Universal RDF Dataset Normalization Algorithm (2015) in Java

An implementation of the URDNA-2015 algorithm which transforms any RDF dataset into a canonical form.

License	The Apache License, Version 2.0
GroupId	io.setl
ArtifactId	rdf-urdna
Last Version	1.1
Release Date	Apr 3, 2021
Type	jar
Description	Universal RDF Dataset Normalization Algorithm (2015) in Java An implementation of the URDNA-2015 algorithm which transforms any RDF dataset into a canonical form.
Project URL	https://github.com/setl/rdf-urdna
Source Code Management	https://github.com/setl/rdf-urdna

Download rdf-urdna

Filename	Size
rdf-urdna-1.1.pom
rdf-urdna-1.1.jar	19 KB
rdf-urdna-1.1-sources.jar	10 KB
rdf-urdna-1.1-javadoc.jar	397 KB

How to add to project

Apache Maven

<!-- https://jarcasting.com/artifacts/io.setl/rdf-urdna/ -->
<dependency>
    <groupId>io.setl</groupId>
    <artifactId>rdf-urdna</artifactId>
    <version>1.1</version>
</dependency>

Gradle Groovy

// https://jarcasting.com/artifacts/io.setl/rdf-urdna/
implementation 'io.setl:rdf-urdna:1.1'

Gradle Kotlin

// https://jarcasting.com/artifacts/io.setl/rdf-urdna/
implementation ("io.setl:rdf-urdna:1.1")

Apache Buildr

'io.setl:rdf-urdna:jar:1.1'

Apache Ivy

<dependency org="io.setl" name="rdf-urdna" rev="1.1">
  <artifact name="rdf-urdna" type="jar" />
</dependency>

Groovy Grape

@Grapes(
@Grab(group='io.setl', module='rdf-urdna', version='1.1')
)

Scala SBT

libraryDependencies += "io.setl" % "rdf-urdna" % "1.1"

Leiningen

[io.setl/rdf-urdna "1.1"]

Dependencies

runtime (1)

Group / Artifact	Type	Version
com.apicatalog : titanium-json-ld	jar	1.0.0

test (1)

Group / Artifact	Type	Version
junit : junit	jar	4.12

Project Modules

There are no modules declared in this project.

rdf-urdna

This is an implementation of the Universal RDF Dataset Normalization Algorithm (2015).

Usage:

   RdfDataset normalizedData = RdfNormalize.normalize(rdfInput);

The library passes all the standard tests for the URDNA2015 algorithm.

Users are advised that the time the URDNA2015 algorithm takes to complete is influenced by the number of blank nodes in the input. It is possible to create small datasets that would take more energy than exists in the observable universe to normalize.

SETL

Versions

Version
1.1 Apr 3, 2021
1.0 Nov 10, 2020