Fuentes y metodología
Every layer on this map comes from a public record someone else published. This page states where each one came from, when it was last pulled, what licence governs it, and — most importantly — what it does not tell you. If a number here looks confident, read the gaps underneath it.
| Layer | Records | Source date | Last pulled |
|---|---|---|---|
| Acuerdos de agencias 287(g) | 10 | 2026-07-20 | 30 de julio de 2026 |
| Cámaras ALPR / Flock | 1426 | — | 30 de julio de 2026 |
| Zonas de redlining (HOLC) | 168 | 1935-1940 | 30 de julio de 2026 |
| Centros de detención con contrato de ICE | 5 | — | 30 de julio de 2026 |
| Centros de datos | 20 | — | 30 de julio de 2026 |
Acuerdos de agencias 287(g)
10 records
La Sección 287(g) de la Ley de Inmigración y Nacionalidad permite que ICE delegue ciertas facultades migratorias federales a agentes locales. Un acuerdo aquí significa que esta agencia firmó un memorando con ICE. El modelo importa: el Modelo de Aplicación en Cárceles opera sobre personas ya ingresadas en una cárcel local; el acuerdo de Oficial de Servicio de Órdenes permite a agentes designados entregar órdenes administrativas de ICE a personas bajo custodia; el Modelo de Fuerza de Tarea extiende la aplicación migratoria a la vigilancia policial cotidiana. Este registro describe a la agencia y su contrato, no a ninguna persona.
- Refresh cadence
- Periodic — re-pulled from the source on a schedule.
- Atribución
- U.S. Immigration and Customs Enforcement
Known gaps and caveats
- Positions are county interior points, not agency addresses.
- Where several agencies share a county, dots are spread on a small deterministic circle so each stays selectable.
- A signed agreement does not indicate how actively it is used.
Cámaras ALPR / Flock
1426 records
Un lector automático de matrículas fotografía cada vehículo que pasa, convierte la matrícula en texto y la almacena con hora y ubicación. Las redes de estas cámaras permiten a una agencia reconstruir por dónde viajó un vehículo durante semanas o meses, y muchas redes son consultables por agencias externas. Esta es una herramienta de transparencia que muestra dónde se ha observado la infraestructura: no es un rastreador en vivo y no dice nada sobre quién pasa por allí.
- Licencia
- ODbL 1.0
- Refresh cadence
- Frequent — the upstream data changes constantly.
- Atribución
- © OpenStreetMap contributors, ODbL — mapped by DeFlock volunteers
Known gaps and caveats
- Crowd-sourced and incomplete: the absence of a camera here is not evidence that none exists.
- Historical, not real-time. Devices are removed, moved and re-aimed without notice.
- Only 1356 of 1426 records identify a manufacturer, so this is an ALPR layer rather than a Flock-only layer.
- 1 cameras could not be matched to a county polygon.
Zonas de redlining (HOLC)
168 records
En los años 30, la Home Owners’ Loan Corporation federal calificó los barrios de A a D según el riesgo hipotecario, y la calificación dependía explícitamente de la raza, etnia y estatus migratorio de los residentes. Las áreas con calificación D se delinearon en rojo — "redlined" — y quedaron privadas de crédito durante décadas. Estas líneas son el sustrato histórico de buena parte de la geografía actual de la riqueza, la vivienda y la vigilancia policial. Esta capa muestra una política aplicada a un área, tomada de mapas históricos digitalizados.
- Licencia
- CC BY-NC-SA 4.0
- Refresh cadence
- Rare — a historical dataset that does not meaningfully change.
- Atribución
- Robert K. Nelson, LaDale Winling, et al., "Mapping Inequality: Redlining in New Deal America", American Panorama, ed. Robert K. Nelson and Edward L. Ayers
Known gaps and caveats
- Only the 8 Minnesota cities HOLC surveyed appear: Austin, Duluth, Mankato, Minneapolis, Rochester, St. Cloud, St. Paul, Staples. A neighbourhood with no polygon was not necessarily spared housing discrimination — it may simply never have been graded.
- Boundaries are georeferenced from hand-drawn 1930s map sheets and are approximate.
- Racial covenants are a separate record, mapped by Mapping Prejudice at the University of Minnesota, and are linked rather than duplicated here.
- This layer is CC BY-NC-SA 4.0 and cannot be redistributed under this project's own CC BY 4.0 data terms.
Centros de detención con contrato de ICE
5 records
Estos son edificios y contratos: una instalación que acordó retener personas para ICE, quién la opera y bajo qué tipo de acuerdo. Las cárceles del condado suelen alquilar camas a ICE mediante un acuerdo intergubernamental, lo que convierte una instalación local en parte del sistema federal de detención. Esta capa describe únicamente instalaciones y contratos. No contiene información sobre ninguna persona detenida, y nunca la contendrá.
- Refresh cadence
- Periodic — re-pulled from the source on a schedule.
- Atribución
- U.S. Immigration and Customs Enforcement
Known gaps and caveats
- Facility-level only. This layer contains no information about any detained person, by design.
- ICE publishes no coordinates; positions are city or county interior points, not building addresses.
- Covers only adult facilities authorised to hold people over 72 hours — not juvenile or family facilities, and not short-term holding rooms.
- Contracts change without announcement; a listed facility may not currently hold anyone for ICE.
Centros de datos
20 records
Los centros de datos son el sustrato físico sobre el que funciona el resto de este mapa: el almacenamiento y el cómputo detrás de las redes de lectores de matrículas, los sistemas de registros y las analíticas vendidas a las agencias. También tienen consecuencias locales inmediatas: demanda de electricidad y agua, uso del suelo, ruido, exenciones fiscales y costos de red que pagan otros usuarios. Donde una comunidad se ha organizado, esta capa muestra la campaña para que pueda encontrarla en lugar de empezar de cero.
- Refresh cadence
- Periodic — re-pulled from the source on a schedule.
- Atribución
- FracTracker Alliance
Known gaps and caveats
- Compiled from permit filings obtained by FOIA. A permit is not proof a facility was built, and a built facility may have changed hands since.
- Power source and operating status are not in the upstream record and are left null rather than guessed.
- Community-response fields come from data/community/data-center-campaigns.json and are populated only where a contributor has cited a public source.
- Includes enterprise server rooms alongside hyperscale campuses; the upstream file does not distinguish them by size.
Methodology
Geocoding
Two of these sources publish records with no coordinates at all. ICE lists 287(g) agreements by agency and county, and its detention roster gives only a city and state. We resolve those to positions using US Census reference geography: county interior points from the 2023 Gazetteer, and boundaries from Census TIGERweb. An interior point is guaranteed to fall inside its county, which matters in Minnesota where a bounding-box centre can land in open water.
This means a 287(g) dot marks a jurisdiction, not a building. Where several agencies share a county, their dots are spread on a small deterministic circle so each stays selectable — a display device, flagged on every affected record, never a claim about where an agency sits.
County assignment
Every record, including ones that arrive with real coordinates, is tested against county boundaries with a ray-casting point-in-polygon check. That is what lets the "near me" view answer a question that spans layers — your county's sheriff agreements, the cameras around you, and the housing-policy history of the ground you are standing on — from one lookup.
Location lookup and privacy
The place search ships as a static file of Minnesota places drawn from the Census Gazetteer, and the entire lookup runs in your browser. Sending a typed address to a geocoding service would hand a third party exactly the information this project promises not to collect, so we do not do it. The trade is precision: results are town-level, not street-level. Browser geolocation, if you choose it, is read into memory and never stored or transmitted.
What we refuse to ingest
No layer here describes a person. Not detainees, not officers, not agents, not residents. Where an upstream source mixes individual records into a systemic dataset, we take the systemic part and drop the rest. This is a boundary in the ingest code, not a preference — see what this is and is not.
Reproducing this data
Every dataset here is rebuilt by a script in scripts/ingest/ that reads only public sources and needs no API key. Running npm run data reproduces all of it from scratch. If a number on this site is wrong, the script that produced it is readable and the upstream source is linked above.