Presume the BA did a perfect job defining the requirements and defining the information. The UML diagram shows a simplified use case with actors, Business User/Analyst (BA), Ontologist, and Data Architect/Modeler In our case, we can take an RDBMS as a source and transfer the data into an RDF Store, or vice versa. Just like we can translate an algorithm from one computer language into another, we can move data from one physical representation into another without loss of information. The derived Financial Industry Business Data Model (FIB-DM) has Associative Entities rather than relationships derived from FIBO object properties. The conventional mapping is not bi-directional. The assumption that we can derive the data model relationships from the object properties is false. In recent years, Ontology Web Language (OWL) became the notation of choice for Conceptual Business Models, “domain ontologies.” The Financial Industry Business Ontology (FIBO) is a well-known example. For this purpose it is sufficient to transform data model relationships or foreign keys into object properties. Historically, the first transformations were one-directional, ontology staging, and Knowledge Graphs, from relational sources. The conventional mapping of ontology object properties to data model relationships, however, is a simplification. By implication, that means that there is a one-to-one correspondence of Ontology Class and Logical Data Model Entity. My previous article made the case that the Ontology Class and Data Model Hierarchy are the same. The Resource Description Framework (RDF) stores data as triples of a subject, predicate, and object. These transformations are straight-forward and well-defined because the models describe information data sets with relationships between the sets : Since their first versions, model transformations, the generation of a Physical Data Model from the LDM has been a core feature.Įnterprise Modeling tools also support the transformation of data into object-oriented models and vice versa. BackgroundĬommercial Data Modeling tools have be around for more than two decades. The Configurable Ontology to Data model Transformation ( CODT) enables the user to initialize transformation options. The model transformation of this mapping requires user configuration and a holistic, metadata-set based approach rather than conventional parsing of RDF/OWL files. I propose that the Associative Entity, rather than a mere relationship is the correct mapping of object properties. This article examines where the ontology object property to LDM relationship transformation fails for unconstrained cardinalities in the Open World ontology, ternary and higher relations, and critical RDF-S/OWL definitions for sub – and inverse object properties. The Association or Associative entity is appropriate the design pattern to capture semantics within the limits of the Entity-Relationship Diagrams. Ontology-derived Conceptual Data Models are Semantic Models by their origin. The Semantic Data Model emphases the common relations between entities. Academic papers, commercial tools, and education map ontology class to logical data model (LDM) entity, data property to attribute, and erroneously object property to the relationship. Model transformations depend on a mapping of meta-model elements of the source to elements of the target model.
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