Applications using Jelly
If you are using Jelly in your project, we would be glad to list it here! Please open an issue or open a pull request with the information on your use case.
Jelly-JVM
- Nanopub Registry and Nanopub Query – next-gen services for distributed storage, management, and querying of nanopublications.
- Jelly is used for communication between the services in the nanopub network. Jelly endpoints (ending with
.jelly) are also exposed for downstream applications to consume nanopubs. - The Registry stores nanopublications in the Jelly format and uses a Jelly transcoder to merge nanopubs on the fly into a single stream.
- Jelly is used for communication between the services in the nanopub network. Jelly endpoints (ending with
jelly-cli– simple but performant command-line utility for working with Jelly files.- The app can be used to convert to/from Jelly, validate and debug Jelly files.
- You can find the code and released binaries on GitHub. The repository also has up-to-date installation instructions and command usage examples.
- RiverBench benchmark suite.
- Jelly is used as one of the serialization formats for distributing datasets in RiverBench.
- Jelly is also used for distributing the RDF metadata of benchmark datasets, tasks, and other resources.
- This is implemented in the ci-worker application – a Scala 3 program making heavy use of Jelly-JVM's streaming capabilities.
- Jelly-JVM benchmark code. This code was used to produce the results seen on the performance page.
- RDF Stream Taxonomy (RDF-STaX) uses Jelly for distributing the RDF-STaX ontology and the living literature review of RDF streaming.
- This is implemented using Apache Jena's RIOT command-line utility and Jelly-JVM's Jena plugin. Source code: GitHub.
Example datasets in the Jelly format
Below listed are some example datasets available in the Jelly format. All of these are in the delimited format. The licenses for these datasets are specified on the linked documentation pages.
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Large datasets (millions of triples/quads):
- ASSIST-IoT weather measurements (documentation) – 80 million triples.
- 5 million nanopublications (documentation) – 171 million quads.
- RDF-star annotated facts from YAGO (documentation) – 2 million triples.
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Small datasets:
- RDF-STaX ontology (documentation).
- RiverBench suite metadata (documentation) – RiverBench also includes metadata in Jelly for benchmark tasks, datasets, and more.
You can find some more interesting datasets in the Jelly format on the RiverBench website.
Commercial support
NeverBlink provides commercial support services for Jelly, including implementing custom features, system integrations, implementations for new languages, benchmarking, and more.