The actual differences between Ontologies and Graph databases for appropriate usage | LinkedIn
Can work on ontologies with Neo4j, including those based on OWL (Web Ontology Language). However, Neo4j alone is not an ontology reasoner.
Entity Linking and Relationship Extraction With Relik in LlamaIndex
Build a knowledge graph without an LLM for your RAG applications
Introduction to the Neo4j LLM Knowledge Graph Builder
Bridge the gap and unlock hidden potential within your unstructured data
Parquet Files, ready for Humans and AI | LinkedIn
Apache Parquet is an important part of the mainstream data stack. It provides a space-efficient, widely-supported way to exchange tabular data that can be used directly by various query engines.
LLM Knowledge Graph Builder — First Release of 2025
New features include community summaries, local and global retrievers, running retrievers in parallel, and custom prompt instructions.
key ontology standards
What are the key ontology standards you should have in mind?
Ontology standards are crucial for knowledge representation and reasoning in AI and data… | 32 comments on LinkedIn
key ontology standards
Should you be using GraphRAG?
When (not) to use GraphRAG
Vector Similarity Search in Graph Databases: Combining Graph Structure with Embeddings
Imagine you’re solving a complex puzzle with scattered pieces of information.
Graph Databases after 15 Years – Where Are They Headed?
Speaker: Gábor Szárnyas (LDBC)Event: Data Analytics developer room at FOSDEM 2025Talk page: https://fosdem.org/2025/schedule/track/analytics/Slides: https://...
Spanner Graph is now GA | Google Cloud Blog
Spanner Graph, now GA, includes a notebook experience, query feature and performance improvements and integrations with first- and third-party tools.
The Top 10 Considerations for Knowledge Graph Visualization and Analytics
Kùzu, version 0.8.0 with WASM
We're very happy to announce our latest release of Kùzu, version 0.8.0, is now available and ready to use! This release brings an exciting new feature that…
Kùzu, version 0.8.0
Nakala : from an RDF dataset to a query UI in minutes - SHACL automated generation and Sparnatural - Sparna Blog
Here is a usecase of an automated version of Sparnatural submitted as an example for Veronika Heimsbakk’s SHACL for the Practitioner upcoming book about the Shapes Constraint Language (SHACL). “ The Sparnatural knowledge graph explorer leverages SHACL specifications to drive a user interface (UI) that allows end users to easily discover the content of an RDF graph. What…
Introduction to the Neo4j LLM Knowledge Graph Builder
Explore its functionality and how it leverages the power of LLMs and Neo4j graph databases to improve data analysis and knowledge discovery.
Ontology is not only about data
Ontology is not only about data! Many people think that ontologies are only about data (information). But an information model provides only one perspective… | 85 comments on LinkedIn
Ontology is not only about data
Enterprise Ontology: A Human-Centric Approach to Understanding the Essence of Organisation : Dietz, Jan L. G., Mulder, Hans B. F.: Amazon.nl: Boeken
Enterprise Ontology: A Human-Centric Approach to Understanding the Essence of Organisation : Dietz, Jan L. G., Mulder, Hans B. F.: Amazon.nl: Boeken
Enterprise Ontology
Graphs to Graph Neural Networks: From Fundamentals to Applications — Part 2c: RDF vs.
Knowledge graphs are rapidly gaining traction as a way to store and query complex, interlinked data. Two major approaches dominate this…
Chatting with your knowledge graph
Enabling an LLM to chat directly with structured graph data
RAG Is The First Step, Not the Last
Why AI+Data Architecture Will Transform in 2025
RAG Is The First Step, Not the Last
A comparison between ChatGPT and DeepSeek capabilities writing a valid Cypher query
Today, I conducted a comparison between ChatGPT and DeepSeek chat capabilities by providing them with a schema and a natural language question. I tasked them…
a comparison between ChatGPT and DeepSeek chat capabilities by providing them with a schema and a natural language question. I tasked them with writing a valid Cypher query to answer the question.
Multimodal Graph RAG (mmGraphRAG): Incorporating Vision in Search and Analytics - Enterprise Knowledge
David Hughes presented “Unleashing the Power of Multimodal GraphRAG: Integrating Image Features for Deeper Insights” at Data Day Texas 2025.
Terminology Augmented Generation
Terminology Augmented Generation (TAG)? Recently some fellow terminologists have proposed the new term "Terminology-Augmented Generation (TAG)" to refer to… | 29 comments on LinkedIn
Terminology Augmented Generation
G.V() 3.14.38 Release Notes: Now with Support for Neo4j, Memgraph, Neptune Analytics, Query Editor Improvements, and more!
G.V() 3.14.38 Release Notes: Now with Support for Neo4j, Memgraph, Neptune Analytics, Query Editor Improvements, and more! For the first time ever, G.V() can be used on non Apache TinkerPop graph databases. It is now compatible with Neo4j, Neo4j AuraDB, Memgraph and Amazon Neptune Analytics using the Cypher querying language.
The GQL Standard is Published! Now What? | LinkedIn
Keith W. Hare, Convenor, ISO/IEC JTC1 SC32 WG3 Database Languages The GQL standard (ISO/IEC 39075:2024 Information technology — Database languages — GQL) was published in April, 2024.
Neo4j in 2024: Delivering on Our Vision of Cloud-First Graph Technology - Graph Database & Analytics
Discover Neo4j's 2024 product innovations in cloud-native graph technology, enhancing performance, scalability, AI innovation, and developer productivity.
What is really Graph RAG?
What is really Graph RAG? Inspired by "From Local to Global: A Graph RAG Approach to Query-Focused Summarization" paper from Microsoft! How do you combine… | 12 comments on LinkedIn
What is really Graph RAG?
A zero-hallucination AI chatbot that answered over 10000 questions of students at the University of Chicago using GraphRAG
UChicago Genie is now open source! How we built a zero-hallucination AI chatbot that answered over 10000 questions of students at the University of… | 25 comments on LinkedIn
a zero-hallucination AI chatbot that answered over 10000 questions of students at the University of Chicago
Knowledge graph modeling: what we put in OWL, what we put in SHACL, and what our rule of thumb is to decide
A few weeks ago, Thomas Francart asked me what we put in OWL, what we put in SHACL, and what our rule of thumb is to decide. I wrote this post to answer these…
what we put in OWL, what we put in SHACL, and what our rule of thumb is to decide
Exploring OWL Ontologies Visually: A Paradigm Shift in Understanding 🌐 | LinkedIn
Author: Nicolas Figay Status: DraftAuthor: Nicolas Figay Status: Draft Last update: 2025-01-14 This article was initiated due to the success of the following post A post being not enough for addressing the topic, here is the article developing the subject deeper. Introduction When diving into the wo
GraphRAG interview — Alonso
As technology advances, large language models (LLMs) and information retrieval/management methods evolve at breakneck speed. Knowledge…