SANSA 0.3 (Scalable Semantic Analytics Stack) Released

Dear all,

The Smart Data Analytics group [1] is happy to announce SANSA 0.3 - the
third release of the Scalable Semantic Analytics Stack. SANSA employs
distributed computing via Apache Spark and Flink in order to allow
scalable machine learning, inference and querying capabilities for large
knowledge graphs.


You can find the FAQ and usage examples at

The following features are currently supported by SANSA:

* Reading and writing RDF files in N-Triples, Turtle, RDF/XML, N-Quad
* Reading OWL files in various standard formats
* Support for multiple data partitioning techniques
* SPARQL querying via Sparqlify (with some known limitations until the
   next Spark 2.3.* release)
* SPARQL querying via conversion to Gremlin path traversals
* RDFS, RDFS Simple, OWL-Horst (all in beta status), EL (experimental)
   forward chaining inference
* Automatic inference plan creation (experimental)
* RDF graph clustering with different algorithms
* Rule mining from RDF graphs based AMIE+
* Terminological decision trees (experimental)
* Anomaly detection (beta)
* Distributed knowledge graph embedding approaches: TransE (beta),
   DistMult (beta), several further algorithms planned

Deployment and getting started:

* There are template projects for SBT and Maven for Apache Spark as
   well as for Apache Flink available [2] to get started.
* The SANSA jar files are in Maven Central i.e. in most IDEs you can
   just search for “sansa” to include the dependencies in Maven projects.
* There is example code for various tasks available [3].
* We provide interactive notebooks for running and testing code [4] via

We want to thank everyone who helped to create this release, in
particular the projects Big Data Europe [5], HOBBIT [6], SAKE [7], Big
Data Ocean [8], SLIPO [9], QROWD [10] and BETTER.

View this announcement on Twitter and the SDA blog:

Kind regards,

The SANSA Development Team


Prof. Dr. Jens Lehmann
Computer Science Institute       Enterprise Information Systems
University of Bonn               Fraunhofer IAIS    

Received on Friday, 15 December 2017 12:43:08 UTC