Bridging different data ecosystems
Today, data is distributed across many independent systems. At the same time, AI applications increasingly rely on combining such information.
Some systems structure data as knowledge graphs, while others use standard web APIs. Bridging these approaches has been a long-standing challenge.
The solution, called HeFQUIN, enables these data types to be integrated and queried together in real time.
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Flexible and efficient solution
HeFQUIN retrieves, translates and combines data on the fly, without the need to store it in advance in a central database. This enables more agile and lightweight AI applications.The software is available as open source and can be used in both research and industry.
Facts
Conference: European Semantic Web Conference (ESWC), DubrovnikAward: Best Demo Paper Award
Project: HeFQUIN
Collaboration: Scania
The research was funded by the Knut and Alice Wallenberg Foundation and the Swedish Research Council.