RDF data validation

Optionally you can setup data validation to make sure all data added to the knowledge graph is complying with a specific data model.

SHACL validation#

For more informations about creating SHACL shapes, checkout the SHACL Shapes repository of the Institute of Data Science at Maastricht University: https://github.com/MaastrichtU-IDS/shacl-shapes

To find SHACL shapes, checkout the Shapes of You SHACL shapes registry: http://index.semanticscience.org

Here are a few solutions to validate RDF with SHACL:

Enable SHACL validation when creating a new repository if using Ontotext GraphDB free edition.
Use RDF4J with java (good if your already working on a java app based on RDF4J)
TopQuadrant/shacl (java)
RDFLib/pySHACL (python, requires to load the RDF in rdflib)

You can also validate small RDF files directly from a few web app:

Use Compact SHACL#

You can try out the experimental Compact SHACL syntax to more easily write shapes.

There are currently no VisualStudio Code extension for better visualization of compact SHACL files, but you can use the turtle format to make it more readable. Open the settings.json file in File > Preference > Settings, and add:

    "files.associations": {
        "*.shaclc": "turtle",
        "*.shc": "turtle"
    }

You can easily convert Compact SHACL to RDF SHACL (required for most use of SHACL) with java:

Download the jar:

wget https://gitlab.ontotext.com/yasen.marinov/shaclconvert/-/raw/master/built/shaclconvert.jar

Convert compact SHACL to RDF SHACL:

java -jar shaclconvert.jar input.shaclc output.shacl

ShEx validation#

Here are a few solutions to validate RDF with ShEx:

iovka/shex-java using RDF4J
hsolbrig/PyShEx (python, can perform validation directly on a SPARQL endpoint)

You can also validate small RDF files directly from a few web app: