The data model in DFRNT data products follows the TerminusDB graph metamodel 1:1, and enables easy data modelling and advanced visualisation
The data modeller provides 1:1 mapping between the graphical field definitions and the JSON-LD schema definitions for Types, Traits and Enums from TerminusDB, which makes it a great playground to exchange JSON-LD data definitions.
Records is where instance data lives, your data. They are called documents in TerminusDB lingo and the RDF triples they involve are represented using the JSON-LD format, and the structure is controlled through layered JSON-LD class constructs. Records may include the following kinds of properties (data fields):
Properties hold the data and references between records in the system. Beneath the data model, it’s RDF triples all the way down. The RDF triples are constrained by a schema checker that checks that all data is consistent. Instead of OWL and SHACL, TerminusDB has an enterprise-orientated (vs academic) data model with both shapes and constraints like multiplicities, cardinalities, data types and more.
The properties on Types and Traits can either be of a base type or link to other Types, Traits or Enum values and data structures. Base data properties, Traits and Enums are attached directly to the Record, while Type references are directional links to other records.
Composition of Traits and Types means that property definitions from their parents get inherited down a hierarchy. The same property name may not be inherited from multiple parents, that is called a prevented diamond property violation.
All records have a type that defines the data structure of the record. Types have properties that may be composed (inherited) from one or multiple types.
Traits are reusable data structures that can be attached to types as properties, and may be composed by one or multiple traits. By defining a data structure as a trait, instead of as a type, it can be reused across types to build complex data structures.
Some traits have special meaning in DFRNT.tech and are used to build data structures and taxonomies that have semantic meaning, as part of the collaborative semantic knowledge graph.
Enumerations (list of constant values) can be used to constrain properties to certain values. They are frequently used for categories and other sets of information.