Less dependency bloat, easier integrations! We've rewritten the fastest JVM-based RDF serialization library (Jelly-JVM) from Scala to pure Java. This means:

- 🪶 Drastically reduced dependency bloat. For Apache Jena users, that means a drop in dependency size from 10.6 MB to 0.23 MB.
- 🔨 Easier integrations with Java code – no need to wrangle Scala-specific structures.
- 🤗 Easier contributions from the community! With Java, it will be easier for others to understand and modify the code.

Double award! 🏆 🏆 Best Poster and the Dieter Fensel Visionary Award at European Semantic Web Conference went to the work "Representing and querying data tensors in #RDF and #SPARQL", done by Piotr Marciniak, our CTO Piotr Sowiński, and Maria Ganzha.

We are deeply thankful for this distinction! The work is absolutely key to #neurosymbolic systems we are building.

Poster: https://ostrzyciel.eu/assets/pdf/poster_tensor_rdf_eswc_2025.pdf
Paper: http://arxiv.org/pdf/2504.19224
Website, code, datasets, and more: https://w3id.org/rdf-tensor

We are hiring! Looking for a Scala / Java developer to join our R&D team building cutting-edge neurosymbolic AI systems. Details and application form: https://tinyurl.com/dwjmzpbm

Say hi to our first customer! 🎉 We are partnering with @knowledgepixels to help them build hyper-scalable knowledge graph tools boosting scientific knowledge sharing.

We helped them scale the #Nanopublication network with NeverBlink’s streaming KG tech Jelly, which was the perfect fit for this use case. 💪

We went down from dozens of minutes to retrieve 60k nanopubs to less than 4 seconds. ⌚

If you are applying #KnowledgeGraphs to a performance-sensitive domain, reach out to @ostrzyciel

We are happy to announce the release of jelly-cli v0.1.0!

A new, easy-to-use tool that lets you translate Jelly to other #RDF knowledge graph formats and back 🔁 with just one command. It will also help you inspect and validate #Jelly files 🔎

Try it out! https://github.com/Jelly-RDF/cli