Jesper Kuiper (TNO)

At Semantic Treehouse, we're all about shaping ideas about data and its meaning into explicit and explainable message models. These message models are the bedrock on which to build powerful and unambiguous software ecosystems, like the European Union's envisioned Digital Product Passport system!

In a previous blogpost by my colleague Wouter (ENDORSE '25, BOMOS), he talked about our vision of using Generative AI for semantic interoperability. The core idea he conveyed there, and which I will also highlight here again, is that semantic interoperability at its core is not a technical problem. It's a problem of – a lack of – human coordination. Keeping this in mind, we have asked ourselves the question: How can AI help advance or accelerate the systematic BOMOS approach to standardization? In this blog post, I'm happy to show to you the first part of our STH Co-pilot roadmap: AI-assisted message model creation!

AI-assisted message model generation​

When creating a message model from the ground up, it's sometimes hard to just get started. That's where the AI-assisted generation feature can help. It can provide initial suggestions for message model elements, helping to kickstart the development process. You only provide a description for the message model you'd like:

Now the AI will generate a message model based on your description. The generated message model will be displayed in the editor, allowing you to review and refine it further:

Now of course this message model will not be perfect – far from it. In fact, it's likely to contain errors and omissions, but it's a starting point that can be refined and improved upon. Semantic Treehouse already has many great collaboration features, such as issues, comments, and support for iterative versioning.

Looking ahead​

Semantic Treehouse's AI-assisted message model generation feature is just one example of how AI can enhance standardization, collaboration, and productivity. As we continue to explore the possibilities of AI in software development, we'll be sharing more insights and best practices. Stay tuned for more updates on this exciting topic! In the meantime, if you'd like to become involved, you can join our Discord server and discuss your vision with our team. On our Gitlab page, you can follow the technical developments more closely as well.

The call for a more transparent and sustainable economy is loud and clear. We want to know where products come from, what they are made of, and how we can responsibly reuse them. Digital Product Passports (DPPs) are essential for this: they give each product its own passport detailing its lifecycle. The European Union is strongly committed to DPPs to encourage more sustainable choices. However, practical implementation is challenging and complex. Products travel the globe, through supply chains with numerous actors and diverse IT systems. How do we ensure that the data in a DPP in Spain is as usable and understandable as it is in the Netherlands or Vietnam? We need a "common language", a standard that ensures everyone interprets the same information in the same way. Without such a language, a DPP is like a product instruction manual in a language you don't speak. You see the words, but the instructions are lost on you.

The need for practical implementations of DPPs is precisely what we are addressing within our work, and we are addressing it from multiple perspectives. For instance, we have established a DPP Semantic Treehouse environment – https://dpp.vocabulary-hub.eu/ – which serves as the hub where the 'common language' for all product types can be hosted, managed, and shared. Beyond this environment, we are actively engaged in various projects, developing features to simplify the process of creating DPPs. But how does that work? Let's dive into it!