Effective knowledge orchestration demands more than data aggregation; it requires semantic coherence across diverse sources.

What it is:

The Ontology Pipeline is a framework for building a semantic knowledge infrastructure, with iterative steps to guide the process. 

What it does:

Refresh over coffee. Share experiences.

Networking prompt and let’s ‘break the ice’ - connect with someone you’ve not met before! Mingle with your peers. Take time to forge a new connection in your DAM and Semantic Data community.

Exhibition - your chance to check out the live demos, to contrast and compare. Talk to those who have the solution you might need.

Foundations matter. 

Data quality is one of the most important pillars of a Semantic Architecture. Regardless of our particular projects or roles well defined semantics are only valuable if there is accurate, representative, and timely data. Unfortunately, too many organizations are unable to (or shouldn’t) trust their data enough to create the information experiences where people learn, make decisions, or connect. 

Practical guidance on the art of tagging

• How taxonomy and other metadata tags help improve AI responses 
• How to identify areas of potential AI hallucinations 
• How to increase the accuracy of AI outputs. 

Context:

Language is a tool. From our first grunts, whoops, and mutterings as Homo sapiens, we have used language to communicate - but also to persuade and control. In a world of growing complexity, uncertainty, and fractaled meaning, we still attempt to organize and find meaning through the expression of language.

Perceived meaning is often dependent on the language we use. With language we can misinform, but we can also use it to create order and stability.