About

I am an engineer working on data and AI, with the goal of solving real business problems.

I always start with what we really want to achieve, only then do I look for a technical solution.

This blog is about that, connecting business and IT from the data and AI angle.

What I work on #

I am an engineer at Schuberg Philis, where I started our current data and AI practice. I design the models and build the systems that run on them. Most of my current work sits in the knowledge layer: RDF ontologies, knowledge graphs and semantic models that encode what business terms mean, so generative AI can answer questions against enterprise data and stay traceable and auditable. Combining deterministic domain logic with generative models is called neuro-symbolic AI, which is the subject of most of what I write here.

Before that I spent about a decade on the data underneath. I designed ISA-88 and ISA-95 models for an industrial IoT platform covering 98 plants, 4,000+ machines and 90 billion data points, and built the real-time event processing for it in Go. I led an Azure data platform in a regulated financial environment, with automated lineage and auditability. I modeled GraphQL schemas to connect a parcel logistics chain, built Data Vault 2.0 architectures for national KPI reporting, and put a data quality framework in place with the data stewards who had to work with it.

I keep working on the knowledge layer and the data platform under it, because an ontology is only useful when the data below it is governed, the lineage is traceable and the quality is known. Working with data for years, I have come to expect answers you can trace back to a source. I also believe AI will change how businesses operate, but only if it can be trusted, and that means being able to check its output against the data it came from. A knowledge layer is what makes that check possible.

Background #

• MSc Information Studies, University of Amsterdam
• BSc Bedrijfskunde (Business Administration), University of Groningen
• Based in Amsterdam

I studied business administration before information systems, and how organizations work interests me as much as the technology does. Modeling an organization’s data is a direct way to see what it is really trying to do, and a practical place to start changing it.

If any of what I write is useful (or wrong), I’d like to hear it. My links are below.

I work at Schuberg Philis. Everything here is my own opinion and does not represent my employer.