SPARQL-ML - Machine Learning for SPARQL Query Optimization over Centralized and Distributed RDF Knowledge Graphs

The SPARQL-ML project develops AI and machine-learning-based generic approaches for optimized query processing over large RDF Knowledge Graphs to facilitate the development of high-performance centralized and distributed data storage solutions. The final output will be a set of W3C-standard-conformant tools that implement Optimized SPARQL query execution on top of centralized and federated RDF Knowledge Graphs.

Funding

This project receives funding from of the Eureka Eurostars programme (Project ID: 5736), which is part of the European Partnership on Innovative SMEs, in cooperation with the German Federal Ministry of Education and Research (BMBF).

Latest News

2025-09-25 - 2nd Plenary Meeting scheduled

Our 2nd Plenary Meeting will take place on 2025-11-27 in London at our partner Openlink.

2025-06-01 - LLM-TEXT2KG-Workshop - ESWC 2025 - Slovenia

eccenca organized this workshop which aims to explore the novel intersection of LLMs and KG generation, focusing on innovative approaches, best practices, and challenges.

2025-05-25 - 1st Plenary Meeting - Paderborn

During our first plenary meeting we presented the first project outputs, reviewed query plans, and agreed that the next step will be testing in a customer environment to collect query runtimes.

2024-11-13 - Kick-off Meeting

Today, we met in Leipzig to practically kick-off our project.

2024-10-21 - Funding approved

We are happy to announce that the first partners got the funding approval. We are starting to organize our kick-off meeting now.

2024-08-26 - Website online 🚀

Our new domain sparql-ml.eu is registered and a first page is online.