How do properties create links between concepts?
As an OWL ontology, the CDM allows to create as many properties as needed to fully describe the many interactions between concepts. Currently, there are approximately 1000 relations between the objects described in the CDM.

This allows for metadata to be connected in the Cellar in both inferred and non-inferred way.
For example, in Cellar, the metadata may say that “advocate general Y delivers case law X”. If we suppose that the AGENT and the WORK are connected in a non-inferred way: this means that the link between the two objects is obtained directly from the metadata of the document ingested in the Cellar.
Then, because there is an inverse object property defined for cdm:delivers in the CDM (cdm:delivered_by) Cellar will also be able to infer the following statement “case law X is delivered by advocate general Y”.
That way, it is possible to retrieve the information for the case law X coming from the agent’s metadata, but it is also possible to retrieve the agent’s information coming from the case law metadata.

How do properties shape metadata?
In addition to object properties, OWL ontologies also allow the definition of data properties. These properties describe the type of data that is expected for a given concept.
For example, in the CDM the data property cdm:case-law_affaire_year specifies that this metadata has a domain (i.e., the subject of the data property) that is cdm:case-law and a range (i.e., the value of this property) that is xsd:gYear. In other words, to associate a year of the affaire to a case law, the value needs to be expressed in an xsd:gYear format, and this constraint comes directly from the CDM rules.
We have approximately 900 data properties in the CDM.
What is cardinality in the CDM?
As mentioned in the previous sections, properties can define relationships between concepts and constrain the format of metadata according to specific rules defined in the CDM. Another possibility that the CDM gives is to define cardinality for properties.
For example, the CDM allows to define a property cdm:item_belongs_to_manifestation and give it a cardinality of “minimum 1” (1 to N). Because this is defined as a restriction in the CDM, this means that to be considered an “item”, an instance has to be linked to minimum 1 “manifestation” with the property cdm:item_belongs_to_manifestation. The cardinality for an instance to be considered a “manifestation” is of exactly 1 “expression”. Cardinality also works with data properties, such as defining exactly 1 “manifestation type” in the rdfs:Literal format.
In other words, what the illustration below tells us is that for an instance in the Cellar to be considered a manifestation, it must be the manifestation of exactly 1 “expression”, and it needs to have a type formatted in a textual string for example.
Bear in mind that we only show a selection of examples here and that cardinality and property restrictions are a lot more complex than that in the CDM, with dozens of them defined for each class.

How do we assess the quality of the metadata?
One key principle of CDM is to ensure a high level of quality for the metadata while responding to the evolving needs of the businesses. To do so, different tests are implemented to guarantee this level of quality.
One of them consists of making sure the metadata in the CDM corresponds to our standards. This is done, for example, using a consistent and normalized structure across versions of the CDM, the systematic definition of classes and properties, or the use of naming conventions, etc.
With these tests, we also want to ensure the backward compatibility of the CDM so that the business’ requirements are met, without breaking existing functionalities by adding or changing code.