Froilan Sia·1d agoProtégé vs. GraphDB vs. Neo4j: Choosing Your Ontology ToolingThree tools, three purposes. How to design, store, and query enterprise knowledge at scale — and where each one actually belongs.A response icon2A response icon2
Volodymyr Pavlyshyn·Nov 3Two Ways to Reason Over RDF: Datalog in RDFox vs. oxiliteWhy Datalog over RDF
Volodymyr Pavlyshyn·Oct 30Certified answers for knowledge graphsLeanRDF puts RDF entailment in Lean 4: Elpi searches, a verified checker decides, and every “yes” comes with a theorem.
Sixing Huang·Oct 25Building a Governed Diabetes Prescription Knowledge Graph in RDFA Medicare-based graph that explains itself, checks its own quality and speaks three languages
DhanushKumar·Oct 22Ontology in AI: The Semantic Layer That Turns Data into Reliable IntelligenceModern AI can generate fluent answers from unstructured text, but fluency is not the same as understanding. A model may recognise the words…
ER/Studio·Oct 9Your AI Doesn’t Just Need More Data. It Needs to Know What the Data Means.Imagine giving an AI assistant access to every database in your organization.
Vishwa Teja Vangari·Oct 4How much semantic modeling do your AI agents need?You are arranging a meeting. Six people will attend in the office, and two will join online. You give a personal assistant the invitation…
Volodymyr Pavlyshyn·Sep 27Graphs that describe graphs: schema management that travels with your dataEvery triple store can hold an ontology. Very few can tell you which ontology is meant for which data, and none of the big ones keep that…
