| Knowledge Graph Insights | https://knowledgegraphinsights.com/ |
| LarrySwanson.com | https://www.larryswanson.com/ |
| https://www.linkedin.com/in/larryswanson/ |
Even as #RDF has become ubiquitous in enterprises and across the web, its awkward handling of #reification — the ability to refer to other statements in a graph — has limited its wider adoption.
@ora and Adrian Gschwend lead the W3C working group that is tackling this problem. RDF 1.2 introduces the reifier, which lets you annotate individual graph relationships with provenance, confidence, and source.
Long before Foundation Capital published their "trillion dollar opportunity" article about #contextGraphs, Daniel Davis had been building a platform for them.
Daniel's work in complex domains like aircraft safety and autonomous vehicles, as well as his study of quantum mechanics, gave him insights that led him to explore ways to ground probabilistic AI systems in logic and knowledge, settling on context graphs as the best way to do it.
As interest in knowledge graphs grows by the day, @veronahe is busier than ever with her efforts to connect the #dataEngineering, #informationArchitecture, and #ontology practices that drive modern knowledge engineering.
Best known as an advanced #knowledgeGraph practitioner and a leading expert on the #SHACL standard, Veronika also regularly shares her knowledge by teaching and appearing on podcasts like this one.
When Gartner declared 2026 "The Year of Context," @joereis leapt into action, immediately writing a good-natured satirical article about "context products," "context lakes," and the "analyst singularity."
No one is better than Joe at dismantling tech industry hype. This was a fun and instructive conversation. Hope you enjoy it, too.
Few people have advanced the craft and management of #contentDesign as much as Melanie Seibert. She's been designing content experiences and managing design teams decades. She shares some of her best insights in her new book, "Managing Content Design Teams."
Melanie was one of my earliest guests on this pod. It was great to reconnect and hear her freshest insights. I hope you enjoy the conversation as much as we did.
Yale University manages huge collections of precious #culturalHeritage artifacts housed in multiple museums, libraries, and other collections.
Using #knowledgeGraph and #ontology engineering design patterns that he has developed over his career, Robert Sanderson helps scholars, researchers, and the general public access information about — and make connections across — millions of unique items in Yale's collections
I enjoyed @sboots’s essay on becoming a “generative AI vegetarian”, and for a few reasons: it’s a great read, first and foremost, but also my GOODNESS is this well-sourced. Sean pulls together many, many threads here; always grateful for a map like this.
The promise of #agenticAI is being realized in systems like the Service Copilot that Zeiss microscopes provides for its field service engineers, integrating technical documentation, subject matter expertise, and user-generated insights, all orchestrated and shared with a suite of AI agents.
While it relies heavily on modern LLM technology, Max Gärber says it's the system's solid #knowledgeGraph and metadata foundation that make it a success.
The complementary nature of #knowledgeGraphs and #LLMs has become clear and long-time knowledge engineering professionals like Quentin Reul now routinely combine them in hybrid #neurosymbolicAI systems.
While it's tempting to get caught up in the details of rapidly advancing AI technology, Quentin emphasizes the importance of always staying focused on the business problems your systems solve.
An instructive conversation. Hope you enjoy it too.
Ethan Marcotte