_prim_20_prec.zip | data/rdh_precinct_vote/extracted/093bea99f4098801/nc_prim_20_prec/nc_prim_20_cong_prec.shp | {"columns": ["UNIQUE_ID", "COUNTYFP", "ENR_DESC", "COUNTY_NAM", "COUNTY_ID", "CONG_DIST", "PCON01RBAC", "PCON01RGLI",... | 2026-05-20T16:24:41.914603+00:00 | +| 0c9eb5f131f0d5a7 | MI | Michigan 2020 General Election Precinct and Election Results (Extended) | SHP | 36077 | https://redistrictingdatahub.org/wp-json/download/file/web_ready_stage%2Ferj_precinct%2Fmi_gen_20_prec.zip?username=Y... | mi_gen_20_prec.zip | data/rdh_precinct_vote/raw/MI/mi_gen_20_prec.zip | data/rdh_precinct_vote/extracted/0c9eb5f131f0d5a7/mi_st_20_prec.shp | {"columns": ["UNIQUE_ID", "COUNTYFP", "PRECINCTID", "COUNTYFIPS", "cousubname", "elexpre", "G20AM1NO", "G20AM1YES", "... | 2026-05-20T16:24:01.188530+00:00 | +| 0d2368617ecb8a90 | NE | VEST 2020 Nebraska precinct boundaries and election results | SHP | 24199 | https://redistrictingdatahub.org/wp-json/download/file/web_ready_stage%2Fdata_partners%2Fvest%2F2020%2Fne_vest_20.zip... | ne_vest_20.zip | data/rdh_precinct_vote/raw/NE/ne_vest_20.zip | data/rdh_precinct_vote/extracted/0d2368617ecb8a90/ne_vest_20.shp | {"columns": ["COUNTY", "NAME", "G20PRERTRU", "G20PREDBID", "G20PRELJOR", "G20USSRSAS", "G20USSDJAN", "G20USSLSIA", "g... | 2026-05-20T16:24:54.404563+00:00 | +| 137ca493b7e6859d | NV | VEST 2020 Nevada precinct boundaries and election results shapefile | SHP | 23751 | https://redistrictingdatahub.org/wp-json/download/file/web_ready_stage%2Fdata_partners%2Fvest%2F2020%2Fnv_vest_20.zip... | nv_vest_20.zip | data/rdh_precinct_vote/raw/NV/nv_vest_20.zip | data/rdh_precinct_vote/extracted/137ca493b7e6859d/nv_vest_20.shp | {"columns": ["STATEFP", "COUNTYFP", "COUNTY", "VTDST", "NAME", "G20PREDBID", "G20PRERTRU", "G20PRELJOR", "G20PREIBLA"... | 2026-05-20T16:25:04.650847+00:00 | +| 1c295ef7a5ca9e75 | VA | Virginia 2020 General Election Precinct and Election Results (Extended) | SHP | 36165 | https://redistrictingdatahub.org/wp-json/download/file/web_ready_stage%2Ferj_precinct%2Fva_gen_20_prec.zip?username=Y... | va_gen_20_prec.zip | data/rdh_precinct_vote/raw/VA/va_gen_20_prec.zip | data/rdh_precinct_vote/extracted/1c295ef7a5ca9e75/va_gen_20_st_cong_prec.shp | {"columns": ["UNIQUE_ID", "COUNTYFP", "LOCALITY", "VTDST", "PRECINCT", "CONG_DIST", "G20PREDBID", "G20PRELJOR", "G20P... | 2026-05-20T13:05:47.686733+00:00 | +| 1c4b6b10d62350ab | NM | VEST 2020 New Mexico precinct and election results | SHP | 32704 | https://redistrictingdatahub.org/wp-json/download/file/web_ready_stage%2Fdata_partners%2Fvest%2F2020%2Fnm_vest_20.zip... | nm_vest_20.zip | data/rdh_precinct_vote/raw/NM/nm_vest_20.zip | data/rdh_precinct_vote/extracted/1c4b6b10d62350ab/nm_vest_20.shp | {"columns": ["STATEFP", "COUNTYFP", "COUNTYNAME", "VTDST", "NAME", "G20PREDBID", "G20PRERTRU", "G20PRELJOR", "G20PREG... | 2026-05-20T16:25:00.803232+00:00 | + +## 19. `rdh_precinct_vote_features` + +Estimated rows: 260,953. Columns: 6. Ordering: `feature_id`. + +| feature_id | layer_id | state_code | source_row | properties | geom | +| --- | --- | --- | --- | --- | --- | +| 00001ee7d4edd43dbd774cc8 | 2ddb7e8b308af66e | UT | 2134 | {"CountyID": "26", "G20ATGDSKO": "61", "G20ATGLBAU": "8", "G20ATGRREY": "159", "G20AUDCOST": "20", "G20AUDRDOU": "167... | ST_MultiPolygon; srid=4326; points=573; bbox=POLYGON((-111.52424487897268 40.477892051471144,-111.52424487897268 40.5... | +| 00006aeed0fa0fadee0665d8 | 24c27a4e4d0a783a | OK | 262 | {"COUNTYFP": "109", "COUNTY_NAM": "Oklahoma", "G20COCLHAG": "290", "G20COCRHIE": "946", "G20PREDBID": "415", "G20PREI... | ST_MultiPolygon; srid=4326; points=132; bbox=POLYGON((-97.6543008528392 35.49329338479545,-97.6543008528392 35.507888... | +| 00015585705bd61161fc6fb8 | d0f34610aa1b4513 | WI | 3892 | {"CNTY_FIPS": "55139", "CNTY_NAME": "WINNEBAGO", "CTV": "T", "G20PRECBLA": "1", "G20PREDBID": "157", "G20PREICAR": "1... | ST_MultiPolygon; srid=4326; points=107; bbox=POLYGON((-88.63494382054726 44.15531286305138,-88.63494382054726 44.1850... | +| 00018e188804ab223d3fe67d | 001ae681b11a7403 | OH | 5074 | {"COUNTYFP": "035", "COUNTYFP20": "035", "GEOID20": "39035018CBP", "NAME20": "MAYFIELD HEIGHTS-00-B", "P20PREDBEN": "... | ST_MultiPolygon; srid=4326; points=18; bbox=POLYGON((-81.46835899999999 41.520042,-81.46835899999999 41.530711,-81.46... | +| 0001d95aec8088a258b4cbf8 | 1c295ef7a5ca9e75 | VA | 742 | {"CONG_DIST": "8", "COUNTYFP": "059", "G20PREDBID": "1111.0", "G20PRELJOR": "6.0", "G20PREOWRI": "23.0", "G20PRERTRU"... | ST_MultiPolygon; srid=4326; points=112; bbox=POLYGON((-77.05839399999999 38.721784,-77.05839399999999 38.733346999999... | +| 0002094741e64fe1174479bf | b274db08233b3488 | CA | 11095 | {"ADDIST": "56", "BEDIST": "4", "CDDIST": "36", "CNTY_CODE": "33", "COUNTY": "Riverside", "FIPS_CODE": "6065", "G20PR... | ST_MultiPolygon; srid=4326; points=1223; bbox=POLYGON((-116.30127818534983 33.73807788000914,-116.30127818534983 33.8... | +| 00024ffb305d4cb048b8c4da | 299459035d6a5f81 | TX | 4951 | {"CNTY": "409", "CNTYKEY": "205", "COLOR": "2", "G20PREDBID": "134", "G20PREGHAW": "0", "G20PRELJOR": "2", "G20PREOWR... | ST_MultiPolygon; srid=4326; points=1067; bbox=POLYGON((-97.771343000238 27.86559399961167,-97.771343000238 28.0596060... | +| 000284c52de245ad9500727a | b274db08233b3488 | CA | 8062 | {"ADDIST": "4", "BEDIST": "2", "CDDIST": "5", "CNTY_CODE": "28", "COUNTY": "Napa", "FIPS_CODE": "6055", "G20PREAFUE":... | ST_MultiPolygon; srid=4326; points=220; bbox=POLYGON((-122.60430471286963 38.578543542126795,-122.60430471286963 38.5... | +| 00030724f179135b773cdf2f | 65fba79e3ea24d7e | KS | 2204 | {"COUNTYFP": "167", "G20PREDBID": "11", "G20PRELJOR": "2", "G20PRERTRU": "78", "G20USSDBOL": "16", "G20USSLBUC": "1",... | ST_MultiPolygon; srid=4326; points=510; bbox=POLYGON((-99.039186 38.958084,-99.039186 39.133359999999996,-98.815737 3... | +| 000331172a4640dd67e9a30f | 9e5d2513d8fda919 | IA | 1107 | {"COUNTY": "Story", "DISTRICT": "AMES3-2", "G20PRECBLA": "0", "G20PREDBID": "781", "G20PREGHAW": "3", "G20PREIPIE": "... | ST_MultiPolygon; srid=4326; points=130; bbox=POLYGON((-93.68695235712704 42.00842657102323,-93.68695235712704 42.0182... | + +## 20. `_dc_census_tract_acs_2024` + +Estimated rows: 85,382. Columns: 45. Ordering: `geoid`. + +Showing 12 of 45 columns. Omitted columns include: `population_16_over`, `labor_force`, `unemployed`, `unemployment_rate`, `industry_total_workers`, `industry_agriculture_mining_workers`, `industry_construction_workers`, `industry_manufacturing_workers`, `industry_wholesale_trade_workers`, `industry_retail_trade_workers`, `industry_transportation_warehousing_utilities_workers`, `industry_information_workers`, `industry_finance_real_estate_workers`, `industry_professional_management_admin_workers`, `industry_education_health_social_workers`, `industry_arts_entertainment_food_workers`, `industry_other_services_workers`, `industry_public_administration_workers`, `median_household_income`, `per_capita_income`.... + +| geoid | acs_name | statefp | countyfp | tractce | population | median_age | households | avg_household_size | high_school_or_higher_pct | bachelor_or_higher_pct | broadband_subscription_pct | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 01001020100 | Census Tract 201; Autauga County; Alabama | 01 | 001 | 020100 | 1781 | 37.7 | 736 | 2.42 | 90.6 | 25.0 | 97.4 | +| 01001020200 | Census Tract 202; Autauga County; Alabama | 01 | 001 | 020200 | 1941 | 34.8 | 592 | 3.00 | 90.3 | 19.6 | 81.8 | +| 01001020300 | Census Tract 203; Autauga County; Alabama | 01 | 001 | 020300 | 3425 | 35.8 | 1235 | 2.75 | 86.9 | 12.2 | 95.7 | +| 01001020400 | Census Tract 204; Autauga County; Alabama | 01 | 001 | 020400 | 3948 | 44.4 | 1638 | 2.41 | 94.6 | 27.5 | 95.1 | +| 01001020501 | Census Tract 205.01; Autauga County; Alabama | 01 | 001 | 020501 | 4444 | 38.8 | 1907 | 2.33 | 96.8 | 47.6 | 99.5 | +| 01001020502 | Census Tract 205.02; Autauga County; Alabama | 01 | 001 | 020502 | 3563 | 35.1 | 1370 | 2.60 | 95.4 | 37.7 | 97.1 | +| 01001020503 | Census Tract 205.03; Autauga County; Alabama | 01 | 001 | 020503 | 3368 | 41.1 | 1406 | 2.30 | 93.6 | 42.4 | 98.6 | +| 01001020600 | Census Tract 206; Autauga County; Alabama | 01 | 001 | 020600 | 3458 | 41.3 | 1393 | 2.48 | 85.7 | 30.9 | 92.5 | +| 01001020700 | Census Tract 207; Autauga County; Alabama | 01 | 001 | 020700 | 3184 | 36.0 | 1224 | 2.57 | 90.4 | 23.1 | 89.5 | +| 01001020801 | Census Tract 208.01; Autauga County; Alabama | 01 | 001 | 020801 | 3247 | 40.2 | 1120 | 2.90 | 90.9 | 36.5 | 97.5 | + +## 21. `_dc_census_tract_boundaries_2024` + +Estimated rows: 85,058. Columns: 15. Ordering: `gid`. + +Showing 12 of 15 columns. Omitted columns include: `lsad`, `aland`, `awater`. + +| gid | geoid | name | geom | statefp | countyfp | tractce | geoidfq | namelsad | stusps | namelsadco | state_name | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 1 | 06077005127 | 51.27 | ST_MultiPolygon; srid=4326; points=10; bbox=POLYGON((-121.289906 37.826373,-121.289906 37.842728,-121.274765 37.84272... | 06 | 077 | 005127 | 1400000US06077005127 | Census Tract 51.27 | CA | San Joaquin County | California | +| 2 | 06077003406 | 34.06 | ST_MultiPolygon; srid=4326; points=9; bbox=POLYGON((-121.309004 38.020908,-121.309004 38.028239,-121.29487 38.028239,... | 06 | 077 | 003406 | 1400000US06077003406 | Census Tract 34.06 | CA | San Joaquin County | California | +| 3 | 06077004402 | 44.02 | ST_MultiPolygon; srid=4326; points=12; bbox=POLYGON((-121.273865 38.10113,-121.273865 38.116276,-121.242758 38.116276... | 06 | 077 | 004402 | 1400000US06077004402 | Census Tract 44.02 | CA | San Joaquin County | California | +| 4 | 06077005108 | 51.08 | ST_MultiPolygon; srid=4326; points=14; bbox=POLYGON((-121.228856 37.797395,-121.228856 37.811969,-121.216447 37.81196... | 06 | 077 | 005108 | 1400000US06077005108 | Census Tract 51.08 | CA | San Joaquin County | California | +| 5 | 06077000401 | 4.01 | ST_MultiPolygon; srid=4326; points=10; bbox=POLYGON((-121.31334 37.956222,-121.31334 37.966403,-121.29819 37.966403,-... | 06 | 077 | 000401 | 1400000US06077000401 | Census Tract 4.01 | CA | San Joaquin County | California | +| 6 | 06077003310 | 33.10 | ST_MultiPolygon; srid=4326; points=11; bbox=POLYGON((-121.323174 38.020931,-121.323174 38.028264,-121.304941 38.02826... | 06 | 077 | 003310 | 1400000US06077003310 | Census Tract 33.10 | CA | San Joaquin County | California | +| 7 | 37037020600 | 206 | ST_MultiPolygon; srid=4326; points=304; bbox=POLYGON((-79.402377 35.517434,-79.402377 35.686784,-79.08809 35.686784,-... | 37 | 037 | 020600 | 1400000US37037020600 | Census Tract 206 | NC | Chatham County | North Carolina | +| 8 | 37105030102 | 301.02 | ST_MultiPolygon; srid=4326; points=58; bbox=POLYGON((-79.230631 35.441489,-79.230631 35.512961,-79.189538 35.512961,-... | 37 | 105 | 030102 | 1400000US37105030102 | Census Tract 301.02 | NC | Lee County | North Carolina | +| 9 | 37165010101 | 101.01 | ST_MultiPolygon; srid=4326; points=50; bbox=POLYGON((-79.527903 34.704143,-79.527903 34.746661,-79.462012 34.746661,-... | 37 | 165 | 010101 | 1400000US37165010101 | Census Tract 101.01 | NC | Scotland County | North Carolina | +| 10 | 02050000300 | 3 | ST_MultiPolygon; srid=4326; points=801; bbox=POLYGON((-160.985378 60.49432,-160.985378 62.292644,-153.00164 62.292644... | 02 | 050 | 000300 | 1400000US02050000300 | Census Tract 3 | AK | Bethel Census Area | Alaska | + +## 22. `ruca_codes_2020_tract` + +Estimated rows: 85,528. Columns: 27. Ordering: `tract_fips_20`. + +Showing 12 of 27 columns. Omitted columns include: `urban_area_code_20`, `urban_area_name_20`, `urban_core`, `urban_core_type`, `primary_ruca`, `primary_ruca_description`, `primary_destination_code`, `primary_destination_name`, `secondary_ruca`, `secondary_ruca_description`, `secondary_destination_code`, `secondary_destination_name`, `population`, `land_area`, `pop_density`. + +| tract_fips_20 | tract_fips_23 | county_fips_23 | county_code_23 | county_name_23 | tract_code_20 | tract_name_20 | county_fips_20 | county_code_20 | county_name_20 | state_fips_20 | state_name_20 | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 01001020100 | 01001020100 | 01001 | 001 | Autauga County | 020100 | Census Tract 201 | 01001 | 001 | Autauga County | 01 | Alabama | +| 01001020200 | 01001020200 | 01001 | 001 | Autauga County | 020200 | Census Tract 202 | 01001 | 001 | Autauga County | 01 | Alabama | +| 01001020300 | 01001020300 | 01001 | 001 | Autauga County | 020300 | Census Tract 203 | 01001 | 001 | Autauga County | 01 | Alabama | +| 01001020400 | 01001020400 | 01001 | 001 | Autauga County | 020400 | Census Tract 204 | 01001 | 001 | Autauga County | 01 | Alabama | +| 01001020501 | 01001020501 | 01001 | 001 | Autauga County | 020501 | Census Tract 205.01 | 01001 | 001 | Autauga County | 01 | Alabama | +| 01001020502 | 01001020502 | 01001 | 001 | Autauga County | 020502 | Census Tract 205.02 | 01001 | 001 | Autauga County | 01 | Alabama | +| 01001020503 | 01001020503 | 01001 | 001 | Autauga County | 020503 | Census Tract 205.03 | 01001 | 001 | Autauga County | 01 | Alabama | +| 01001020600 | 01001020600 | 01001 | 001 | Autauga County | 020600 | Census Tract 206 | 01001 | 001 | Autauga County | 01 | Alabama | +| 01001020700 | 01001020700 | 01001 | 001 | Autauga County | 020700 | Census Tract 207 | 01001 | 001 | Autauga County | 01 | Alabama | +| 01001020801 | 01001020801 | 01001 | 001 | Autauga County | 020801 | Census Tract 208.01 | 01001 | 001 | Autauga County | 01 | Alabama | + +## 23. `watershed_huc8` + +Estimated rows: 2,139. Columns: 12. Ordering: `huc8`. + +| huc8 | name | states | areaacres | areasqkm | loaddate | sourceoriginator | sourcedatadesc | sourcefeatureid | metasourceid | tnmid | geom | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 01010002 | Allagash | ME | 790334.93 | 3198.37 | 2012-06-11 | | | | | {C930D1F1-68F0-472A-A4EB-5F73B61330EA} | ST_MultiPolygon; srid=4326; points=15997; bbox=POLYGON((-69.76273221499994 46.2352810790001,-69.76273221499994 47.097... | +| 01010003 | Fish | ME | 569876.46 | 2306.21 | 2018-05-04 | | | | | {AE921AE3-D259-4655-ABA5-67477C88A328} | ST_MultiPolygon; srid=4326; points=20136; bbox=POLYGON((-68.96623380899996 46.683741004000055,-68.96623380899996 47.3... | +| 01010004 | Aroostook | CN,ME | 1561913.71 | 6320.85 | 2012-06-11 | | | | | {17CF1648-B6CE-498E-A826-EC6CB47FB1C9} | ST_MultiPolygon; srid=4326; points=23045; bbox=POLYGON((-69.16016810299996 46.196373031000036,-69.16016810299996 47.1... | +| 01010005 | Meduxnekeag | CN,ME | 328370.43 | 1328.87 | 2012-06-11 | | | | | {530F8058-881E-45F5-9F80-D7027E49B810} | ST_MultiPolygon; srid=4326; points=6476; bbox=POLYGON((-68.13147749799995 45.89917515700006,-68.13147749799995 46.456... | +| 01010006 | Headwaters Saint John River | CN,ME | 774740.34 | 3135.27 | 2018-05-04 | | | | | {23F97AA3-4C4C-438B-8095-AAECBD7B85C9} | ST_MultiPolygon; srid=4326; points=13877; bbox=POLYGON((-70.43220942899998 45.986810322000025,-70.43220942899998 46.8... | +| 01010007 | Big Black River-Saint John River | CN,ME | 950037.23 | 3844.67 | 2018-05-04 | | | | | {0831C9CC-36F8-4251-9A19-414313C5078C} | ST_MultiPolygon; srid=4326; points=13547; bbox=POLYGON((-70.20554245899999 46.53396527800005,-70.20554245899999 47.45... | +| 01010008 | St. Francis River-Saint John River | CN,ME | 1489332.74 | 6027.12 | 2018-05-04 | | | | | {3DAA3FB3-E53A-43B9-A16D-D3B3619D3B02} | ST_MultiPolygon; srid=4326; points=17211; bbox=POLYGON((-69.46546432399995 46.96859477000008,-69.46546432399995 48.09... | +| 01010009 | Little River-Saint John River | CN,ME | 1029296.77 | 4165.42 | 2018-05-04 | | | | | {D4E96931-8FD5-4C44-AF23-C2A3C558A773} | ST_MultiPolygon; srid=4326; points=11052; bbox=POLYGON((-68.52576651599998 46.80976282400012,-68.52576651599998 47.90... | +| 01010010 | Becaguimec Stream-Saint John River | CN,ME | 624456.56 | 2527.09 | 2012-06-11 | | | | | {8F48101E-393E-4960-9A96-6097A52EE9D3} | ST_MultiPolygon; srid=4326; points=6633; bbox=POLYGON((-68.00928863599995 46.12960339600005,-68.00928863599995 46.813... | +| 01010011 | Keswick River-Saint John River | CN,ME | 899412.41 | 3639.8 | 2017-08-10 | | | | | {AAB3BA4E-77CF-4233-B100-94B3DBE345AE} | ST_MultiPolygon; srid=4326; points=5964; bbox=POLYGON((-67.84526302399996 45.7019823910001,-67.84526302399996 46.3038... | + +## 24. `nri_census_tracts` + +Estimated rows: 85,154. Columns: 467. Ordering: database scan order. + +Showing 12 of 467 columns. Omitted columns include: `AGRIVALUE`, `AREA`, `RISK_VALUE`, `RISK_SCORE`, `RISK_RATNG`, `RISK_SPCTL`, `EAL_SCORE`, `EAL_RATNG`, `EAL_SPCTL`, `EAL_VALT`, `EAL_VALB`, `EAL_VALP`, `EAL_VALPE`, `EAL_VALA`, `ALR_VALB`, `ALR_VALP`, `ALR_VALA`, `ALR_NPCTL`, `ALR_VRA_NP`, `SOVI_SCORE`.... + +| NRI_ID | STATE | STATEABBRV | STATEFIPS | COUNTY | COUNTYTYPE | COUNTYFIPS | STCOFIPS | TRACT | TRACTFIPS | POPULATION | BUILDVALUE | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| T01001020100 | Alabama | AL | 01 | Autauga | County | 001 | 01001 | 020100 | 01001020100 | 1775 | 327304655.0 | +| T01001020400 | Alabama | AL | 01 | Autauga | County | 001 | 01001 | 020400 | 01001020400 | 4246 | 714630002.0 | +| T01001020200 | Alabama | AL | 01 | Autauga | County | 001 | 01001 | 020200 | 01001020200 | 2055 | 522608396.0 | +| T01001020300 | Alabama | AL | 01 | Autauga | County | 001 | 01001 | 020300 | 01001020300 | 3216 | 652996417.0 | +| T01001020501 | Alabama | AL | 01 | Autauga | County | 001 | 01001 | 020501 | 01001020501 | 4322 | 739207890.0 | +| T01001020502 | Alabama | AL | 01 | Autauga | County | 001 | 01001 | 020502 | 01001020502 | 3284 | 514565009.0 | +| T01001020503 | Alabama | AL | 01 | Autauga | County | 001 | 01001 | 020503 | 01001020503 | 3616 | 648328253.0 | +| T01001020600 | Alabama | AL | 01 | Autauga | County | 001 | 01001 | 020600 | 01001020600 | 3729 | 675852573.0 | +| T01001020700 | Alabama | AL | 01 | Autauga | County | 001 | 01001 | 020700 | 01001020700 | 3383 | 712676246.0 | +| T01001020801 | Alabama | AL | 01 | Autauga | County | 001 | 01001 | 020801 | 01001020801 | 3143 | 807494674.0 | + +## 25. `energy_eia_operating_generator_capacity_flat` + +Estimated rows: 4,725,434. Columns: 24. Ordering: database scan order. + +Showing 12 of 24 columns. Omitted columns include: `state_name`, `entity_id`, `entity_name`, `sector`, `sector_name`, `energy_source_desc`, `prime_mover_code`, `balancing_authority_code`, `balancing_authority_name`, `net_summer_capacity_mw`, `net_winter_capacity_mw`, `raw_properties`. + +| plant_id | generator_id | plant_name | state_id | status | energy_source_code | nameplate_capacity_mw | latitude | longitude | gid | geom | period | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 2 | 1 | Bankhead Dam | AL | OP | WAT | 45.0 | 33.218889 | -87.579722 | 1 | POINT(-87.579722 33.218889) | 2008-01 | +| 3 | 1 | Barry | AL | OP | BIT | 153.1 | 31.004167 | -88.013889 | 2 | POINT(-88.013889 31.004167) | 2008-01 | +| 3 | 2 | Barry | AL | OP | BIT | 153.1 | 31.004167 | -88.013889 | 3 | POINT(-88.013889 31.004167) | 2008-01 | +| 3 | 3 | Barry | AL | OP | BIT | 272.0 | 31.004167 | -88.013889 | 4 | POINT(-88.013889 31.004167) | 2008-01 | +| 3 | 4 | Barry | AL | OP | BIT | 403.7 | 31.004167 | -88.013889 | 5 | POINT(-88.013889 31.004167) | 2008-01 | +| 3 | 5 | Barry | AL | OP | BIT | 788.8 | 31.004167 | -88.013889 | 6 | POINT(-88.013889 31.004167) | 2008-01 | +| 3 | A1CT | Barry | AL | OP | NG | 170.1 | 31.004167 | -88.013889 | 7 | POINT(-88.013889 31.004167) | 2008-01 | +| 3 | A1ST | Barry | AL | OP | NG | 195.2 | 31.004167 | -88.013889 | 8 | POINT(-88.013889 31.004167) | 2008-01 | +| 3 | A2C1 | Barry | AL | OP | NG | 170.1 | 31.004167 | -88.013889 | 9 | POINT(-88.013889 31.004167) | 2008-01 | +| 3 | A2C2 | Barry | AL | OP | NG | 170.1 | 31.004167 | -88.013889 | 10 | POINT(-88.013889 31.004167) | 2008-01 | + +## 26. `energy_eia_facility_fuel_flat` + +_No matching table found in `public` for `public.energy_eia_facility_fuel_flat`._ + +## 27. `energy_eia_seds_flat` + +Estimated rows: 2,575,437. Columns: 10. Ordering: database scan order. + +| gid | period | year | series_id | series_description | state_id | state_name | value | unit | raw_properties | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 1 | 1960 | 1960 | ABICB | Aviation gasoline blending components consumed by the industrial sector | AK | Alaska | 0.0 | Billion Btu | {"period": "1960", "seriesDescription": "Aviation gasoline blending components consumed by the industrial sector", "s... | +| 2 | 1960 | 1960 | ABICB | Aviation gasoline blending components consumed by the industrial sector | AL | Alabama | 0.0 | Billion Btu | {"period": "1960", "seriesDescription": "Aviation gasoline blending components consumed by the industrial sector", "s... | +| 3 | 1960 | 1960 | ABICB | Aviation gasoline blending components consumed by the industrial sector | AR | Arkansas | 0.0 | Billion Btu | {"period": "1960", "seriesDescription": "Aviation gasoline blending components consumed by the industrial sector", "s... | +| 4 | 1960 | 1960 | ABICB | Aviation gasoline blending components consumed by the industrial sector | AZ | Arizona | 0.0 | Billion Btu | {"period": "1960", "seriesDescription": "Aviation gasoline blending components consumed by the industrial sector", "s... | +| 5 | 1960 | 1960 | ABICB | Aviation gasoline blending components consumed by the industrial sector | CA | California | 0.0 | Billion Btu | {"period": "1960", "seriesDescription": "Aviation gasoline blending components consumed by the industrial sector", "s... | +| 6 | 1960 | 1960 | ABICB | Aviation gasoline blending components consumed by the industrial sector | CO | Colorado | 0.0 | Billion Btu | {"period": "1960", "seriesDescription": "Aviation gasoline blending components consumed by the industrial sector", "s... | +| 7 | 1960 | 1960 | ABICB | Aviation gasoline blending components consumed by the industrial sector | CT | Connecticut | 0.0 | Billion Btu | {"period": "1960", "seriesDescription": "Aviation gasoline blending components consumed by the industrial sector", "s... | +| 8 | 1960 | 1960 | ABICB | Aviation gasoline blending components consumed by the industrial sector | DC | District of Columbia | 0.0 | Billion Btu | {"period": "1960", "seriesDescription": "Aviation gasoline blending components consumed by the industrial sector", "s... | +| 9 | 1960 | 1960 | ABICB | Aviation gasoline blending components consumed by the industrial sector | DE | Delaware | 0.0 | Billion Btu | {"period": "1960", "seriesDescription": "Aviation gasoline blending components consumed by the industrial sector", "s... | +| 10 | 1960 | 1960 | ABICB | Aviation gasoline blending components consumed by the industrial sector | FL | Florida | 0.0 | Billion Btu | {"period": "1960", "seriesDescription": "Aviation gasoline blending components consumed by the industrial sector", "s... | + +## 28. `internet_cables` + +Estimated rows: 693. Columns: 14. Ordering: `feature_id`. + +Showing 12 of 14 columns. Omitted columns include: `properties`, `geom`. + +| feature_id | name | cable_id | color | owners | rfs_year | decommission_year | length_raw | length_km | cable_type | url | extra_urls | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 2africa-0 | 2Africa | 2africa | #939597 | Bayobab, China Mobile, Meta, Orange, Telecom Egypt, Vodafone, WIOCC, center3 | 2024 | | 45,000 km | 45000 | | https://www.2africacable.net/ | ["https://www.submarinenetworks.com/en/systems/asia-europe-africa/2africa"] | +| 2africa-1 | 2Africa | 2africa | #b5258f | Bayobab, China Mobile, Meta, Orange, Telecom Egypt, Vodafone, WIOCC, center3 | 2024 | | 45,000 km | 45000 | | https://www.2africacable.net/ | ["https://www.submarinenetworks.com/en/systems/asia-europe-africa/2africa"] | +| 5-villages-6-islands-0 | 5 Villages 6 Islands | 5-villages-6-islands | #694099 | Tokyo Metropolitan Government | 2019 | | 355 km | 355 | | | [] | +| acs-alaska-oregon-network-akorn-0 | ACS Alaska-Oregon Network (AKORN) | acs-alaska-oregon-network-akorn | #4c4fa1 | Alaska Communications | 2009 | | 3,000 km | 3000 | | https://www.alaskacommunications.com | [] | +| aden-djibouti-0 | Aden-Djibouti | aden-djibouti | #08acdb | Djibouti Telecom, Orange, Sparkle, Tata Communications, TeleYemen | 1994 | | 269 km | 269 | | https://www.teleyemen.com.ye/ | [] | +| adria-1-0 | Adria-1 | adria-1 | #65b545 | ALBtelecom, Hrvatski Telekom | 1996 | | 440 km | 440 | | | [] | +| aec-1-0 | AEC-1 | aec-1 | #923c96 | EXA Infrastructure | 2016 | | 5,521 km | 5521 | | https://exainfra.net/ | ["https://www.submarinenetworks.com/en/systems/trans-atlantic/aec"] | +| africa-1-0 | Africa-1 | africa-1 | #939597 | G42, Mobily, Pakistan Telecommunications Company Ltd., TeleYemen, Telecom Egypt, Zain Omantel International, e& | 2026 | | 10,000 km | 10000 | | | ["https://www.submarinenetworks.com/en/systems/asia-europe-africa/africa-1"] | +| africa-coast-to-europe-ace-0 | Africa Coast to Europe (ACE) | africa-coast-to-europe-ace | #8cc63f | Bayobab, Cable Consortium of Liberia, Canalink, Dolphin Telecom, GUILAB, Gambia Submarine Cable Company, Internationa... | 2012 | | 17,000 km | 17000 | | | ["https://www.submarinenetworks.com/en/systems/euro-africa/ace"] | +| airraq-0 | Airraq | airraq | #bc3e96 | Unicom, Inc. | 2025 | | 680 km | 680 | | https://www.gci.com/ | [] | + +## 29. `internet_cable_landing_points` + +Estimated rows: 3,361. Columns: 6. Ordering: `feature_id`, `ordinal`. + +| feature_id | ordinal | landing_id | name | country | is_tbd | +| --- | --- | --- | --- | --- | --- | +| 2africa-0 | 0 | luanda-angola | Luanda, Angola | Angola | | +| 2africa-0 | 1 | manama-bahrain | Manama, Bahrain | Bahrain | | +| 2africa-0 | 2 | moroni-comoros | Moroni, Comoros | Comoros | | +| 2africa-0 | 3 | muanda-congo-dem-rep- | Muanda, Congo, Dem. Rep. | Congo, Dem. Rep. | | +| 2africa-0 | 4 | pointe-noire-congo-rep- | Pointe-Noire, Congo, Rep. | Congo, Rep. | | +| 2africa-0 | 5 | abidjan-cte-divoire | Abidjan, Côte d'Ivoire | Côte d'Ivoire | | +| 2africa-0 | 6 | djibouti-city-djibouti | Djibouti City, Djibouti | Djibouti | | +| 2africa-0 | 7 | port-said-egypt | Port Said, Egypt | Egypt | | +| 2africa-0 | 8 | ras-ghareb-egypt | Ras Ghareb, Egypt | Egypt | | +| 2africa-0 | 9 | suez-egypt | Suez, Egypt | Egypt | | + +## 30. `internet_city_dominance` + +Estimated rows: 4,552. Columns: 13. Ordering: `id`. + +Showing 12 of 13 columns. Omitted columns include: `geom`. + +| id | city | country | latitude | longitude | country_name | region | status | physical_capacity_tbps | added_physical_capacity_tbps | logical_dominance_ips | top_asns | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| aachen-de | Aachen | DE | 50.7756 | 6.0836 | Germany | Europe | existing | 0 | 0 | 97803 | [{"asn": "47610", "ip_count": "65792", "name": "RWTH-AS"}, {"asn": "34953", "ip_count": "8448", "name": "RelAix Netwo... | +| aalborg-dk | Aalborg | DK | 57.05 | 9.9167 | Denmark | Europe | existing | 0 | 0 | 1074688 | [{"asn": "9158", "ip_count": "914432", "name": "Telenor Denmark"}, {"asn": "6834", "ip_count": "90624", "name": "KMD ... | +| aalen-de | Aalen | DE | 48.8333 | 10.1 | Germany | Europe | existing | 0 | 0 | 96512 | [{"asn": "553", "ip_count": "65536", "name": "BelW\u00fc"}, {"asn": "6735", "ip_count": "24576", "name": "TNG Stadtne... | +| aalsmeer-nl | Aalsmeer | NL | 52.2667 | 4.75 | Netherlands | Europe | existing | 0 | 0 | 50633 | [{"asn": "1136", "ip_count": "32768", "name": "KPN NL"}, {"asn": "44074", "ip_count": "16384", "name": "RFH-AS"}, {"a... | +| aalst-be | Aalst | BE | 50.9383 | 4.0392 | Belgium | Europe | existing | 0 | 0 | 263680 | [{"asn": "5432", "ip_count": "262144", "name": "Proximus"}, {"asn": "204959", "ip_count": "1024", "name": "ONTEX"}, {... | +| aarau-ch | Aarau | CH | 47.4 | 8.05 | Switzerland | Europe | existing | 0 | 0 | 54272 | [{"asn": "33965", "ip_count": "17920", "name": "Litecom AG"}, {"asn": "6730", "ip_count": "17152", "name": "Sunrise G... | +| aarhus-dk | Aarhus | DK | 56.1572 | 10.2107 | Denmark | Europe | existing | 0 | 0 | 70144 | [{"asn": "44869", "ip_count": "65536", "name": "Fibia"}, {"asn": "3292", "ip_count": "1024", "name": "TDC A/S"}, {"as... | +| abakan-ru | Abakan | RU | 53.7167 | 91.4667 | Russia | Europe | existing | 0 | 0 | 82432 | [{"asn": "12389", "ip_count": "73984", "name": "Rostelecom"}, {"asn": "51612", "ip_count": "3072", "name": "ALFATEL-A... | +| aba-ng | Aba | NG | 5.1167 | 7.3667 | Nigeria | Africa | existing | 0 | 0 | 33280 | [{"asn": "36873", "ip_count": "32768", "name": "Airtel Networks Nigeria"}, {"asn": "29465", "ip_count": "512", "name"... | +| abbotsford-ca | Abbotsford | CA | 49.05 | -122.3167 | Canada | North America | existing | 0 | 0 | 59648 | [{"asn": "6327", "ip_count": "58880", "name": "Shaw Cablesystems"}, {"asn": "19662", "ip_count": "512", "name": "Unis... | + +## 31. `fcc_bdc_location_provider_aggregates` + +Sampled actual table: `public.fcc_bdc_location_provider_aggregate`. + +Estimated rows: 998. Columns: 17. Ordering: `as_of_date`, `geography_type`, `geoid`. + +Showing 12 of 17 columns. Omitted columns include: `copper_provider_count`, `business_fiber_provider_count`, `business_100_20_provider_count`, `provider_file_rows`, `updated_at`. + +| as_of_date | geography_type | geoid | provider_count | fiber_provider_count | cable_provider_count | fixed_wireless_provider_count | provider_100_20_count | business_provider_count | max_advertised_download_mbps | max_advertised_upload_mbps | matched_location_rows | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 2025-12-31 | County | 01069 | 11 | 8 | 4 | 4 | 11 | 11 | 100000.0 | 100000.0 | 273014 | +| 2025-12-31 | County | 01071 | 9 | 7 | 2 | 4 | 9 | 9 | 10000.0 | 10000.0 | 88104 | +| 2025-12-31 | County | 01073 | 16 | 11 | 2 | 4 | 15 | 15 | 100000.0 | 100000.0 | 1123613 | +| 2025-12-31 | County | 01089 | 15 | 12 | 4 | 4 | 14 | 15 | 100000.0 | 100000.0 | 810226 | +| 2025-12-31 | County | 04003 | 15 | 5 | 2 | 12 | 12 | 14 | 2300.0 | 2300.0 | 280879 | +| 2025-12-31 | County | 04013 | 42 | 25 | 5 | 21 | 40 | 38 | 1000000.0 | 1000000.0 | 8603178 | +| 2025-12-31 | County | 04019 | 28 | 9 | 3 | 18 | 24 | 23 | 100000.0 | 100000.0 | 2323405 | +| 2025-12-31 | County | 05119 | 20 | 11 | 5 | 6 | 19 | 19 | 100000.0 | 100000.0 | 694836 | +| 2025-12-31 | County | 05145 | 20 | 11 | 5 | 10 | 17 | 19 | 10000.0 | 10000.0 | 124592 | +| 2025-12-31 | County | 06001 | 25 | 11 | 1 | 16 | 24 | 23 | 100000.0 | 100000.0 | 2476379 | + +## 32. `fcc_bdc_broadband_connection_table` + +Sampled actual table: `public.data_center_broadband_connection`. + +Estimated rows: 1,833. Columns: 48. Ordering: `master_id`. + +Showing 12 of 48 columns. Omitted columns include: `source`, `operator`, `city`, `country`, `longitude`, `latitude`, `geom`, `fcc_bdc_as_of_date`, `fcc_bdc_geography_type`, `fcc_bdc_geoid`, `fcc_provider_count`, `fcc_fiber_provider_count`, `fcc_cable_provider_count`, `fcc_fixed_wireless_provider_count`, `fcc_max_advertised_download_mbps`, `fcc_max_advertised_upload_mbps`, `fcc_100_20_provider_count`, `fcc_summary_json`, `fetched_at`, `updated_at`.... + +| master_id | name | state | census_tract_geoid | census_broadband_subscription_pct | fcc_bdc_status | fcc_provider_geography_type | fcc_county_provider_count | fcc_tract_provider_count | fcc_tract_fiber_provider_count | fcc_tract_business_provider_count | fcc_tract_max_advertised_download_mbps | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| curated/0002744301 | Verizon | NJ | 34023000702 | 95.6 | fcc_location_provider_joined | Tract | 13 | 7 | 4 | 7 | 10000.0 | +| curated/0007805491 | Discover Financial Services New Albany | OH | 39049007205 | 98.9 | fcc_location_provider_joined | Tract | 26 | 5 | 2 | 5 | 5000.0 | +| curated/0009474864 | Google Data Center | NC | 37027030300 | 80.8 | fcc_location_provider_joined | Tract | 10 | 8 | 4 | 8 | 5000.0 | +| curated/0013924557 | Project Alluvion | IA | 19153011028 | 94.9 | fcc_location_provider_joined | Tract | 26 | 11 | 7 | 9 | 10000.0 | +| curated/0014271367e0e039e1b1b386315f6581 | Newton (Atlanta) Data Center | GA | 13297110801 | 87.7 | fcc_location_provider_joined | Tract | 9 | 6 | 4 | 6 | 5000.0 | +| curated/0014593270 | Apple - Maiden Data Center | NC | 37035011702 | 79.5 | fcc_location_provider_joined | Tract | 15 | 7 | 2 | 7 | 5000.0 | +| curated/0014930068 | HPC (880) | NM | 35001980000 | 96.0 | fcc_location_provider_joined | Tract | 21 | 9 | 0 | 8 | 2000.0 | +| curated/0014997588 | Meta Henrico Data Center | VA | 51087201404 | 90.3 | fcc_location_provider_joined | Tract | 7 | 5 | 3 | 5 | 16000.0 | +| curated/0015884451 | Barclays Datacenter | NJ | 34039037300 | 93.0 | fcc_location_provider_joined | Tract | 8 | 5 | 3 | 5 | 10000.0 | +| curated/0016282459 | CyberNAP Glen Burnie | MD | 24003730404 | 91.8 | fcc_location_provider_joined | Tract | 15 | 6 | 2 | 6 | 2300.0 | + +## 33. `opposition_cases_geocoded` + +Estimated rows: 18. Columns: 15. Ordering: database scan order. + +Showing 12 of 15 columns. Omitted columns include: `opposition_type`, `data_source`, `geom`. + +| id | state | location | state_id | lat | lon | investment_billion | status | developer | commons_type | governance_response | outcome | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 1 | AZ | Goodyear-Buckeye | 4 | 33.45 | -112.39 | 14.0 | Blocked | Tract | Water+Grid | Zoning denial | Withdrawn then relocated | +| 2 | MO | Peculiar | 29 | 38.72 | -94.46 | 1.5 | Blocked | Diode Ventures | Land+Water | Zoning amendment | Prohibited by ordinance | +| 3 | IN | Chesterton | 18 | 41.61 | -87.06 | 1.3 | Blocked | Provident Realty | Water+Air+Wildlife | Council withdrawal | Developer withdrew | +| 4 | VA | Richmond/Henrico | 51 | 37.51 | -77.33 | 0.5 | Blocked | DC Blox | Noise+Aesthetics | Deferral then withdrawal | Developer withdrew; revised smaller | +| 5 | VA | Catlett Station/Fauquier | 51 | 38.65 | -77.64 | 0.4 | Blocked | Headwaters Dev | Noise+Water+Power+Environment | Pre-hearing withdrawal | Developer withdrew before hearing | +| 6 | OR | Cascade Locks | 41 | 45.67 | -121.87 | 0.1 | Blocked | Roundhouse Digital | Grid rates+Credibility | Recall election | Officials recalled; Port Authority stopped | +| 7 | VA | Prince William | 51 | 38.7 | -77.48 | 24.7 | Delayed | QTS+Compass | Environment+Noise+Grid+Historic | Litigation | 3 lawsuits active; one dismissed+appealed | +| 8 | VA | Culpeper | 51 | 38.47 | -77.99 | 12.0 | Delayed | Culpeper Acquisitions | Land preservation+Historic | Planning denial | Unanimous denial; Board deferred | +| 9 | VA | King George | 51 | 38.27 | -77.15 | 6.0 | Delayed | Amazon | Infrastructure+Resources | Political reversal | Renegotiation; rezoning reconsidered | +| 10 | VA | Midlothian/Powhatan | 51 | 37.44 | -77.81 | 3.0 | Delayed | Province Group | Noise+Traffic+Environment | Deferred then approved | Approved 3-2 despite opposition; utility delay | + +## 34. `census_tract_huc8_link` + +Estimated rows: 806. Columns: 5. Ordering: database scan order. + +| geoid | huc8 | overlap_sqm | overlap_sqkm | tract_overlap_pct | +| --- | --- | --- | --- | --- | +| 26163581600 | 04090004 | 4049402.7790175527 | 4.049402779017552 | 0.9999999999919172 | +| 18097352300 | 05120201 | 2405395.5570320487 | 2.405395557032049 | 1.0000000000003517 | +| 36029009200 | 04120104 | 5329322.178747755 | 5.329322178747755 | 1.0000000000042821 | +| 04013113100 | 15060106 | 1304588.2283894438 | 1.3045882283894439 | 1.0000000000020903 | +| 06085505007 | 18050003 | 3029721.5568704605 | 3.0297215568704603 | 1.0000000000049134 | +| 04013422514 | 15050100 | 1122663.8417252041 | 1.1226638417252042 | 0.45491211388156216 | +| 04013422514 | 15060106 | 1345205.8969148104 | 1.3452058969148104 | 0.5450878842156984 | +| 51059460503 | 02070008 | 32892.9460603483 | 0.0328929460603483 | 0.022607669336869043 | +| 51059460503 | 02070010 | 1422053.3794437945 | 1.4220533794437944 | 0.9773923114961641 | +| 12057011611 | 03100206 | 5641554.468745705 | 5.641554468745705 | 1.0000000000018656 | + +## 35. `im3_state_projected_moderate_50` + +Estimated rows: 328. Columns: 19. Ordering: database scan order. + +Showing 12 of 19 columns. Omitted columns include: `water_cooling_frac`, `cooling_energy_demand_mwh`, `cooling_water_demand_mgy`, `cooling_water_consumption_mgy`, `normalized_locational_cost`, `normalized_gravity_score`, `weighted_siting_score`. + +| id | state_code | latitude | longitude | growth_scenario | market_gravity_weight | region | state_id | total_cost_million_usd | campus_size_square_ft | data_center_it_power_mw | mechanical_cooling_frac | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 1_0 | AL | | | moderate | 50 | alabama | 1 | 522.04 | 1000000 | 36 | 0.0 | +| 1_1 | AL | | | moderate | 50 | alabama | 1 | 501.9 | 1000000 | 36 | 0.0 | +| 1_2 | AL | | | moderate | 50 | alabama | 1 | 526.54 | 1000000 | 36 | 0.0 | +| 4_0 | AZ | | | moderate | 50 | arizona | 4 | 499.47 | 1000000 | 36 | 0.0 | +| 4_1 | AZ | | | moderate | 50 | arizona | 4 | 499.47 | 1000000 | 36 | 0.0 | +| 4_10 | AZ | | | moderate | 50 | arizona | 4 | 517.41 | 1000000 | 36 | 1.0 | +| 4_11 | AZ | | | moderate | 50 | arizona | 4 | 517.41 | 1000000 | 36 | 1.0 | +| 4_12 | AZ | | | moderate | 50 | arizona | 4 | 515.52 | 1000000 | 36 | 0.75 | +| 4_13 | AZ | | | moderate | 50 | arizona | 4 | 515.52 | 1000000 | 36 | 0.75 | +| 4_2 | AZ | | | moderate | 50 | arizona | 4 | 499.47 | 1000000 | 36 | 0.0 | + +## 36. `im3_projected_state_demand_summary` + +Estimated rows: 31. Columns: 13. Ordering: database scan order. + +Showing 12 of 13 columns. Omitted columns include: `market_gravity_weight`. + +| state | state_id | projected_facility_count | total_cost_million_usd | total_it_power_mw | total_campus_area_sqft | total_cooling_energy_demand_mwh | total_cooling_water_demand_mgy | total_cooling_water_consumption_mgy | avg_mechanical_cooling_fraction | avg_water_cooling_fraction | scenario | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| ALABAMA | 1 | 3 | 1550.48 | 108.0 | 3000000 | 0.0 | 130.56 | 104.45 | 0.0 | 1.0 | moderate | +| ARIZONA | 4 | 14 | 7134.93 | 504.0 | 14000000 | 685908.0 | 293.76 | 235.01 | 0.518 | 0.482 | moderate | +| CALIFORNIA | 6 | 21 | 10882.16 | 756.0 | 21000000 | 0.0 | 913.91 | 731.13 | 0.0 | 1.0 | moderate | +| COLORADO | 8 | 3 | 1502.28 | 108.0 | 3000000 | 141912.0 | 65.28 | 52.22 | 0.5 | 0.5 | moderate | +| FLORIDA | 12 | 3 | 1499.31 | 108.0 | 3000000 | 283824.0 | 0.0 | 0.0 | 1.0 | 0.0 | moderate | +| GEORGIA | 13 | 14 | 7094.73 | 504.0 | 14000000 | 0.0 | 609.28 | 487.42 | 0.0 | 1.0 | moderate | +| ILLINOIS | 17 | 16 | 7940.21 | 576.0 | 16000000 | 0.0 | 696.31 | 557.05 | 0.0 | 1.0 | moderate | +| IOWA | 19 | 14 | 6884.15 | 504.0 | 14000000 | 0.0 | 609.28 | 487.42 | 0.0 | 1.0 | moderate | +| KENTUCKY | 21 | 3 | 1471.14 | 108.0 | 3000000 | 0.0 | 130.56 | 104.45 | 0.0 | 1.0 | moderate | +| MASSACHUSETTS | 25 | 2 | 994.64 | 72.0 | 2000000 | 0.0 | 87.04 | 69.63 | 0.0 | 1.0 | moderate | + +## 37. `utility_rate_tracker_2025_2028` + +Estimated rows: 374. Columns: 14. Ordering: database scan order. + +Showing 12 of 14 columns. Omitted columns include: `status`, `source_file`. + +| state_code | utility_provider | state_name | state_id | service_type | customer_count | total_revenue_increase_2025_2028 | time_period | monthly_increase_amount | monthly_pct_increase_ratio | effective_date | effective_date_raw | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| IN | AES Indiana | Indiana | 18 | Electricity | 530802.0 | 201979178.0 | Increase in annual revenue | 10.0 | 0.0335 | 2026-06-01T00:00:00 | 2026-06-01 00:00:00 | +| OH | AES Ohio | Ohio | 39 | Electricity | 540836.0 | 529465023.41 | Increase in annual revenue | 15.28 | 0.09 | 2025-11-06T00:00:00 | 2025-11-06 00:00:00 | +| OH | AES Ohio | Ohio | 39 | Electricity | 540836.0 | 211350000.0 | January 1, 2027 - December 31, 2029 | 11.47 | 0.0613 | 2027-01-01T00:00:00 | 2027-01-01 00:00:00 | +| AL | Alabama Power Company | Alabama | 01 | Electricity | 1546483.0 | | | 3.32 | | 2028-01-01T00:00:00 | 2028 | +| IL | Ameren Illinois | Illinois | 17 | Electricity | 1224108.0 | 673366000.0 | January 1, 2025 - December 31, 2027 | | | 2025-01-01T00:00:00 | 2025-01-01 00:00:00 | +| IL | Ameren Illinois | Illinois | 17 | Natural Gas | 802310.0 | 218844000.0 | Increase in annual revenue | | | 2026-01-01T00:00:00 | 2026-01-01 00:00:00 | +| MO | Ameren Missouri | Missouri | 29 | Electricity | 1264469.0 | 1273136986.0 | Increase in annual revenue | | | 2025-06-01T00:00:00 | 2025-06-01 00:00:00 | +| MO | Ameren Missouri | Missouri | 29 | Natural Gas | 136274.0 | 105028767.0 | Increase in annual revenue | 13.0 | 0.12 | 2025-09-01T00:00:00 | 2025-09-01 00:00:00 | +| TN | Appalachian Power | Tennessee | 47 | Electricity | 49489.0 | 13006129.0 | September 2025 - August 2027 | 2.99 | | 2025-09-01T00:00:00 | 2025-09-01 00:00:00 | +| WV | Appalachian Power | West Virginia | 54 | Electricity | 418138.0 | 247689863.0 | Increase in annual revenue | | | 2025-09-29T00:00:00 | 2025-09-29 00:00:00 | + +## 38. `energy_atlas_layers_catalog` + +Estimated rows: 0. Columns: 8. Ordering: `table_name`. + +| table_name | source_item_id | source_type | source_title | source_owner | source_url | category | imported_at | +| --- | --- | --- | --- | --- | --- | --- | --- | +| energy_eia_electricity_operating_generator_capacity | electricity_operating-generator-capacity | EIA API | operating-generator-capacity | U.S. Energy Information Administration | https://api.eia.gov/v2/electricity/operating-generator-capacity | power_plants | 2026-05-25T10:49:29.577662+00:00 | +| energy_eia_seds | seds | EIA API | seds | U.S. Energy Information Administration | https://api.eia.gov/v2/seds | state_energy | 2026-05-25T11:16:25.100722+00:00 | + +## 39. `legiscan_sessions` + +Estimated rows: 646. Columns: 14. Ordering: `session_id`. + +Showing 12 of 14 columns. Omitted columns include: `bill_count`, `imported_at`. + +| session_id | state_id | state_abbr | year_start | year_end | session_title | session_tag | is_special | is_prior | dataset_hash | dataset_date | dataset_size_mb | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 1161 | 17 | KY | 2016 | 2016 | 2016 Regular Session | Regular Session | False | True | b4e38f344e60236669dbdd690d13af16 | 2021-12-31 | 2.83556 | +| 1164 | 41 | SD | 2016 | 2016 | 2016 Regular Session | Regular Session | False | True | 0a8b763b54e5dd488be5a1b3fb734baa | 2021-12-31 | 1.935084 | +| 1168 | 48 | WV | 2016 | 2016 | 2016 Regular Session | Regular Session | False | True | 6f937790ca345729d2b96dbd0b7b56d8 | 2021-12-31 | 4.768601 | +| 1169 | 9 | FL | 2016 | 2016 | 2016 Regular Session | Regular Session | False | True | 6459a5c03d80799db88fc81f57fcc7e2 | 2021-12-31 | 4.00847 | +| 1170 | 34 | ND | 2017 | 2018 | 2017-2018 Regular Session | Regular Session | False | True | 93c768b8ca89afcc365010abd0ceeb2c | 2021-12-31 | 2.815085 | +| 1171 | 36 | OK | 2016 | 2016 | 2016 Regular Session | Regular Session | False | True | b93a03306038b9fbebe2ae3db73a6254 | 2021-12-31 | 9.760202 | +| 1172 | 1 | AL | 2016 | 2016 | 2016 Regular Session | Regular Session | False | True | e800c0b0cdea4446e6a9ef36040ac9ba | 2021-12-31 | 3.003159 | +| 1180 | 44 | UT | 2016 | 2016 | 2016 Regular Session | Regular Session | False | True | 7b12b1a2effde90d73d81bd62e2d36c6 | 2021-12-31 | 3.234579 | +| 1187 | 46 | VA | 2016 | 2016 | 2016 Regular Session | Regular Session | False | True | 48a324f85c12c45e250a3ac0ed4d1959 | 2021-12-31 | 10.107357 | +| 1188 | 3 | AZ | 2016 | 2016 | 2016 Regular Session | Regular Session | False | True | 748c6048c5e630c61254b2823e3007b4 | 2021-12-31 | 4.386376 | + +## 40. `legiscan_bills` + +Estimated rows: 1,263,868. Columns: 21. Ordering: `bill_id`. + +Showing 12 of 21 columns. Omitted columns include: `session_id`, `description`, `state_link`, `change_hash`, `subjects`, `sponsor_count`, `vote_count`, `text_count`, `imported_at`. + +| bill_id | state | bill_number | bill_type | title | status | status_date | completed | body | is_relevant | relevance_tags | url | +| --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | --- | +| 777770 | KY | HB11 | B | AN ACT relating to service animals. | 1 | 2016-01-05 | 0 | H | False | | https://legiscan.com/KY/bill/HB11/2016 | +| 780574 | KY | HB70 | B | AN ACT proposing an amendment to Section 145 of the Constitution of Kentucky relating to persons entitled to vote. | 2 | 2016-02-05 | 0 | H | False | | https://legiscan.com/KY/bill/HB70/2016 | +| 780667 | KY | HB40 | B | AN ACT relating to criminal records. | 4 | 2016-04-12 | 1 | H | False | | https://legiscan.com/KY/bill/HB40/2016 | +| 783555 | KY | HB12 | B | AN ACT relating to problem, compulsive, or pathological gambling and making an appropriation therefor. | 1 | 2016-01-05 | 0 | H | False | | https://legiscan.com/KY/bill/HB12/2016 | +| 783597 | KY | SB11 | B | AN ACT relating to alcoholic beverages. | 4 | 2016-04-09 | 1 | S | False | | https://legiscan.com/KY/bill/SB11/2016 | +| 784891 | KY | SB12 | B | AN ACT relating to the extended hours supplemental license. | 2 | 2016-01-15 | 0 | S | False | | https://legiscan.com/KY/bill/SB12/2016 | +| 784982 | KY | HB13 | B | AN ACT relating to driving under the influence and declaring an emergency. | 1 | 2016-01-05 | 0 | H | False | | https://legiscan.com/KY/bill/HB13/2016 | +| 786510 | KY | SR13 | R | Adjourn the Senate in honor and loving memory of Colonel Walker Russell "Russ" Reynolds. | 4 | 2016-04-15 | 0 | S | False | | https://legiscan.com/KY/bill/SR13/2016 | +| 786515 | KY | SR12 | R | Adjourn in honor and loving memory of Mary Alice Willett Higdon. | 4 | 2016-04-15 | 0 | S | False | | https://legiscan.com/KY/bill/SR12/2016 | +| 786520 | KY | SR11 | R | A RESOLUTION honoring Wilbur M. Zevely upon his recognition by the Northern Kentucky Bar Foundation with its Lifetime... | 0 | | 0 | S | False | | https://legiscan.com/KY/bill/SR11/2016 | diff --git a/docs/database-tables.md b/docs/database-tables.md index d9baf17..e3af455 100644 --- a/docs/database-tables.md +++ b/docs/database-tables.md @@ -13,12 +13,13 @@ ## Table Organization -Tables are organized into five categories: +Tables are organized into six categories: 1. **Core Data Center Tables** - Master inventories and source data 2. **Enrichment Tables** - Data centers joined with contextual data -3. **Base Layer Tables** - Geographic and demographic reference layers -4. **Infrastructure Tables** - Energy and connectivity infrastructure -5. **Legislation Tables** - LegiScan state and federal bill data (2016-2026) +3. **Environmental and Election Source Tables** - Long-form climate, drought, fire/smoke, and precinct-election source layers +4. **Base Layer Tables** - Geographic and demographic reference layers +5. **Infrastructure Tables** - Energy and connectivity infrastructure +6. **Legislation Tables** - LegiScan state and federal bill data (2016-2026) --- @@ -147,20 +148,224 @@ Tables are organized into five categories: **Source**: FEMA National Risk Index (December 2025 release) -### `data_center_rdh_precinct_vote_matches` -**Rows**: Varies -**Purpose**: Per-facility precinct-level election results +### `data_center_historical_climate` +**Rows**: 1,833 +**Purpose**: One-row-per-facility historical climate summary for data center locations **Key Columns**: -- Data center identifiers -- `precinct_name`, `precinct_id` +- `master_id` (TEXT) - FK to `master_data_centers` +- `source`, `name`, `operator`, `city`, `state`, `country` +- `latitude`, `longitude`, `geom` +- `daymet_dataset_version`, `gridmet_dataset_version` +- `climate_period_start`, `climate_period_end` - Current period: 1991-01-01 to 2020-12-31 +- **Temperature**: `mean_annual_temperature_c`, `mean_summer_temperature_c`, `max_daily_temperature_c`, `min_daily_temperature_c` +- **Humidity / wet bulb**: `mean_relative_humidity_pct`, `mean_wet_bulb_temperature_c`, `max_wet_bulb_temperature_c`, `extreme_wet_bulb_days` +- **Cooling / heat**: `cooling_degree_days_c`, `annual_cooling_degree_days_c_mean`, `extreme_heat_days`, `annual_extreme_heat_days_mean` +- **Precipitation**: `precipitation_total_mm`, `annual_precipitation_mm_mean`, `annual_precipitation_cv`, `wet_day_precipitation_p95_mm` +- **Wind**: `mean_wind_speed_ms`, `max_daily_mean_wind_speed_ms`, `sustained_wind_days`, `annual_sustained_wind_days_mean` + +**Source**: Daymet + gridMET historical climate data + +**Notes**: Built by `historical_climate_data_centers.ipynb` / `open_meteo_historical_data_centers.ipynb` + +### `data_center_usdm_drought_exposure` +**Rows**: 1,833 +**Purpose**: Per-facility drought exposure summary from weekly U.S. Drought Monitor polygons + +**Key Columns**: +- `master_id` (TEXT) - FK to `master_data_centers` +- `source`, `name`, `operator`, `city`, `state`, `country` +- `latitude`, `longitude`, `geom` +- `usdm_status` - `covered` or `no_coverage` +- `drought_period_start`, `drought_period_end` - Current period: 2000-01-04 to 2025-12-30 +- `weeks_observed` +- `weeks_in_d0_or_worse`, `weeks_in_d1_or_worse`, `weeks_in_d2_or_worse`, `weeks_in_d3_or_worse`, `weeks_in_d4` +- `pct_weeks_in_d0_or_worse`, `pct_weeks_in_d1_or_worse`, `pct_weeks_in_d2_or_worse`, `pct_weeks_in_d3_or_worse`, `pct_weeks_in_d4` +- `worst_dm_category`, `mean_dm_category` +- `longest_d0_streak_weeks`, `longest_d2_streak_weeks`, `longest_d3_streak_weeks` + +**Source**: U.S. Drought Monitor weekly spatial data + +**Notes**: +- Summary table is rolled up from `data_center_usdm_drought_dc_week` +- `dm_category` scale: D0-D4, stored as 0-4 +- 1,830 facilities have covered status; 3 have no coverage + +### `data_center_hms_smoke_exposure` +**Rows**: 1,833 +**Purpose**: Per-facility wildfire-smoke exposure summary from NOAA HMS smoke polygons + +**Key Columns**: +- `master_id` (TEXT) - FK to `master_data_centers` +- `source`, `name`, `operator`, `city`, `state`, `country` +- `latitude`, `longitude`, `geom` +- `hms_status` +- `smoke_period_start`, `smoke_period_end` - Current period: 2005-08-05 to 2026-05-22 +- `days_observed` +- `days_with_any_smoke`, `days_with_light_or_worse`, `days_with_medium_or_worse`, `days_with_heavy_smoke` +- `pct_days_with_any_smoke`, `pct_days_with_light_or_worse`, `pct_days_with_medium_or_worse`, `pct_days_with_heavy_smoke` +- `worst_density_rank`, `worst_density`, `mean_density_rank` +- `longest_any_smoke_streak_days`, `longest_medium_or_heavy_streak_days`, `longest_heavy_smoke_streak_days` + +**Source**: NOAA Hazard Mapping System (HMS) smoke polygons + +**Notes**: +- Summary table is rolled up from `data_center_hms_smoke_dc_day` +- Density rank: 0 = observed no smoke, 1 = Light, 2 = Medium, 3 = Heavy +- HMS product path uses NOAA's `/FIRE/web/HMS/Smoke_Polygons/` archive + +### `data_center_election_context` +**Rows**: 1,833 +**Purpose**: Standardized one-row-per-facility election context derived from RDH precinct matches + +**Key Columns**: +- `master_id` (TEXT) - FK to `master_data_centers` +- `name`, `city`, `state` +- `rdh_layer_title` +- `precinct_identifier_name` - `election_year`, `office` -- `candidate`, `party`, `votes` -- `vote_share_pct` +- `democratic_votes`, `republican_votes`, `total_votes` +- `turnout_or_vote_share` +- `updated_at` + +**Source**: Redistricting Data Hub precinct election shapefiles + +**Notes**: +- Built from `data_center_rdh_precinct_vote_matches` plus RDH feature properties +- Current rows cover 2020-2024 election layers; 1,829 facilities have non-null election year context + +### `data_center_rdh_precinct_vote_matches` +**Rows**: 3,330 +**Purpose**: Spatial join bridge between data centers and RDH precinct vote features + +**Key Columns**: +- `master_id` (TEXT) - FK to `master_data_centers` +- `feature_id` (TEXT) - FK to `rdh_precinct_vote_features` +- `layer_id` (TEXT) - FK to `rdh_precinct_vote_layers` +- `state_code` +- `join_method` +- `match_distance_m` +- `matched_at` **Source**: Redistricting Data Hub precinct shapefiles -**Notes**: Spatial join to voting precincts (point-in-polygon) +**Notes**: Spatial join to voting precincts (point-in-polygon, with nearest/fallback logic where needed) + +--- + +## Environmental and Election Source Tables + +### `usdm_drought_weekly` +**Rows**: 12,080 +**Purpose**: Raw weekly U.S. Drought Monitor polygons by drought category + +**Key Columns**: +- `id` (BIGINT) - Primary key +- `week_date` (DATE) +- `dm_category` (SMALLINT) - Drought Monitor category D0-D4 stored as 0-4 +- `objectid`, `shape_leng`, `shape_area` +- `geom` (GEOMETRY) - Drought polygon geometry + +**Source**: U.S. Drought Monitor spatial archive + +**Notes**: Source table for `data_center_usdm_drought_dc_week` + +### `data_center_usdm_drought_dc_week` +**Rows**: ~2.48 million +**Purpose**: Long-form weekly drought exposure for each covered data center + +**Key Columns**: +- `master_id` (TEXT) - FK to `master_data_centers` +- `week_date` (DATE) +- `worst_dm` (SMALLINT) - Worst drought category covering the facility that week + +**Source**: Spatial join of `master_data_centers` to `usdm_drought_weekly` + +**Notes**: +- Primary key: (`master_id`, `week_date`) +- `worst_dm = -1` indicates an observed week with no drought polygon covering the facility + +### `hms_smoke_days` +**Rows**: 7,075 +**Purpose**: One row per observed NOAA HMS smoke product day, including zero-polygon days + +**Key Columns**: +- `smoke_date` (DATE) - Primary key +- `source`, `source_file`, `source_url` +- `feature_count` (INTEGER) - Number of smoke polygons for the day +- `fetched_at`, `updated_at` + +**Source**: NOAA HMS smoke polygon archive + +**Notes**: Denominator table for daily smoke-exposure percentages + +### `hms_smoke_daily` +**Rows**: 536,286 +**Purpose**: Raw daily NOAA HMS smoke polygons with density categories + +**Key Columns**: +- `id` (BIGINT) - Primary key +- `smoke_date` (DATE) - FK to `hms_smoke_days` +- `satellite` +- `start_raw`, `end_raw`, `start_utc`, `end_utc` +- `density`, `density_rank` +- `source`, `source_file`, `source_url` +- `geom` (GEOMETRY) - Smoke polygon geometry + +**Source**: NOAA Hazard Mapping System (HMS) smoke polygons + +**Notes**: Density rank 1-3 corresponds to Light, Medium, Heavy + +### `data_center_hms_smoke_dc_day` +**Rows**: ~13.9 million +**Purpose**: Long-form daily smoke exposure for each data center and observed HMS product day + +**Key Columns**: +- `master_id` (TEXT) - FK to `master_data_centers` +- `smoke_date` (DATE) - FK to `hms_smoke_days` +- `max_density_rank` (SMALLINT) - Maximum smoke density covering the facility on that date +- `polygon_hits` (INTEGER) + +**Source**: Spatial join of `master_data_centers` to `hms_smoke_daily` + +**Notes**: +- Primary key: (`master_id`, `smoke_date`) +- `max_density_rank = 0` indicates an observed HMS day with no smoke polygon covering the facility + +### `rdh_precinct_vote_layers` +**Rows**: 69 +**Purpose**: Metadata for downloaded RDH precinct election layers + +**Key Columns**: +- `layer_id` (TEXT) - Primary key +- `state_code` +- `title` +- `format` +- `datasetid` +- `source_url` +- `filename`, `local_path`, `spatial_path` +- `metadata` (JSONB) +- `loaded_at` + +**Source**: Redistricting Data Hub precinct election datasets + +**Notes**: Current loaded layers cover 45 distinct state codes + +### `rdh_precinct_vote_features` +**Rows**: 260,953 +**Purpose**: Staged RDH precinct polygons and source attributes + +**Key Columns**: +- `feature_id` (TEXT) - Primary key +- `layer_id` (TEXT) - FK to `rdh_precinct_vote_layers` +- `state_code` +- `source_row` +- `properties` (JSONB) - Raw RDH election attributes +- `geom` (GEOMETRY) - Precinct polygon geometry + +**Source**: Redistricting Data Hub precinct election shapefiles + +**Notes**: Source feature table for `data_center_rdh_precinct_vote_matches` --- @@ -293,7 +498,7 @@ Tables are organized into five categories: - Use for proximity analysis (e.g., "all generators within 50 km of data center") #### `energy_eia_facility_fuel_flat` -**Rows**: Varies +**Rows**: Not loaded yet **Purpose**: Monthly generation by plant/fuel **Key Columns**: @@ -305,6 +510,8 @@ Tables are organized into five categories: **Source**: EIA Form 923 via API +**Notes**: Target table defined in `ingest_eia_energy_layers.py`; current database does not yet have `public.energy_eia_facility_fuel_flat`. + #### `energy_eia_seds_flat` **Rows**: 2.57 million **Purpose**: Annual state energy consumption/production (1960-2024) diff --git a/docs/research-ideas.md b/docs/research-ideas.md index ff697d8..5c7a668 100644 --- a/docs/research-ideas.md +++ b/docs/research-ideas.md @@ -167,6 +167,163 @@ ORDER BY current.pct_grid_saturated DESC; --- +## Ready-to-Run Analyses Enabled by New Context Tables + +**Status**: Four one-row-per-facility context tables are now loaded and documented: +- `data_center_historical_climate` +- `data_center_usdm_drought_exposure` +- `data_center_hms_smoke_exposure` +- `data_center_election_context` + +These make several publishable descriptive analyses possible without another major ingestion step. + +### Climate Exposure and Cooling Burden +**Core idea**: Data centers are energy-intensive cooling loads. The historical climate table lets us ask whether facilities are already sited in hotter, wetter-bulb, or more cooling-intensive climates. + +**Research Questions**: +- Are clustered facilities in hotter or more humid climate regimes than isolated facilities? +- Do hyperscalers choose cooler/non-metro climates more often than colocation providers? +- Are facilities with high `cooling_degree_days_c` or `extreme_wet_bulb_days` also near constrained grids? +- Do hotter sites overlap with lower-income or politically less powerful communities? + +**Suggested Output**: `output/data_center_climate_exposure_summary.md` + +**Starter Query**: +```sql +SELECT + dc.state, + COUNT(*) AS facilities, + AVG(c.mean_annual_temperature_c) AS mean_temp_c, + AVG(c.annual_cooling_degree_days_c_mean) AS annual_cdd_c, + AVG(c.extreme_wet_bulb_days) AS extreme_wet_bulb_days +FROM master_data_centers dc +JOIN data_center_historical_climate c USING (master_id) +GROUP BY dc.state +HAVING COUNT(*) >= 10 +ORDER BY annual_cdd_c DESC; +``` + +### Drought Exposure and Water-Use Politics +**Core idea**: The USDM summary table makes drought exposure measurable at each facility, and it can be joined to HUC8 watersheds, opposition cases, and climate metrics. + +**Research Questions**: +- Which major clusters have the highest share of weeks in D2+ drought? +- Are water-sensitive regions still attracting new or projected facilities? +- Are opposition cases more common where `pct_weeks_in_d2_or_worse` or `longest_d2_streak_weeks` is high? +- Do non-metro hyperscaler sites trade cheaper land/power for higher drought exposure? + +**Suggested Output**: `output/data_center_drought_water_risk_summary.md` + +**Starter Query**: +```sql +SELECT + w.huc8, + w.huc8_name, + COUNT(*) AS facilities, + AVG(d.pct_weeks_in_d2_or_worse) AS avg_pct_d2_or_worse, + MAX(d.longest_d2_streak_weeks) AS max_d2_streak_weeks +FROM data_center_watershed_huc8 w +JOIN data_center_usdm_drought_exposure d USING (master_id) +GROUP BY w.huc8, w.huc8_name +HAVING COUNT(*) >= 5 +ORDER BY avg_pct_d2_or_worse DESC; +``` + +### Wildfire Smoke, Operational Resilience, and Worker Exposure +**Core idea**: Smoke exposure is a climate-adaptation issue for facility operations and for workers who build, maintain, and secure these sites. + +**Research Questions**: +- Are facilities in the West and Mountain West systematically more smoke-exposed? +- Do major clusters create regional redundancy risk because many facilities share the same smoke exposure profile? +- Are smoke-exposed data centers in communities already facing higher FEMA NRI risk or lower resilience scores? +- Do smoke exposure patterns differ by operator strategy? + +**Suggested Output**: `output/data_center_smoke_resilience_summary.md` + +**Starter Query**: +```sql +SELECT + dc.state, + COUNT(*) AS facilities, + AVG(s.pct_days_with_any_smoke) AS avg_any_smoke_days, + AVG(s.pct_days_with_heavy_smoke) AS avg_heavy_smoke_days, + MAX(s.longest_heavy_smoke_streak_days) AS max_heavy_smoke_streak +FROM master_data_centers dc +JOIN data_center_hms_smoke_exposure s USING (master_id) +GROUP BY dc.state +HAVING COUNT(*) >= 10 +ORDER BY avg_heavy_smoke_days DESC; +``` + +### Political Geography of Host Communities +**Core idea**: `data_center_election_context` provides a rough but reusable local political context for each facility. It is not a causal measure of support/opposition, but it can help frame siting politics and legislative outcomes. + +**Research Questions**: +- Are data centers more common in precincts with stronger Democratic or Republican vote shares? +- Do clustered and isolated facilities sit in different local political environments? +- Are opposition cases associated with precinct partisanship, turnout, or close elections? +- Do state-level data center bills emerge from states where host precincts differ from statewide political averages? + +**Suggested Output**: `output/data_center_political_geography_summary.md` + +**Starter Query**: +```sql +SELECT + dc.state, + COUNT(*) AS facilities, + AVG(ec.democratic_votes / NULLIF(ec.total_votes, 0)) AS avg_dem_vote_share, + AVG(ec.republican_votes / NULLIF(ec.total_votes, 0)) AS avg_rep_vote_share +FROM master_data_centers dc +JOIN data_center_election_context ec USING (master_id) +WHERE ec.total_votes > 0 +GROUP BY dc.state +HAVING COUNT(*) >= 10 +ORDER BY facilities DESC; +``` + +### Compound Exposure Index +**Core idea**: Combine NRI, historical climate, drought, smoke, watershed concentration, and demographics into a transparent screening index for cumulative exposure. + +**Research Questions**: +- Which facilities or clusters have high climate, drought, smoke, and FEMA risk simultaneously? +- Are compound-exposure sites demographically different from lower-exposure sites? +- Do projected IM3 facilities fall into lower- or higher-risk exposure profiles than current facilities? + +**Implementation Notes**: +- Standardize each indicator as a percentile rank before combining. +- Keep the index descriptive and auditable; avoid black-box weighting. +- Report sensitivity using equal weights, environment-only weights, and infrastructure-weighted variants. + +**Suggested Output**: `output/data_center_compound_exposure_index.csv` + +**Starter Query**: +```sql +WITH joined AS ( + SELECT + dc.master_id, + dc.name, + dc.state, + c.annual_cooling_degree_days_c_mean, + d.pct_weeks_in_d2_or_worse, + s.pct_days_with_heavy_smoke, + n."RISK_SCORE" + FROM master_data_centers dc + LEFT JOIN data_center_historical_climate c USING (master_id) + LEFT JOIN data_center_usdm_drought_exposure d USING (master_id) + LEFT JOIN data_center_hms_smoke_exposure s USING (master_id) + LEFT JOIN data_center_nri_exposure n USING (master_id) +) +SELECT * +FROM joined +ORDER BY + annual_cooling_degree_days_c_mean DESC NULLS LAST, + pct_weeks_in_d2_or_worse DESC NULLS LAST, + pct_days_with_heavy_smoke DESC NULLS LAST +LIMIT 50; +``` + +--- + ## Methodological Extensions ### 6. Time-Series Analysis of Cluster Growth @@ -538,9 +695,10 @@ If you're interested in collaborating on any of these research directions, pleas **Priorities for external collaboration**: 1. Power capacity data acquisition -2. Water stress/drought overlay +2. Climate, drought, smoke, and compound-exposure analysis 3. Opposition cases database compilation -4. International comparative analysis +4. Water stress/drought overlay +5. International comparative analysis ---