Google popularized the term "knowledge graph" in this 2012 blog post. Since then, there has been a massive momentum around ...

I will be using the W3C graph standards RDF, OWL and SPARQL in my example. Show Me the Data Catalog Ontology. A data catalog ontology provides the concepts and relationships of how metadata resources ...

For example, a user might input a question like “Which policies have a high-risk rating?” and the LLM can generate a Cypher query to extract the relevant data from the graph. The knowledge ...

But, the killer application of graph is rapid large-scale data integration. Here’s a proven process for realizing the promise of the graph data model, specifically using W3C, RDF and OWL. Zippy Data ...

According to Gartner’s Top 10 Data and Analytics Trends for 2021, knowledge graphs are the foundation of modern data and analytics, with capabilities to enhance and improve user collaboration ...

Knowledge graphs are a valuable tool that organizations can use to manage the vast amounts of data they collect, store, and analyze. At Data Summit 2023, Joseph Hilger, COO, Enterprise Knowledge LLC ...

The feature engineering is a key element as well. There are also many industry-standard data models, which support RDF and the graph model. For example, Fibo for financial services, HL7 FHIR for ...

Connecting And Leveraging Data. Knowledge graph technology is transforming the way that organizations manage and make sense of data: A Unified View: By integrating data from multiple sources ...

Knowledge graphs: The link between data and meaning While Google popularized the term “knowledge graph” in 2012, the concept of representing knowledge as interconnected information has roots ...