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Revolutionising Data Access with SPARQL Endpoint and Virtual Knowledge Graph

In 2019, Open Data Hub and Ontopic embarked on an ambitious project to develop a Virtual Knowledge Graph that would leverage real-world data. The goal was to provide seamless access to real-time mobility and tourism data through a SPARQL endpoint.

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In 2020, the first version of the SPARQL endpoint was unveiled. This groundbreaking tool exposed the data from the two primary Open Data Hub Data Spaces, catering to both the mobility and tourism domains. The SPARQL endpoint became the go-to resource for querying and accessing valuable information.


In acknowledgment of the significance of user experience, Ontopic introduced a user-friendly version of the SPARQL endpoint in 2021. This intuitive interface was designed to facilitate data consumption and the creation of precise SPARQL queries, simplifying the process and empowering users to leverage the SPARQL endpoint’s capabilities more effectively. The testing phase has concluded for now. However, it can be reopened in response to genuine and specific needs.

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As 2022 drew to a close, Ontopic took a significant step forward by officially publishing a testing version of the SPARQL endpoint. This version was powered by real data sourced from the Open Data Hub, ensuring its reliability and accuracy. With this milestone, Ontopic solidified its commitment to delivering a robust and dependable resource for data consumption.

Whether you’re a data enthusiast, developer, or domain expert, if you have a real use case and wish to explore the power of knowledge graphs and semantics in the Open Data Hub, please don’t hesitate to contact us. While the current testing phase has concluded, we are ready to reopen it in response to genuine and specific needs.

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The Open Data Hub Virtual Knowledge Graph was a great opportunity to show how data can be integrated into a highly usable source of precise information and knowledge. The solutions developed also thanks to this project allow now the fast and inexpensive creation of semantic layers, which can be used from a large variety of applications, such as PowerBI, Tableau, Metabase, Excel, Pandas and many more, in addition to the native RDF-oriented solutions.

Peter Hopfgartner