Here's an example: one cantonal authority publishes environmental data on air quality, while another collects information on traffic volumes. Linked data joins these otherwise unrelated data sources together so that a connection can be made ‒ for example, to determine the impact of rush hour traffic on air pollution in a particular region. Understanding these relationships enables users to make evidence-based decisions, for instance when planning low-emission zones or optimizing public transport.
Linked data is therefore much more than a technical concept ‒ it is a key to digital transformation in the public sector.
Intuitive rather than complicated: The SPARQL AI Explorer from ti&m
The theory of linked data sounds convincing; in practice, however, it often fails due to its complexity. The creation of SPARQL queries in particular requires a deep understanding of ontologies, data structures and the language itself. This is exactly where ti&m's SPARQL AI Explorer comes in: with an innovative approach that combines technological excellence and user-friendliness.
From the user’s point of view, easy access is top of the list. Users don’t need any prior knowledge of SPARQL or linked data to build a query: AI-powered user guidance will lead them through the process step by step, making suggestions and allowing them to iteratively refine the query until they get the information they want. This makes linked data accessible to specialist departments, project managers and analysts who have previously shied away from its complexity.
The technical basis of the approach is an intelligent linking of ontologies, metadata and modern language models (LLMs), supplemented by a visual representation of the data structure. Users can see how the data is organized and what relationships exist, and can access the query directly via an interactive interface. This creates transparency, understanding and trust – and accelerates the wide-scale use of semantically enriched data.
The SPARQL AI Explorer is a prototype for the data-driven administration of the future, with AI as a catalyst for democratizing the public data landscape.
Open to the future: An open-source contribution to the linked data community
ti&m has published the SPARQL AI Explorer as an open-source project, not only to demonstrate what linked data can offer, but also to make it actually usable. What we want to see is more widespread use, greater community involvement and everybody working together to take development further. Developers, authorities and organizations can use, expand and integrate the Explorer into their own data landscapes just as they please – whether that’s in open government data, smart cities or digital administration.
The concept is deliberately designed to be modular and reusable: relational or non-relational databases, data lakes and data warehouses can also be developed using similar mechanisms. In the future, the approach will even enable integration with visualization tools, so that users can not only query complex data, but also read it in natural language and view the results graphically. The approach can be specifically extended to include current AI concepts such as agents and MCP servers, enabling integrated natural querying and interpretation of various data sets. This paves the way for an open, AI-supported data stack.
With the SPARQL AI Explorer, ti&m shows how artificial intelligence, semantic technologies and open source can come together to drive real innovation – and break down barriers on the way to a data-based, networked state. Let’s keep building together: a digital future where data is not only available, but actually useful.
Frontend of the SPARQL AI Explorer