Contents
In this tutorial, we will start by exploring why structured terminology work is more important than ever in the era of AI. We will look at a range of use cases and applications of terminology across different workflows and environments—showing concretely what you can achieve with a solid terminology database: performing quality checks in CAT tools or authoring systems, supporting AI agents, serving as a knowledge base for PIM systems, and much more.
We will then move to the core of the tutorial: how to get started. Rather than focusing on theory or comparing terminology approaches, we will take a practical, hands-on perspective. Drawing on our experience at MED‑EL, I will walk you through the steps involved: which tools and resources you need, how to define the structure and metadata of your database, how to organize your work efficiently, and how to set realistic goals and timelines.
We will also have time to discuss your specific needs and explore how the steps presented in the tutorial can be adapted to your own context.