This blog is a preview of our session at Sirus Connects on October 9, 2026, where we map out the Linked Data landscape for beginners: what to learn first, which tools are worth your time, and what you can safely ignore.
Speaker:
At first glance, Linked Data is intimidating. On second glance, it's actually quite wholesome and fun to explore.
Something as “intimidating” as Linked Data can actually become surprisingly wholesome and fun — if you know where to start. First encounters with Linked Data often feel like trying to wrap your head around abstract concepts while endlessly scrolling through overly detailed specifications, or worse, lacklustre documentation.
That was exactly my experience when I started out. Today, I enjoy working in this space by building tooling for a research project at the intersection of academia and industry.
You need a map
So how do you go from walking in blindly as a complete beginner to navigating the Linked Data landscape with confidence? It’s simple: you need a map.
In my talk at Sirus Connects, I guide you through this landscape from a very practical perspective. Rather than focusing on heavy theory, we break the world of Linked Data into manageable pieces: what you need to understand to get started, what tools are worth your time, and what you can safely ignore in the beginning. Think of it as a map through a landscape that often feels more complex than it really is.
From alphabet soup to clear purpose
You will leave with a clearer mental model of how the different parts of the Linked Data ecosystem fit together, and how they were built to solve different challenges. At first glance, RDF, SPARQL, RML, and SHACL can feel like alphabet soup. But each has a clear purpose:
- RDF: The core data model of Linked Data. Information is expressed as simple triples — subject, predicate, object — forming a graph of relationships. Surprisingly powerful, because all knowledge becomes a network of connections between things.
- SPARQL: The query language for RDF, similar to SQL but designed for graph data.
- SHACL: A framework for validating RDF data, helping you check whether your data is complete and consistent.
- RML: A mapping language used to transform existing data into RDF.
- LDES: A way of publishing or consuming Linked Data as streams or feeds, making it easier to share and access distributed data sources.
- JSON-LD: A bridge format that brings Linked Data into a more familiar JSON structure.
Many entry points, no single right path
The Linked Data ecosystem is large, modular, and sometimes fragmented. What often surprises beginners is how many different entry points exist. You can work with Linked Data through JSON-LD for more familiar structures, or dive deeper into triple stores and reasoning engines if you want to explore inference and advanced querying.
There is no single “right path” – instead, the ecosystem offers multiple routes depending on your goals, background, and preferred tools.
Once you move beyond theory, you also discover a wide range of tools built in Python and TypeScript that help you manipulate, validate, and integrate RDF data in real applications.
Make it click at Sirus Connects
If you’re curious about Linked Data but unsure where to begin, this session will give you the clarity and confidence to get started.
Join me at Sirus Connects on October 9 to explore Linked Data in a way that finally makes it click.
Want to follow this live?
Join this session at Sirus Connects on October 9, 2026, from 10h35 to 11h20. Register and secure your spot.
Can’t make it? Reach out to us, we are happy to share our experience and discuss how Linked Data could work for your organisation.
