Building an End-to-End Linked Data Engineering Project
Last Updated on July 25, 2023 by Editorial Team
Author(s): Edoardo Bianchi
Originally published on Towards AI.
Data Modeling and Analysis using Semantic Web Technologies

This member-only story is on us. Upgrade to access all of Medium.
The first section of the final application. Image by the author.
Applications are generally limited by the data they have access to. Data retrieved comes from defined sources, generally designed for the application itself. That’s fine, but imagine an app that can access a more global database, different sources connected together, forming a big, comprehensive, machine-readable data source.
This is linked data. This is the Semantic Web.
In this article, I present an end-to-end project that demonstrates (1) how relational data can be transformed into linked data, ready to be integrated, (2)… Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Towards AI Academy
We Build Enterprise-Grade AI. We'll Teach You to Master It Too.
15 engineers. 100,000+ students. Towards AI Academy teaches what actually survives production.
Start free — no commitment:
→ 6-Day Agentic AI Engineering Email Guide — one practical lesson per day
→ Agents Architecture Cheatsheet — 3 years of architecture decisions in 6 pages
Our courses:
→ AI Engineering Certification — 90+ lessons from project selection to deployed product. The most comprehensive practical LLM course out there.
→ Agent Engineering Course — Hands on with production agent architectures, memory, routing, and eval frameworks — built from real enterprise engagements.
→ AI for Work — Understand, evaluate, and apply AI for complex work tasks.
Note: Article content contains the views of the contributing authors and not Towards AI.