knowwheregraph

is a Knowledge Graph.

KnowWhereGraph is a large-scale geospatial and environmental knowledge graph containing over 29 billion RDF triples. It fuses knowledge graph technology with geo-enrichment capabilities to provide location-centric answers about environmental and human systems globally. The graph integrates 30+ data layers spanning natural hazards, climate, soil properties, demographics, health, agriculture, and more.

Domains

environment, public health

License

CC BY 4.0

Homepage

knowwheregraph

Repository

GitHub

Infores ID

infores:knowwheregraph

FAIRsharing ID

Unknown

Product Summary

Products

From this Resource
ID Name URL Category Format Description
knowwheregraph.graph KnowWhereGraph RDF Knowledge Graph knowwheregraph.org GraphProduct rdfxml KnowWhereGraph knowledge graph with 2...
knowwheregraph.sparql KnowWhereGraph SPARQL Endpoint sparql ProgrammingInterface http SPARQL endpoint with GeoSPARQL suppor...
knowwheregraph.explorer KnowWhereGraph Knowledge Explorer # GraphicalInterface http Faceted search interface providing ta...
knowwheregraph.ontology KnowWhereGraph Ontology Documentation ontology DocumentationProduct http Comprehensive ontology documentation ...

Usages

Humanitarian Response
Humanitarian aid coordination and supply chain management during crises
Supply Chain Management
Food supply chain sustainability, agriculture sustainability assessment
Emergency Management
Disaster response, emergency management, natural hazard assessment
Agricultural Finance
Farm credit assessment, land valuation, agricultural potential evaluation

Details

KnowWhereGraph

Overview

KnowWhereGraph is the first large-scale geospatial and environmental knowledge graph, combining knowledge graph technology with geo-enrichment capabilities to answer fundamental geographic questions: “What is here?”, “What happened here before?”, and “How does this region compare to…?” for any location on Earth within seconds.

The graph contains over 29 billion RDF triples representing densely-integrated statements across diverse environmental and human systems domains. It integrates 30+ data layers spanning natural hazards, climate variables, soil properties, demographics, health indicators, agriculture, and more, creating a comprehensive framework for environmental intelligence and geospatial knowledge discovery.

Data Content and Scale

Graph Statistics

  • Total Triples: 29+ billion RDF statements
  • Node Count: Estimated 5+ billion entities
  • Data Layers Integrated: 30+ diverse datasets
  • Spatial Coverage: Global - designed for any location on Earth

Domains and Topics

KnowWhereGraph covers a comprehensive range of environmental and human systems:

Environmental and Climate:

  • Natural hazards: hurricanes, wildfires, earthquakes, debris flows, severe weather
  • Climate variables: air temperature, precipitation, climate divisions, seasonal patterns
  • Soil properties: soil types, soil characteristics, pedogenic processes
  • Land cover: crop types, land use classifications
  • Water systems: hydrological features, water availability

Human and Social Systems:

  • Demographics: population statistics, population density, population change
  • Human health: health indicators, disease data, health outcomes
  • Transportation: transportation networks, infrastructure data
  • Food systems: agricultural production, food security, food supply chains
  • Expert networks: domain expertise, research networks

Geographic and Spatial:

  • Place and region identifiers: gazetteers, boundaries
  • Hierarchical spatial representations: S2 Discrete Global Grid cells
  • Multiple geographic conceptualizations: ZIP codes, climate divisions, administrative boundaries
  • Geopolitical boundaries: administrative regions, political entities

Data Access and Formats

Query Interfaces

SPARQL Endpoint

  • Direct SPARQL and GeoSPARQL query support
  • Location: https://knowwheregraph.org/sparql/
  • Enables complex geospatial queries across all data layers
  • Supports spatial reasoning and analysis

Knowledge Explorer

  • Web-based faceted search interface
  • Features:
    • Faceted filtering by multiple data characteristics
    • Table view and map view panels for results
    • Automatic SPARQL query generation from user input
    • Hyperlinked result navigation for graph dereferencing
  • Location: https://www.knowwheregraph.org/tools/knowledge-explorer/

GIS Integration

ArcGIS Integration

  • Native ArcGIS Pro plugin for graph queries
  • Automatic geodatabase creation from query results
  • Seamless integration with GIS workflows

QGIS Integration

  • Open-source GIS plugin for graph querying
  • Geo-enrichment capabilities within QGIS
  • Support for adding multidisciplinary geospatial data

Data Format

  • Primary Format: RDF (Resource Description Framework)
  • Standards: OWL (Web Ontology Language), GeoSPARQL, SHACL
  • Ontologies: Custom KnowWhereGraph Ontology, SOSA, OWL-Time, GeoSPARQL
  • Spatial Representation: S2 Hierarchical Discrete Global Grid (DGG)
  • Backend: GraphDB semantic repository

Technical Architecture

Ontology

The KnowWhereGraph Ontology (KWGO) provides the semantic foundation:

  • 150 entity classes for representing concepts
  • 70 object properties for relationships
  • 75 data properties for attributes
  • Modular design for extensibility
  • Alignment with standard semantic web vocabularies

Design Principles

  • Geo-enrichment: Specialized capabilities for linking disparate geospatial datasets
  • Cross-domain integration: Semantic linking across diverse data silos
  • Densely connected: Highly interconnected through inferred relationships
  • Spatially explicit: All data elements have spatial grounding
  • Semantically lifted: Includes novel strategies for lifting imagery data into semantic form

Key Features

Geo-Enrichment Pioneer

KnowWhereGraph is pioneering geo-enrichment capabilities directly integrated into knowledge graphs and GIS environments, enabling:

  • Automatic data enrichment based on spatial relationships
  • Cross-domain insights for any geographic location
  • Multidisciplinary data synthesis at scale

Multi-Interface Access

Multiple complementary interfaces for different use cases:

  • Programmatic access for developers (SPARQL, GeoSPARQL)
  • GIS-native tools for domain specialists (ArcGIS, QGIS)
  • Faceted search for knowledge discovery (Knowledge Explorer)
  • API-based access for application integration

Densely Connected Graph

Highly interconnected relationships enable:

  • Complex multi-hop queries across domains
  • Inference of new knowledge through semantic relationships
  • Comparative analysis across regions and time periods

Semantically Lifted Imagery

Novel approaches to include:

  • Remotely sensed imagery integrated as knowledge graph entities
  • Drone imagery semantically linked to ground-truth data
  • AI-based methods for automated imagery analysis and integration

Use Cases and Applications

Supply Chain Management

  • Food supply chain sustainability and traceability
  • Wildfires impact assessment on agricultural production
  • Commodity market and supply chain analysis
  • Food security assessment and forecasting

Humanitarian Response

  • Emergency response coordination and resource allocation
  • Expert-need matching during crises
  • Humanitarian aid supply chain management
  • Crisis situation awareness and rapid assessment

Disaster Management

  • Natural hazard monitoring and forecasting
  • Emergency management planning and response
  • Risk assessment for communities and critical infrastructure
  • Multi-hazard analysis and planning

Agricultural Applications

  • Crop planning and optimization
  • Soil analysis and land suitability assessment
  • Farm credit assessment and land valuation
  • Agricultural sustainability evaluation
  • Food system resilience analysis

Environmental Policy

  • Agricultural sustainability metrics and assessment
  • Soil conservation practice evaluation
  • Farm labor impact assessment
  • Environmental regulation development and enforcement
  • Climate adaptation planning

Organizational Structure

Lead Organization

  • University of California, Santa Barbara - Center for Spatial Studies, Department of Geography

Partner Institutions

  • Kansas State University (agricultural data expertise)
  • Michigan State University (soil and agricultural systems)
  • Arizona State University (supply chain and optimization)
  • University of Southern California (environmental systems)
  • University of Bristol (knowledge graph and semantic web)

Industry and Government Partners

  • Esri - Geographic Information Systems technology
  • Oliver Wyman - Commodity markets and supply chain expertise
  • Hydronos Labs - Weather, climate, and agriculture information
  • U.S. Geological Survey (USGS) - Geospatial data expertise
  • Natural Resources Conservation Service (NRCS) - Agricultural and environmental data
  • Direct Relief - Humanitarian aid operational experience

Funding and Support

  • Funder: National Science Foundation (NSF)
  • Program: Convergence Accelerated Program
  • Grant: OIA-2033521
  • Duration: Multi-year support for infrastructure and research

Citation and Usage

KnowWhereGraph data and services are freely available under the Creative Commons Attribution 4.0 (CC BY 4.0) license. Users are encouraged to cite appropriate KnowWhereGraph publications when using data or services in research and applications.

The knowledge graph is maintained and operated by the Center for Spatial Studies at University of California, Santa Barbara in collaboration with partner institutions and supported by the National Science Foundation.

Automated Evaluation

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Created: December 17, 2025 | Last modified: May 30, 2026