Semantic layers and knowledge graphs promise new ways for AI systems to work with organisational knowledge, but moving from the idea to a production architecture introduces difficult choices. Should you use a labelled property graph or a triplestore? Should data be copied into a graph or virtualised where it already lives? If multiple silos are connected, how should security work? Where should the ontology live, who owns it, and how should it be governed?

In this session, the author of The Semantic Blueprint (Packt, 2027) takes an architect’s approach to these decisions. Rather than presenting a feature matrix, you will work through a series of architecture katas that begin with a problem and its business context, then examine the available approaches and the trade-offs each one makes, including where the speaker’s preferred stack has limitations.

You will also examine ownership and governance as architecture decisions that need to be considered from the beginning rather than added later as policy. By working from context through options and trade-offs to a decision, you will develop a practical way to choose between semantic architecture approaches, reason about security when knowledge is connected, and identify the questions worth asking before deciding whether to buy or build.

What You Will Learn

• How to evaluate labelled property graphs, triplestores, data copying, and virtualisation based on their trade-offs

• How to reason about security when knowledge and data from multiple silos are connected

• Why ontology ownership and governance need to be treated as architecture decisions

• How to work from business context through architectural options and trade-offs to an appropriate decision

Who Should Attend

Enterprise Architects, Data Architects, Software Architects, AI Architects, Data Engineers, and technical leaders responsible for semantic layers, knowledge graphs, or enterprise knowledge systems.