Tutorial: Mapping the Core Business Vocabulary from XSD to RDF

Use Case UC2.2 focuses on enabling data interoperability by converting XML data into RDF format, ensuring that it adheres to the semantic standards defined by the chosen Core Vocabulary. Specifically, it zooms in on the process of mapping an existing XML Schema Definition (XSD) to a Core Vocabulary. For this tutorial, we will use the Core Business Vocabulary (CBV). The procedure involves defining the transformation rules that align data from the existing XSD to the concepts and terms of the Core Vocabulary. . This tutorial guides you through the key steps in creating the mappings to Core Vocabularies (CV) involving:

We will create a conceptual mapping between the XSD elements and RDF terms from the Core Business Vocabulary. This will guide the transformation of the XML data to RDF. There are two levels of conceptual mapping:

The RDF Mapping Language (RML) is ideal for the task of implementing the conceptual mappings as technical mappings, because it allows for seamless mapping from XML to RDF. We will use RML to create machine-executable mapping rules as follows.
First, the rml:logicalSource is declared, with the root of the tree in the XML file, which is */LegalEntity in our use case that assumes there to be an rml:source called SampleData_Business.xml with instance data.
Next, a rr:subjectMap is added to say how each <LegalEntity> node becomes the RDF subject—here we build an IRI from generate-id(.) and type it as legal:LegalEntity.
Finally, one or more rr:predicateObjectMap blocks capture the properties we need; in the simplest case we map the child element <LegalName> to the vocabulary property legal:legalName.
The complete example RML mapping code looks as follows, in Turtle syntax:

This needs to be carried out for all elements from the XSD that were selected for mapping in Phase 1.

Now that we have created the mappings, we can apply them to sample data using RMLMapper or a similar tool selected from the SEMIC Tooling Assistant. For this tutorial, we will use RMLMapper, which will read the RML mapping file and the input XML data, and then generate the corresponding RDF output.
The snippet below is a single triple set produced when the mapping is run over the sample file SampleData_Business.xml (see Phase 1).
It shows that one of the XML <LegalEntity> records—the Belgian committee for UNICEF—has been turned into an RDF resource of type legal:LegalEntity with its legal:legalName correctly populated.

We will validate the output in two ways: to check that it exists and the graph and to check that it exists as intended also regarding any constraints on the shape of the graph.
You can validate the generated RDF using SPARQL queries to ensure that the transformation adheres to the defined conceptual mapping. Since we want to validate rather than retrieve information, we use SPARQL ASK queries, which will return either a ‘yes’ or a ‘no’. For our running example, the SPARQL query for validating the LegalEntity is:

SHACL validation can be applied to ensure that the RDF data conforms to the required shapes and structures regarding any constraints that must hold.
An example SHACL shape for validating LegalEntity is:
To create a SHACL shape for the given RDF output, where the LegalEntity (legal:LegalEntity) has a legalName property, we need to define a SHACL shape that validates the type of the LegalEntity, the presence of the legalName property, and its datatype.

Once the mappings are validated, the next step is to disseminate the mapping as a package of documentation together with the artefacts. The package includes: