Knowledge Graph Insights

Ben Rode As the Cyc project winds down, one of its main contributors, Benjamin Rode, is attempting to migrate as much as possible of its upper ontology to RDF. It's an ambitious project, much like Cyc itself. Cyc arose from the early AI research community, and Ben has a fascinating perspective on that milieu as well. We talked about: his work to port as much as possible of the Cyc upper ontology i...

Lulit Tesfaye Generative AI has prompted a flurry of experimentation in enterprises, resulting in a parade of failed pilots, unproven PoCs, and unrealized return on investment. Lulit Tesfaye helps companies improve and optimize their AI capabilities by adding semantics to their enterprise architectures. This puts their precious knowledge assets in a context that machines can actually work with. A...

Giancarlo Guizzardi For nearly three decades, Giancarlo Guizzardi has researched and advanced the field of semantics and the practice of ontology and conceptual modeling. His work on the Unified Foundational Ontology (UFO), the OntoUML pattern language, and AI explainability are just a few of the accomplishments that make him an exemplar of the "full-stack ontologist." We talked about: his broad-r...

Ora Lassila and Adrian Gschwend 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. RDF 1.2 addresses this with the reifier: a new element that lets you attach provenance, confidence, and source directly to a relationship — including claims you're tracking bu...

Daniel Davis Long before Foundation Capital published their "trillion dollar opportunity" article about them, Daniel Davis had been building a platform for context graphs. 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 the logic and knowled...

Veronika Heimsbakk With interest in knowledge graphs growing by the day, Veronika Heimsbakk is busier than ever with her efforts to connect the data engineering, information architecture, and ontology practices that drive modern knowledge engineering. Best known as an advanced knowledge graph practitioner and a leading expert on the SHACL standard, Veronika also regularly shares her knowledge thro...

Joe Reis When Gartner declared 2026 "The Year of Context," Joe Reis leapt into action, immediately writing a good-natured satirical article about "context products," "context lakes," and the "analyst singularity." It's a fun article that exemplifies Joe's no-nonsense approach to industry education and concludes with a serious point — "context does matter, and most organizations are terrible at it....

Robert Sanderson Yale University manages huge collections of precious cultural heritage artifacts housed in multiple museums, libraries, and other collections. Using knowledge graph 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...

Max Gärber The promise of agentic AI is being realized in systems like the Service Copilot that Zeiss microscopes provides for its field service engineers. The system integrates technical documentation, subject matter expertise, and user-generated insights which are orchestrated and shared with a suite of AI agents. While it relies heavily on modern LLM technology, it's the system's solid knowledg...

Quentin Reul The complementary nature of knowledge graphs and LLMs has become clear, and long-time knowledge engineering professionals like Quentin Reul now routinely combine them in hybrid neuro-symbolic AI 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 syste...

Jim Hendler As the World Wide Web emerged in the late 1990s, AI experts like Jim Hendler spotted an opportunity to imbue in the new medium, in a scale-able way, knowledge about the information on the web along with its simple representation as content. With his colleagues Tim Berners-Lee, the inventor of the web, and Ora Lasilla, an early expert on AI agents, Jim set out their vision in the famous...

Brad Bolliger Brad Bolliger entered the knowledge graph space via enterprise software system design and data analytics. That background informs their pragmatic and strategic approach to the use of semantic technology in systems that facilitate information exchange across government agencies. We talked about: their work at EY (Ernst & Young) on data and analytics strategy assessments and enterprise...

Tara Raafat At Bloomberg, Tara Raafat applies her extensive ontology, knowledge graph, and management expertise to create a solid semantic and technical foundation for the enterprise's mission-critical data, information, and knowledge. One of the keys to the success of her knowledge graph projects is her focus on people. She of course employs the best semantic practices and embraces the latest tec...

Alexandre Bertails At Netflix, Alexandre Bertails and his team have adopted the RDF standard to capture the meaning in their content in a consistent way and generate consistent representations of it for a variety of internal customers. The keys to their system are a Unified Data Architecture (UDA) and a domain modeling language, Upper, that let them quickly and efficiently share complex data proje...

Torrey Podmajersky Torrey Podmajersky is uniquely well-prepared to help digital teams align on language and meaning. Her father's interest in philosophy led her to an early intellectual journey into semantics, and her work as a UX writer at companies like Google and Microsoft has attuned her to the need to discover and convey precise meaning in complex digital experiences. This helps her span the...

Casey Hart Ontology engineering has its roots in the idea of ontology as defined by classical philosophers. Casey Hart sees many other connections between professional ontology practice and the academic discipline of philosophy and shows how concepts like epistemology, metaphysics, and rhetoric are relevant to both knowledge graphs and AI technology in general. We talked about: his work as a lead...

Chris Mungall Capturing knowledge in the life sciences is a huge undertaking. The scope of the field extends from the atomic level up to planetary-scale ecosystems, and a wide variety of disciplines collaborate on the research. Chris Mungall and his colleagues at the Berkeley Lab tackle this knowledge-management challenge with well-honed collaborative methods and AI-augmented computational tooling...

Emeka Okoye Semantic technologies permit powerful connections across a variety of linked data resources across the web. Until recently, developers had to learn the RDF language to discover and use these resources. Leveraging the new Model Context Protocol (MCP) and LLM-powered natural-language interfaces, Emeka Okoye has created the RDF Explorer, an MCP service that lets any developer surf the sem...

Tom Plasterer Shortly after the semantic web was introduced, the demand for discoverable and shareable data arose in both research and industry. Tom Plasterer was instrumental in the early conception and creation of the FAIR data principle, the idea that data should be findable, accessible, interoperable, and reusable. From its origins in the semantic web community, scientific research, and the ph...

Mara Inglezakis Owens Mara Inglezakis Owens brings a human-centered focus to her work as an enterprise architect at a major US airline. Drawing on her background in the humanities and her pragmatic approach to business, she has developed a practice that embodies both "digital anthropology" and product thinking. The result is a knowledge architecture that works for its users and consistently demons...

Frank van Harmelen Much of the conversation around AI architectures lately is about neuro-symbolic systems that combine neural-network learning tech like LLMs and symbolic AI like knowledge graphs. Frank van Harmelen's research has followed this path, but he puts all of his AI research in the larger context of how these technical systems can best support people. While some in the AI world seek to...

Denny Vrandečić As the founder of Wikidata, Denny Vrandečić has thought a lot about how to better connect the world's knowledge. His current project is Abstract Wikipedia, an initiative that aims to let anyone anywhere on the planet contribute to, and benefit from, the world's collective knowledge, in their native language. It's an ambitious goal, but - inspired by the success of other contribut...

Charles Ivie Since the semantic web was introduced almost 25 years ago, many have dismissed it as a failure. Charles Ivie shows that the RDF standard and the knowledge-representation technology built on it have actually been quite successful. More than half of the world's web pages now share semantic annotations and the widespread adoption of knowledge graphs in enterprises and media companies is...

Andrea Gioia In recent years, data products have emerged as a solution to the enterprise problem of siloed data and knowledge. Andrea Gioia helps his clients build composable, reusable data products so they can capitalize on the value in their data assets. Built around collaboratively developed ontologies, these data products evolve into something that might also be called a knowledge product. We...

Dave McComb During the course of his 25-year consulting career, Dave McComb has discovered both a foundational problem in enterprise architectures and the solution to it. The problem lies in application-focused software engineering that results in an inefficient explosion of redundant solutions that draw on overlapping data sources. The solution that Dave has introduced is a data-centric architect...