GraphNews

RDF file extension for DuckDB. Reads and writes supported - nonodename/duck_rdf

I came across a solution that changes how Claude Code handles large codebases.

Large Language Models (LLMs) demonstrate strong reasoning abilities but face limitations such as hallucinations and outdated knowledge. Knowledge Graph (KG)-based Retrieval-Augmented Generation...

Why Hypergraphs? Most graph databases and modeling tools are built on simple graphs — nodes connected by edges, where each edge links exactly two nodes.

Mariam Barry, Gaetan Caillaut, Pierre Halftermeyer, Raheel Qader, Mehdi Mouayad, Fabrice Le Deit, Dimitri Cariolaro, Joseph Gesnouin. Proceedings of the Workshop on Generative AI and Knowledge Graphs (GenAIK). 2025.

How Reliable RAG Systems Separate Finding from Deciding

I couldn’t help myself. After reading Kurt Cagle's recent post comparing RDF 1.2 to Neo4j, I ended up going down the rabbit hole last night. The RDF vs. LPG debate has shaped the graph community for years, but it may be pointing at the wrong distinction. This short article explores an alternative; treating RDF as a hypergraph composed of interconnected named graphs, where observations, classifications, projections, constraints, and provenance all coexist as part of a single system. In this view, LPG-style structures are not competing models. They are projections within the same framework, tailored for specific analytical needs. By separating assertion from interpretation and embedding data contracts directly into the graph using SHACL, we can focus less on formats and more on how to manage and compose graph-based knowledge in a consistent way. I'm looking forward to exploring some code-forward examples in the next few weeks, and folding in the evolving SHACL 1.2 spec.

Everyone is talking about “context graphs” and AI, but we need to be clear about what they are and what they aren’t. Eilon Reshef breaks it down in his new blog.

This illustrates the boundary of the Semantic Web stack.

Explore top LinkedIn career content from experienced professionals.

Explore top LinkedIn content from members on a range of professional topics.

How a fifty-year-old idea from biology is reshaping the way we think about knowledge graphs

This is update from previous blog (version 1): GraphRAG and PostgreSQL integration in docker with Cypher query and AI agents | Microsoft Community...

  Why should I care?   ⚡️In under 15 minutes, you’ll have a Cypher-powered, semantically rich knowledge graph you can query...

A Comparative Architecture Analysis

Context graphs are a hot new conversation these days. And yet I feel like I’ve seen this story before.

A package to scan Cypher queries before you port them between different graph databases. At the time of writing, the package measures compliance against the openCypher 9 specification across four graph database vendors:

White Paper: "Semantic Foundations for AI-Ready Data: Why Governed Semantics, Open Standards, and Data Products Are the Prerequisites for Enterprise AI.," Synthesized with Claude Opus 4.6 (with guardrails) from Gartner D&A Summit 2026 proceedings, Gartner research publications, and industry analysis.

Retrieval-Augmented Generation (RAG) systems typically treat documents as flat text, ignoring the structured metadata and linked relationships that knowledge graphs provide. In this paper, we...

🧩 What Are Modalities in Knowledge Graphs — And Why They Matter

🧠 This one's flying under the radar and it shouldn't be.

Kinetica-Graph Explorer is now available.

Competency Questions for System Architectures

The shift from "finding data" to "reasoning and understanding context" is the driver for a more robust context layer that needs to provide the operational nuances that are typically locked within systems, teams, and organizational silos.