Knowledge networks
Active
By Center of Excellence for Geospatial Information Science (CEGIS)
January 23, 2025
Knowledge networks
part of the Knowledge graphs theme from CEGIS
part of the Knowledge graphs theme from CEGIS
Knowledge graphs are networks of data, patterns, and rules that represent the relationships between real-world entities and can respond to queries.
An open knowledge network is information infrastructure for use cases connected by data fabric.
Publications
Publications
You will find here a sampling of publications. More are available and are being published throughout the year.
Check back often or view our custom search for more!
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Open knowledge network roadmap: Powering the next data revolution
Open access to shared information is essential for the development and evolution of artificial intelligence (AI) and AI-powered solutions needed to address the complex challenges facing the nation and the world. The Open Knowledge Network (OKN), an interconnected network of knowledge graphs, would provide an essential public-data infrastructure for enabling an AI-driven future. It would...A geospatial knowledge graph prototype for national topographic mapping
Knowledge graphs are a form of database representation and handling that show the potential to better meet the challenges of data interoperability, semi-automated information reasoning, and information retrieval. Geospatial knowledge graphs (GKG) have at their core specialized forms of applied ontology that provide coherent spatial context to a domain of information including non-spatial...GeoAI and the future of spatial analytics
This chapter discusses the challenges of traditional spatial analytical methods in their limited capacity to handle big and messy data, as well as mining unknown or latent patterns. It then introduces a new form of spatial analytics—geospatial artificial intelligence (GeoAI)—and describes the advantages of this new strategy in big data analytics and data-driven discovery. Finally, a...GeoAI in the US Geological Survey for topographic mapping
Geospatial artificial intelligence (GeoAI) can be defined broadly as the application of artificial intelligence methods and techniques to geospatial data, processes, models, and applications. The application of these methods to topographic data and phenomena is a focus of research in the US Geological Survey (USGS). Specifically, the USGS has researched and developed applications in...Creating annotations for web ontology language ontology generated from relational databases
Many approaches that have been proposed that allow users to create a Web Ontology Language (OWL) ontology from a relational database fail to include metadata that are inherent to the database tables. Without metadata, the resulting ontology lacks annotation properties. These properties are key when performing ontology alignment. This paper proposes a method to include relevant metadata...
CEGIS science themes
CEGIS science themes
Theme topics home
Theme topics home
Knowledge graphs
Knowledge graphs
Knowledge networks
Knowledge networks
Query use cases
Query use cases
Semantic graphs
Semantic graphs
Semantics and data graph semantics based on The National Map
Web Ontology Language (OWL) files of data summaries, shapes, and patterns
CEGIS - Denver, Colorado
CEGIS - Denver, Colorado
CEGIS - Rolla, Missouri
CEGIS - Rolla, Missouri
CEGIS science themes
CEGIS science themes
Theme topics home
Theme topics home
Knowledge graphs
Knowledge graphs
Knowledge networks
Knowledge networks
Query use cases
Query use cases
Semantic graphs
Semantic graphs
Semantics and data graph semantics based on The National Map
Web Ontology Language (OWL) files of data summaries, shapes, and patterns
CEGIS - Denver, Colorado
CEGIS - Denver, Colorado
CEGIS - Rolla, Missouri
CEGIS - Rolla, Missouri