The enRichMyData partners convened at the Philips offices in Eindhoven, the Netherlands, for an engaging plenary meeting. The focus of the gathering was to test the advanced tools and services developed within the project and to chart the course for upcoming activities, including plans for the exploitation of the enRichMyData toolbox. With just eight months

The 23rd International Semantic Web Conference (ISWC) once again highlighted its role as the premier global venue for advancing semantic web and knowledge graph technologies. These innovations, essential for fostering interoperability and streamlining data enrichment, are closely aligned with the mission of the enRichMyData project. Naturally, our teams played a prominent role in this year’s

The enRichMyData Toolbox Version 2 is designed to handle even the most complex data enrichment scenarios. Useful for data scientists or engineers, this open-source toolbox provides everything needed to design, execute, and optimize data enrichment pipelines with ease. The toolbox brings together a collection of interoperable tools and services that can be seamlessly combined and

enRichMyData was part of the BDVAF’s session “Leveraging Technologies for Data Management to Implement Data Spaces”. This session set the foundation for a new collaboration with innovative projects like WATERVERSE EU, GREEN.DAT.AI, SEDIMARK, DataBri-X, and STELAR. Iroshani Jayawardene, a Research Scientist from SINTEF, delivered a talk on  “Finding Data in Data Spaces – Entity Linking for

enRichMyData participated in the BDVAF’s session “Advancing Data Lifecycle Management: Tools and Strategies for Enhanced Monetisation” as part of the EUDATA+ cluster. This was an excellent  opportunity to present how the project developed toolbox applies to our use cases and a wonderful occasion to map possible synergies with the other projects in the cluster (FAME,

During the 3-day BDVA forum in Budapest, enRichMyData organised a productive session on Generative AI for Data and Knowledge Engineering, sponsored by Dynabic-eu, HUMAINE and INTEND project. The speakers explored the complexity, transparency, fairness, and accountability of adopting generative AI in data and knowledge engineering. They also highlighted some engineering challenges that arise when moving from