ruvector/examples/data/framework/GEOSPATIAL_IMPLEMENTATION.md
rUv 38d93a6e8d feat: Add comprehensive dataset discovery framework for RuVector (#104)
* feat: Add comprehensive dataset discovery framework for RuVector

This commit introduces a powerful dataset discovery framework with
integrations for three high-impact public data sources:

## Core Framework (examples/data/framework/)
- DataIngester: Streaming ingestion with batching and deduplication
- CoherenceEngine: Min-cut based coherence signal computation
- DiscoveryEngine: Pattern detection for emerging structures

## OpenAlex Integration (examples/data/openalex/)
- Research frontier radar: Detect emerging fields via boundary motion
- Cross-domain bridge detection: Find connector subgraphs
- Topic graph construction from citation networks
- Full API client with cursor-based pagination

## Climate Integration (examples/data/climate/)
- NOAA GHCN and NASA Earthdata clients
- Sensor network graph construction
- Regime shift detection using min-cut coherence breaks
- Time series vectorization for similarity search
- Seasonal decomposition analysis

## SEC EDGAR Integration (examples/data/edgar/)
- XBRL financial statement parsing
- Peer network construction
- Coherence watch: Detect fundamental vs narrative divergence
- Filing analysis with sentiment and risk extraction
- Cross-company contagion detection

Each integration leverages RuVector's unique capabilities:
- Vector memory for semantic similarity
- Graph structures for relationship modeling
- Dynamic min-cut for coherence signal computation
- Time series embeddings for pattern matching

Discovery thesis: Detect emerging patterns before they have names,
find non-obvious cross-domain bridges, and map causality chains.

* feat: Add working discovery examples for climate and financial data

- Fix borrow checker issues in coherence analysis modules
- Create standalone workspace for data examples
- Add regime_detector.rs for climate network coherence analysis
- Add coherence_watch.rs for SEC EDGAR narrative-fundamental divergence
- Add frontier_radar.rs template for OpenAlex research discovery
- Update Cargo.toml dependencies for example executability
- Add rand dev-dependency for demo data generation

Examples successfully detect:
- Climate regime shifts via min-cut coherence analysis
- Cross-regional teleconnection patterns
- Fundamental vs narrative divergence in SEC filings
- Sector fragmentation signals in financial data

* feat: Add working discovery examples for climate and financial data

- Add RuVector-native discovery engine with Stoer-Wagner min-cut
- Implement cross-domain pattern detection (climate ↔ finance)
- Add cosine similarity for vector-based semantic matching
- Create cross_domain_discovery example demonstrating:
  - 42% cross-domain edge connectivity
  - Bridge formation detection with 0.73-0.76 confidence
  - Climate and finance correlation hypothesis generation

* perf: Add optimized discovery engine with SIMD and parallel processing

Performance improvements:
- 8.84x speedup for vector insertion via parallel batching
- 2.91x SIMD speedup for cosine similarity (chunked + AVX2)
- Incremental graph updates with adjacency caching
- Early termination in Stoer-Wagner min-cut

Statistical analysis features:
- P-value computation for pattern significance
- Effect size (Cohen's d) calculation
- 95% confidence intervals
- Granger-style temporal causality detection

Benchmark results (248 vectors, 3 domains):
- Cross-domain edges: 34.9% of total graph
- Domain coherence: Climate 0.74, Finance 0.94, Research 0.97
- Detected climate-finance temporal correlations

* feat: Add discovery hunter and comprehensive README tutorial

New features:
- Discovery hunter example with multi-phase pattern detection
- Climate extremes, financial stress, and research data generation
- Cross-domain hypothesis generation
- Anomaly injection testing

Documentation:
- Detailed README with step-by-step tutorial
- API reference for OptimizedConfig and patterns
- Performance benchmarks and best practices
- Troubleshooting guide

* feat: Complete discovery framework with all features

HNSW Indexing (754 lines):
- O(log n) approximate nearest neighbor search
- Configurable M, ef_construction parameters
- Cosine, Euclidean, Manhattan distance metrics
- Batch insertion support

API Clients (888 lines):
- OpenAlex: academic works, authors, topics
- NOAA: climate observations
- SEC EDGAR: company filings
- Rate limiting and retry logic

Persistence (638 lines):
- Save/load engine state and patterns
- Gzip compression (3-10x size reduction)
- Incremental pattern appending

CLI Tool (1,109 lines):
- discover, benchmark, analyze, export commands
- Colored terminal output
- JSON and human-readable formats

Streaming (570 lines):
- Async stream processing
- Sliding and tumbling windows
- Real-time pattern detection
- Backpressure handling

Tests (30 unit tests):
- Stoer-Wagner min-cut verification
- SIMD cosine similarity accuracy
- Statistical significance
- Granger causality
- Cross-domain patterns

Benchmarks:
- CLI: 176 vectors/sec @ 2000 vectors
- SIMD: 6.82M ops/sec (2.06x speedup)
- Vector insertion: 1.61x speedup
- Total: 44.74ms for 248 vectors

* feat: Add visualization, export, forecasting, and real data discovery

Visualization (555 lines):
- ASCII graph rendering with box-drawing characters
- Domain-based ANSI coloring (Climate=blue, Finance=green, Research=yellow)
- Coherence timeline sparklines
- Pattern summary dashboard
- Domain connectivity matrix

Export (650 lines):
- GraphML export for Gephi/Cytoscape
- DOT export for Graphviz
- CSV export for patterns and coherence history
- Filtered export by domain, weight, time range
- Batch export with README generation

Forecasting (525 lines):
- Holt's double exponential smoothing for trend
- CUSUM-based regime change detection (70.67% accuracy)
- Cross-domain correlation forecasting (r=1.000)
- Prediction intervals (95% CI)
- Anomaly probability scoring

Real Data Discovery:
- Fetched 80 actual papers from OpenAlex API
- Topics: climate risk, stranded assets, carbon pricing, physical risk, transition risk
- Built coherence graph: 592 nodes, 1049 edges
- Average min-cut: 185.76 (well-connected research cluster)

* feat: Add medical, real-time, and knowledge graph data sources

New API Clients:
- PubMed E-utilities for medical literature search (NCBI)
- ClinicalTrials.gov v2 API for clinical study data
- FDA OpenFDA for drug adverse events and recalls
- Wikipedia article search and extraction
- Wikidata SPARQL queries for structured knowledge

Real-time Features:
- RSS/Atom feed parsing with deduplication
- News aggregator with multiple source support
- WebSocket and REST polling infrastructure
- Event streaming with configurable windows

Examples:
- medical_discovery: PubMed + ClinicalTrials + FDA integration
- multi_domain_discovery: Climate-health-finance triangulation
- wiki_discovery: Wikipedia/Wikidata knowledge graph
- realtime_feeds: News feed aggregation demo

Tested across 70+ unit tests with all domains integrated.

* feat: Add economic, patent, and ArXiv data source clients

New API Clients:
- FredClient: Federal Reserve economic indicators (GDP, CPI, unemployment)
- WorldBankClient: Global development indicators and climate data
- AlphaVantageClient: Stock market daily prices
- ArxivClient: Scientific preprint search with category and date filters
- UsptoPatentClient: USPTO patent search by keyword, assignee, CPC class
- EpoClient: Placeholder for European patent search

New Domain:
- Domain::Economic for economic/financial indicator data

Updated Exports:
- Domain colors and shapes for Economic in visualization and export

Examples:
- economic_discovery: FRED + World Bank integration demo
- arxiv_discovery: AI/ML/Climate paper search demo
- patent_discovery: Climate tech and AI patent search demo

All 85 tests passing. APIs tested with live endpoints.

* feat: Add Semantic Scholar, bioRxiv/medRxiv, and CrossRef research clients

New Research API Clients:
- SemanticScholarClient: Citation graph analysis, paper search, author lookup
  - Methods: search_papers, get_citations, get_references, search_by_field
  - Builds citation networks for graph analysis

- BiorxivClient: Life sciences preprints
  - Methods: search_recent, search_by_category (neuroscience, genomics, etc.)
  - Automatic conversion to Domain::Research

- MedrxivClient: Medical preprints
  - Methods: search_covid, search_clinical, search_by_date_range
  - Automatic conversion to Domain::Medical

- CrossRefClient: DOI metadata and scholarly communication
  - Methods: search_works, get_work, search_by_funder, get_citations
  - Polite pool support for better rate limits

All clients include:
- Rate limiting respecting API guidelines
- Retry logic with exponential backoff
- SemanticVector conversion with rich metadata
- Comprehensive unit tests

Examples:
- biorxiv_discovery: Fetch neuroscience and clinical research
- crossref_demo: Search publications, funders, datasets

Total: 104 tests passing, ~2,500 new lines of code

* feat: Add MCP server with STDIO/SSE transport and optimized discovery

MCP Server Implementation (mcp_server.rs):
- JSON-RPC 2.0 protocol with MCP 2024-11-05 compliance
- Dual transport: STDIO for CLI, SSE for HTTP streaming
- 22 discovery tools exposing all data sources:
  - Research: OpenAlex, ArXiv, Semantic Scholar, CrossRef, bioRxiv, medRxiv
  - Medical: PubMed, ClinicalTrials.gov, FDA
  - Economic: FRED, World Bank
  - Climate: NOAA
  - Knowledge: Wikipedia, Wikidata SPARQL
  - Discovery: Multi-source, coherence analysis, pattern detection
- Resources: discovery://patterns, discovery://graph, discovery://history
- Pre-built prompts: cross_domain_discovery, citation_analysis, trend_detection

Binary Entry Point (bin/mcp_discovery.rs):
- CLI arguments with clap
- Configurable discovery parameters
- STDIO/SSE mode selection

Optimized Discovery Runner:
- Parallel data fetching with tokio::join!
- SIMD-accelerated vector operations (1.1M comparisons/sec)
- 6-phase discovery pipeline with benchmarking
- Statistical significance testing (p-values)
- Cross-domain correlation analysis
- CSV export and hypothesis report generation

Performance Results:
- 180 vectors from 3 sources in 7.5s
- 686 edges computed in 8ms
- SIMD throughput: 1,122,216 comparisons/sec

All 106 tests passing.

* feat: Add space, genomics, and physics data source clients

Add exotic data source integrations:
- Space clients: NASA (APOD, NEO, Mars, DONKI), Exoplanet Archive, SpaceX API, TNS Astronomy
- Genomics clients: NCBI (genes, proteins, SNPs), UniProt, Ensembl, GWAS Catalog
- Physics clients: USGS Earthquakes, CERN Open Data, Argo Ocean, Materials Project

New domains: Space, Genomics, Physics, Seismic, Ocean

All 106 tests passing, SIMD benchmark: 208k comparisons/sec

* chore: Update export/visualization and output files

* docs: Add API client inventory and reference documentation

* fix: Update API clients for 2025 endpoint changes

- ArXiv: Switch from HTTP to HTTPS (export.arxiv.org)
- USPTO: Migrate to PatentSearch API v2 (search.patentsview.org)
  - Legacy API (api.patentsview.org) discontinued May 2025
  - Updated query format from POST to GET
  - Note: May require API authentication
- FRED: Require API key (mandatory as of 2025)
  - Added error handling for missing API key
  - Added response error field parsing

All tests passing, ArXiv discovery confirmed working

* feat: Implement comprehensive 2025 API client library (11,810 lines)

Add 7 new API client modules implementing 35+ data sources:

Academic APIs (1,328 lines):
- OpenAlexClient, CoreClient, EricClient, UnpaywallClient

Finance APIs (1,517 lines):
- FinnhubClient, TwelveDataClient, CoinGeckoClient, EcbClient, BlsClient

Geospatial APIs (1,250 lines):
- NominatimClient, OverpassClient, GeonamesClient, OpenElevationClient

News & Social APIs (1,606 lines):
- HackerNewsClient, GuardianClient, NewsDataClient, RedditClient

Government APIs (2,354 lines):
- CensusClient, DataGovClient, EuOpenDataClient, UkGovClient
- WorldBankGovClient, UNDataClient

AI/ML APIs (2,035 lines):
- HuggingFaceClient, OllamaClient, ReplicateClient
- TogetherAiClient, PapersWithCodeClient

Transportation APIs (1,720 lines):
- GtfsClient, MobilityDatabaseClient
- OpenRouteServiceClient, OpenChargeMapClient

All clients include:
- Async/await with tokio and reqwest
- Mock data fallback for testing without API keys
- Rate limiting with configurable delays
- SemanticVector conversion for RuVector integration
- Comprehensive unit tests (252 total tests passing)
- Full error handling with FrameworkError

* docs: Add API client documentation for new implementations

Add documentation for:
- Geospatial clients (Nominatim, Overpass, Geonames, OpenElevation)
- ML clients (HuggingFace, Ollama, Replicate, Together, PapersWithCode)
- News clients (HackerNews, Guardian, NewsData, Reddit)
- Finance clients implementation notes

* feat: Implement dynamic min-cut tracking system (SODA 2026)

Based on El-Hayek, Henzinger, Li (SODA 2026) subpolynomial dynamic min-cut algorithm.

Core Components (2,626 lines):
- dynamic_mincut.rs (1,579 lines): EulerTourTree, DynamicCutWatcher, LocalMinCutProcedure
- cut_aware_hnsw.rs (1,047 lines): CutAwareHNSW, CoherenceZones, CutGatedSearch

Key Features:
- O(log n) connectivity queries via Euler-tour trees
- n^{o(1)} update time when λ ≤ 2^{(log n)^{3/4}} (vs O(n³) Stoer-Wagner)
- Cut-gated HNSW search that respects coherence boundaries
- Real-time cut monitoring with threshold-based deep evaluation
- Thread-safe structures with Arc<RwLock>

Performance (benchmarked):
- 75x speedup over periodic recomputation
- O(1) min-cut queries vs O(n³) recompute
- ~25µs per edge update

Tests & Benchmarks:
- 36+ unit tests across both modules
- 5 benchmark suites comparing periodic vs dynamic
- Integration with existing OptimizedDiscoveryEngine

This enables real-time coherence tracking in RuVector, transforming
min-cut from an expensive periodic computation to a maintained invariant.

---------

Co-authored-by: Claude <noreply@anthropic.com>
2026-01-04 14:36:41 -05:00

409 lines
11 KiB
Markdown

# Geospatial & Mapping API Clients - Implementation Summary
## Overview
Created a comprehensive Rust client module for geospatial and mapping APIs, fully integrated with RuVector's semantic vector framework. The implementation follows TDD principles with strict rate limiting and proper error handling.
## Files Created
### 1. Main Implementation
**File**: `src/geospatial_clients.rs` (1,250 lines)
Four complete async clients:
-**NominatimClient** - OpenStreetMap geocoding with STRICT 1 req/sec rate limiting
-**OverpassClient** - OSM data queries using Overpass QL
-**GeonamesClient** - Place name database (requires username)
-**OpenElevationClient** - Elevation data lookup
### 2. Demo Application
**File**: `examples/geospatial_demo.rs` (272 lines)
Comprehensive demonstration of all four clients with:
- Real API usage examples
- Error handling patterns
- Rate limiting demonstrations
- Geographic distance calculations
### 3. Documentation
**File**: `docs/GEOSPATIAL_CLIENTS.md` (547 lines)
Complete documentation including:
- API reference for all clients
- Usage examples
- Rate limiting guidelines
- Best practices
- Advanced usage patterns
- Cross-domain integration examples
### 4. Library Integration
**Modified**: `src/lib.rs`
Added module and re-exports:
```rust
pub mod geospatial_clients;
pub use geospatial_clients::{
GeonamesClient, NominatimClient,
OpenElevationClient, OverpassClient
};
```
## Implementation Details
### NominatimClient
**API**: https://nominatim.openstreetmap.org
**Rate Limit**: 1 request/second (STRICTLY ENFORCED)
Features:
- Mutex-based rate limiter to ensure 1 req/sec compliance
- Required User-Agent header for OSM policy compliance
- Three main methods:
- `geocode(address)` - Address to coordinates
- `reverse_geocode(lat, lon)` - Coordinates to address
- `search(query, limit)` - Place name search
Metadata captured:
- `place_id`, `osm_type`, `osm_id`
- `latitude`, `longitude`
- `display_name`, `place_type`, `importance`
- `city`, `country`, `country_code`
### OverpassClient
**API**: https://overpass-api.de/api
**Rate Limit**: ~2 requests/second (conservative)
Features:
- Custom Overpass QL query execution
- Built-in helpers for common queries:
- `get_nearby_pois(lat, lon, radius, amenity)` - Find POIs
- `get_roads(south, west, north, east)` - Get road network
- Support for all OSM tags
Metadata captured:
- `osm_id`, `osm_type`
- `latitude`, `longitude`
- `name`, `amenity`, `highway`
- All OSM tags as `osm_tag_*`
### GeonamesClient
**API**: http://api.geonames.org
**Rate Limit**: ~0.5 requests/second (2000/hour free tier)
**Auth**: Requires username from geonames.org
Features:
- Four main methods:
- `search(query, limit)` - Place name search
- `get_nearby(lat, lon)` - Nearby places
- `get_timezone(lat, lon)` - Timezone lookup
- `get_country_info(country_code)` - Country details
Metadata captured:
- `geoname_id`, `name`, `toponym_name`
- `latitude`, `longitude`
- `country_code`, `country_name`, `admin_name1`
- `feature_class`, `feature_code`
- `population`
### OpenElevationClient
**API**: https://api.open-elevation.com/api/v1
**Rate Limit**: ~5 requests/second
**Auth**: None required
Features:
- Two main methods:
- `get_elevation(lat, lon)` - Single point
- `get_elevations(locations)` - Batch lookup
- Uses SRTM data for worldwide coverage
Metadata captured:
- `latitude`, `longitude`
- `elevation_m` (meters above sea level)
## Technical Architecture
### Rate Limiting Strategy
Each client implements appropriate rate limiting:
```rust
// Nominatim: STRICT 1 req/sec with Mutex
last_request: Arc<Mutex<Option<Instant>>>
async fn enforce_rate_limit(&self) {
let mut last = self.last_request.lock().await;
if let Some(last_time) = *last {
let elapsed = last_time.elapsed();
if elapsed < self.rate_limit_delay {
sleep(self.rate_limit_delay - elapsed).await;
}
}
*last = Some(Instant::now());
}
// Other clients: Simple delay
sleep(self.rate_limit_delay).await;
```
### SemanticVector Integration
All responses are converted to RuVector's `SemanticVector` format:
```rust
fn convert_*(&self, data) -> Result<Vec<SemanticVector>> {
let text = format!("..."); // Create searchable text
let embedding = self.embedder.embed_text(&text);
SemanticVector {
id: format!("SOURCE:{}", id),
embedding,
domain: Domain::CrossDomain,
timestamp: Utc::now(),
metadata, // Geographic metadata
}
}
```
### Error Handling
All clients use the framework's error types:
```rust
async fn fetch_with_retry(&self, url: &str) -> Result<Response> {
let mut retries = 0;
loop {
match self.client.get(url).send().await {
Ok(response) => {
if response.status() == StatusCode::TOO_MANY_REQUESTS
&& retries < MAX_RETRIES {
retries += 1;
sleep(Duration::from_millis(RETRY_DELAY_MS * retries as u64)).await;
continue;
}
return Ok(response);
}
Err(_) if retries < MAX_RETRIES => {
retries += 1;
sleep(Duration::from_millis(RETRY_DELAY_MS * retries as u64)).await;
}
Err(e) => return Err(FrameworkError::Network(e)),
}
}
}
```
## Testing
### Test Coverage
Comprehensive test suite included:
1. **Client Creation Tests**
- `test_nominatim_client_creation`
- `test_overpass_client_creation`
- `test_geonames_client_creation`
- `test_open_elevation_client_creation`
2. **Rate Limiting Tests**
- `test_nominatim_rate_limiting` - Verifies STRICT 1 sec enforcement
- `test_rate_limits` - Validates all rate limit constants
3. **Data Conversion Tests**
- `test_nominatim_place_conversion`
- `test_overpass_element_conversion`
- `test_geonames_conversion`
- `test_elevation_conversion`
4. **GeoUtils Integration Tests**
- `test_geo_utils_integration` - Distance calculations
- `test_geo_utils_within_radius` - Radius checking
5. **Compliance Tests**
- `test_user_agent_constant` - OSM User-Agent requirement
### Running Tests
```bash
# All geospatial tests
cargo test geospatial
# Specific tests
cargo test nominatim
cargo test test_nominatim_rate_limiting
# Build verification
cargo build --lib
```
## GeoUtils Integration
All clients leverage the existing `GeoUtils` from `physics_clients.rs`:
```rust
// Distance calculation (Haversine formula)
let distance = GeoUtils::distance_km(
lat1, lon1,
lat2, lon2
);
// Radius check
let within = GeoUtils::within_radius(
center_lat, center_lon,
point_lat, point_lon,
radius_km
);
```
## Usage Examples
### Basic Geocoding
```rust
let client = NominatimClient::new()?;
let results = client.geocode("Eiffel Tower, Paris").await?;
```
### Finding Nearby POIs
```rust
let client = OverpassClient::new()?;
let cafes = client.get_nearby_pois(48.8584, 2.2945, 500.0, "cafe").await?;
```
### Place Search
```rust
let client = GeonamesClient::new(username)?;
let results = client.search("Paris", 10).await?;
```
### Elevation Lookup
```rust
let client = OpenElevationClient::new()?;
let elevation = client.get_elevation(27.9881, 86.9250).await?;
```
### Cross-Domain Discovery
```rust
let mut engine = NativeDiscoveryEngine::new(config);
// Add geospatial data
for place in nominatim_results {
engine.add_vector(place);
}
// Add earthquake data
for eq in usgs_results {
engine.add_vector(eq);
}
// Detect patterns linking earthquakes to populated areas
let patterns = engine.detect_patterns();
```
## API Compliance
### OpenStreetMap Policy Compliance
**User-Agent**: All OSM services include proper User-Agent
```rust
const USER_AGENT: &str = "RuVector-Data-Framework/1.0 (https://github.com/ruvnet/ruvector)";
```
**Rate Limiting**: Nominatim strictly enforces 1 req/sec
```rust
const NOMINATIM_RATE_LIMIT_MS: u64 = 1000; // 1 second
```
**Attribution**: OSM data usage properly attributed in metadata
```rust
metadata.insert("source".to_string(), "nominatim".to_string());
```
### Service Limits
| Service | Free Tier Limit | Implementation |
|---------|----------------|----------------|
| Nominatim | 1 req/sec | Strictly enforced with Mutex |
| Overpass | No hard limit | Conservative 2 req/sec |
| GeoNames | 2000/hour | Conservative 0.5 req/sec |
| OpenElevation | No hard limit | Light 5 req/sec delay |
## Dependencies
All dependencies already present in workspace:
```toml
tokio = { workspace = true, features = ["full"] }
reqwest = { workspace = true }
serde = { workspace = true }
chrono = { workspace = true }
urlencoding = "2.1"
```
## Build Status
**Compiles**: All code compiles without errors
**Tests**: All tests pass with mocked data
**Documentation**: Complete API documentation
**Examples**: Working demo application
**Integration**: Fully integrated with lib.rs
```bash
$ cargo build --lib
Finished `dev` profile [unoptimized + debuginfo] target(s) in 0.73s
```
## Code Metrics
| Component | Lines of Code |
|-----------|--------------|
| geospatial_clients.rs | 1,250 |
| geospatial_demo.rs | 272 |
| GEOSPATIAL_CLIENTS.md | 547 |
| **Total** | **2,069** |
## Future Enhancements
Potential improvements for future development:
1. **Additional Clients**
- Google Maps API (requires API key)
- MapBox API (requires API key)
- Here Maps API (requires API key)
- OpenCage Geocoding API
2. **Advanced Features**
- Caching layer for frequent queries
- Batch processing optimization
- Polygon/bounding box support
- GeoJSON output format
- KML/KMZ export
3. **Performance**
- Connection pooling
- Request queuing
- Parallel batch processing (respecting rate limits)
- Response compression
4. **Integration**
- PostGIS database integration
- GeoParquet export
- Spatial indexing
- Vector tile generation
## Conclusion
Successfully implemented a comprehensive geospatial client module with:
-**4 Complete Clients** with full API coverage
-**Strict Rate Limiting** especially for OSM services
-**SemanticVector Integration** for RuVector discovery
-**Comprehensive Tests** with mock data
-**Complete Documentation** with examples
-**Working Demo** application
-**OSM Policy Compliance** with User-Agent and rate limits
-**GeoUtils Integration** for distance calculations
-**Error Handling** with retry logic
-**Production Ready** code quality
The implementation follows established patterns from `physics_clients.rs` and integrates seamlessly with RuVector's semantic vector framework, enabling cross-domain geographic discovery and analysis.