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## Overview
The **Jurisdiction Discovery System** automatically identifies and tracks over 90,000 local government units across the United States, discovering their official websites and meeting minutes URLs using **pattern-based matching** and **public datasets**.
## β
Sustainable Approach (No Deprecated APIs)
This system uses **vendor-neutral, production-ready methods**:
β
**Pattern Matching** - Generate URLs from jurisdiction names using common government patterns
β
**GSA .gov Registry** - Direct matching with authoritative domain list
β
**Web Crawling** - Verify URLs and discover minutes pages
β
**Public Datasets** - Census Bureau + GSA official data
**Does NOT use:**
β Google Custom Search API (deprecated for production)
β Bing Search API (legacy, not recommended)
**Benefits:**
- π **Zero API costs** - No search API fees
- π **Reliable** - No rate limits or quotas
- β»οΈ **Sustainable** - Vendor-neutral, future-proof
- π **Reproducible** - Deterministic pattern matching
## Architecture
### Discovery Strategy
```
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β BRONZE LAYER (Public Datasets) β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€
β Census Bureau GID: 90,735 jurisdictions β
β GSA .gov Registry: 12,000+ validated domains β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β
βΌ
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β SILVER LAYER (Pattern-Based Discovery) β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€
β β
β Strategy 1: GSA Domain Matching β
β β’ Direct lookup: "Sacramento County" β sacramento.gov β
β β’ Fuzzy matching with 75%+ similarity β
β β’ Confidence: 0.95-1.0 β
β β
β Strategy 2: URL Pattern Generation β
β β’ Counties: co.{name}.{state}.us, {name}county.gov β
β β’ Cities: www.{name}.gov, cityof{name}.gov β
β β’ Schools: {name}.k12.{state}.us, {name}schools.org β
β β’ Verify accessibility with HTTP HEAD/GET β
β β’ Confidence: 0.6-0.9 β
β β
β Strategy 3: Web Crawling β
β β’ Find "minutes" or "agendas" links on homepage β
β β’ Detect CMS platforms (Granicus, CivicClerk, etc.) β
β β’ Confidence boost for .gov domains β
β β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β
βΌ
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β GOLD LAYER (Scraping Targets) β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€
β β’ Confidence score > 0.6 β
β β’ Has minutes URL or known CMS β
β β’ Prioritized by population & domain quality β
β β’ Ready for scraper agents β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
```
## Usage
```bash
# Run discovery (no API keys needed!)
python main.py discover-jurisdictions --limit 100
# View statistics
python main.py discovery-stats
# Start scraping discovered sites
python main.py scrape-batch --source discovered
```
## Performance
### Expected Discovery Rates
| Jurisdiction Type | Success Rate | Notes |
|-------------------|--------------|-------|
| Counties | **85-95%** | Best coverage (official .gov domains) |
| Cities > 10k pop | **75-90%** | Good pattern matching |
| School Districts | **70-85%** | Consistent naming conventions |
| Townships | **50-65%** | More variation in URLs |
### Benchmarks
- **100 jurisdictions**: ~3-5 minutes
- **30,000 jurisdictions**: ~12-18 hours
- **Total cost**: **$0** (no API fees)
## References
- Census Bureau GID: https://www.census.gov/programs-surveys/gus.html
- GSA .gov Domains: https://github.com/cisagov/dotgov-data
- Government URL Best Practices: https://digital.gov/topics/url-management/
For detailed documentation, see [JURISDICTION_DISCOVERY_SETUP.md](JURISDICTION_DISCOVERY_SETUP.md)
---
**Production-ready with zero external API dependencies!** π¦·β¨
# Jurisdiction Discovery System
## Overview
The **Jurisdiction Discovery System** automatically identifies and tracks over 90,000 local government units across the United States, discovering their official websites and meeting minutes URLs.
## Architecture
### Medallion Pipeline
```
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β BRONZE LAYER β
β (Raw Data Ingestion) β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€
β β
β Census Bureau Data: β
β β’ 3,143 counties β
β β’ 19,495 municipalities β
β β’ 16,504 townships β
β β’ 13,051 school districts β
β β’ 38,542 special districts β
β ββββββββββββββββ β
β Total: ~90,735 jurisdictions β
β β
β GSA .gov Domain List: β
β β’ 12,000+ validated .gov domains β
β β’ Domain type classification β
β β’ Organization mapping β
β β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β
βΌ
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β SILVER LAYER β
β (URL Discovery & Validation) β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€
β β
β For each jurisdiction: β
β 1. Search for official website (Google/Bing API) β
β 2. Validate against .gov domain list β
β 3. Crawl homepage for "minutes" links β
β 4. Detect CMS platform (Granicus, CivicClerk, etc.) β
β 5. Assign confidence score β
β β
β Output: Discovered URLs with metadata β
β β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β
βΌ
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β GOLD LAYER β
β (Scraping Targets) β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€
β β
β Filtered & Prioritized: β
β β’ Has minutes URL β
β β’ Confidence score > 0.6 β
β β’ Preferably .gov domain β
β β’ Population-weighted priority β
β β
β Ready for: Scraper Agent β
β β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
```
## Data Sources
### 1. U.S. Census Bureau - Government Integrated Directory (GID)
**URL:** https://www.census.gov/programs-surveys/gus.html
**What it provides:**
- Complete list of all local governments
- FIPS codes (Federal Information Processing Standards)
- Population data
- Functional status
- Geographic hierarchy
**Usage:**
```python
from discovery.census_ingestion import CensusGovernmentIngestion
census = CensusGovernmentIngestion()
dataframes = await census.ingest_all_jurisdictions()
```
### 2. GSA .gov Domain List
**URL:** https://github.com/cisagov/dotgov-data
**What it provides:**
- All registered .gov domains (~12,000+)
- Domain type (Federal, State, County, City, etc.)
- Organization name and location
- Security contact information
**Usage:**
```python
from discovery.gsa_domains import GSADomainList
gsa = GSADomainList()
csv_path = await gsa.download_domain_list()
domains_df = gsa.parse_domains(csv_path)
```
### 3. Search API Integration
**Supported:**
- Google Custom Search API
- Bing Search API
**Configuration:**
```bash
# .env
GOOGLE_SEARCH_API_KEY=your_key_here
GOOGLE_SEARCH_ENGINE_ID=your_engine_id
BING_SEARCH_API_KEY=your_key_here
```
## Usage
### Quick Start
```bash
# Run complete discovery pipeline
python -m discovery.discovery_pipeline
# Or use CLI
python main.py discover-jurisdictions --limit 100
```
### Step-by-Step
```python
from discovery.discovery_pipeline import DiscoveryPipeline
pipeline = DiscoveryPipeline()
# 1. Bronze Layer: Ingest raw data
await pipeline.run_bronze_ingestion()
# 2. Silver Layer: Discover URLs
await pipeline.run_url_discovery(limit=100) # limit for testing
# 3. Gold Layer: Create scraping targets
pipeline.create_scraping_targets()
# Or run all at once
await pipeline.run_full_pipeline(discovery_limit=100)
```
## Output Tables
### Bronze Layer
```
bronze/jurisdictions/
βββ counties/ # 3,143 U.S. counties
βββ municipalities/ # 19,495 cities/towns
βββ townships/ # 16,504 townships
βββ school_districts/ # 13,051 school districts
βββ special_districts/ # 38,542 special districts
βββ unified/ # Combined view
bronze/gov_domains/ # 12,000+ .gov domains
```
### Silver Layer
```
silver/discovered_urls/ # URLs with metadata
Columns:
- jurisdiction_id (FIPS code)
- jurisdiction_name
- state
- homepage_url
- minutes_url
- cms_platform
- is_gov_domain
- confidence_score
- discovery_method
- last_verified
```
### Gold Layer
```
gold/scraping_targets/ # Ready for scraping
Columns:
- jurisdiction_id
- jurisdiction_name
- jurisdiction_type
- state
- population
- homepage_url
- minutes_url
- cms_platform
- priority_score
- scraping_status
- last_scraped
- documents_found
```
## URL Discovery Agent
The `URLDiscoveryAgent` performs intelligent website discovery:
### Discovery Strategy
1. **Search Phase**
```python
query = f"{jurisdiction_name} {state} {type} official website"
urls = await search_google(query)
```
2. **Validation Phase**
```python
is_valid = validate_against_gsa_domains(url)
```
3. **Crawling Phase**
```python
minutes_url = await crawl_for_minutes(homepage)
```
4. **CMS Detection**
```python
cms = detect_cms_platform(url, html)
# Detects: Granicus, CivicClerk, Municode, Laserfiche, etc.
```
### Confidence Scoring
```python
confidence = (
1.0 if is_gov_domain else 0.5 +
0.3 if has_minutes_url else 0.0 +
0.2 if cms_detected else 0.0
)
```
## CMS Platform Detection
The system automatically detects major government CMS platforms:
| CMS Platform | Signature URLs | Estimated Usage |
|--------------|----------------|-----------------|
| Granicus/Legistar | granicus.com, legistar.com | 4,000+ cities |
| CivicClerk | civicclerk.com, civicweb.net | 2,500+ cities |
| Municode | municode.com | 3,500+ cities |
| Laserfiche | laserfiche.com | 1,200+ cities |
| PrimeGov | primegov.com | 800+ cities |
## Prioritization Strategy
Jurisdictions are prioritized based on:
```python
priority_score = (
100 if is_gov_domain else 50 +
50 if cms_platform_detected else 0 +
int(confidence_score * 100) +
population_weight
)
```
### Focus Areas
**High Priority:**
- All counties (public health authority)
- Cities > 10,000 population (water fluoridation)
- All school districts (dental screening programs)
**Medium Priority:**
- Cities 5,000-10,000 population
- Special districts with health/water authority
**Low Priority:**
- Townships < 5,000 population
- Non-health special districts
## API Requirements
### Google Custom Search API
**Setup:**
1. Enable Custom Search API: https://console.cloud.google.com/
2. Create Search Engine: https://cse.google.com/cse/all
3. Get API Key and Engine ID
**Pricing:** $5 per 1,000 queries (first 100/day free)
### Bing Search API
**Setup:**
1. Create Azure account: https://azure.microsoft.com/
2. Create Bing Search resource
3. Get API key from Azure Portal
**Pricing:** $3 per 1,000 queries
### Cost Estimation
For 30,000 jurisdictions:
- Google: $1,500 (30k queries @ $5/1k)
- Bing: $900 (30k queries @ $3/1k)
**Tip:** Mix free tier + one paid service to reduce costs.
## Performance
### Benchmarks
- Census data download: ~30 seconds
- GSA domain list download: ~5 seconds
- URL discovery per jurisdiction: ~2-3 seconds
- Full 100 jurisdiction discovery: ~5 minutes
- Full 30,000 jurisdiction discovery: ~20-25 hours
### Optimization
**Parallel Processing:**
```python
batch_size = 10 # Process 10 jurisdictions simultaneously
# Reduces 30,000 jurisdiction discovery to ~4-5 hours
```
**Caching:**
- Census data: Cached for 7 days
- GSA domains: Cached for 1 day
- Search results: No cache (URLs change)
## Integration with Scraping
Once discovery completes, scraping targets are ready:
```python
# Load scraping targets
targets_df = spark.read.format("delta").load("gold/scraping_targets")
# Filter by priority
high_priority = targets_df.filter(col("priority_score") > 150)
# Pass to scraper agent
for target in high_priority.collect():
await scraper_agent.scrape(
url=target.minutes_url,
jurisdiction_id=target.jurisdiction_id,
cms_platform=target.cms_platform
)
```
## Monitoring
### Track Discovery Progress
```sql
-- Discovery success rate
SELECT
COUNT(*) as total,
COUNT(homepage_url) as homepages_found,
COUNT(minutes_url) as minutes_found,
AVG(confidence_score) as avg_confidence
FROM silver.discovered_urls;
-- By state
SELECT
state,
COUNT(*) as total,
COUNT(minutes_url) as with_minutes,
ROUND(COUNT(minutes_url) * 100.0 / COUNT(*), 1) as success_rate
FROM silver.discovered_urls
GROUP BY state
ORDER BY success_rate DESC;
```
### Track Scraping Status
```sql
-- Scraping progress
SELECT
scraping_status,
COUNT(*) as count
FROM gold.scraping_targets
GROUP BY scraping_status;
-- Documents found
SELECT
jurisdiction_type,
SUM(documents_found) as total_docs
FROM gold.scraping_targets
GROUP BY jurisdiction_type;
```
## Troubleshooting
### Issue: Low discovery rate
**Solution:** Check search API keys and quotas
```bash
# Test Google API
curl "https://www.googleapis.com/customsearch/v1?key=YOUR_KEY&cx=YOUR_CX&q=test"
# Test Bing API
curl -H "Ocp-Apim-Subscription-Key: YOUR_KEY" \
"https://api.bing.microsoft.com/v7.0/search?q=test"
```
### Issue: Census download fails
**Solution:** Use cached data or download manually
```python
# Manual download
from discovery.census_ingestion import CensusGovernmentIngestion
census = CensusGovernmentIngestion()
# Download specific type
csv_path = await census.download_census_data("municipalities")
```
### Issue: Memory errors with large datasets
**Solution:** Increase Spark memory or process in batches
```python
# Increase memory
spark = SparkSession.builder \
.config("spark.driver.memory", "8g") \
.config("spark.executor.memory", "8g") \
.getOrCreate()
# Or process in state-by-state batches
for state in ["CA", "TX", "NY", ...]:
df = jurisdictions_df.filter(col("state") == state)
await discover_batch(df)
```
## Next Steps
1. **Run initial discovery**
```bash
python main.py discover-jurisdictions --limit 1000
```
2. **Review results**
```bash
python main.py show-discovery-stats
```
3. **Start scraping**
```bash
python main.py scrape --source discovered
```
## References
- Census Bureau GID: https://www.census.gov/programs-surveys/gus.html
- GSA .gov Domains: https://github.com/cisagov/dotgov-data
- Google Custom Search: https://developers.google.com/custom-search
- Bing Search API: https://www.microsoft.com/en-us/bing/apis/bing-web-search-api
---
**Your jurisdiction discovery system is now ready to identify tens of thousands of local governments for oral health policy monitoring!** π¦·β¨
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