Be careful when designing semantic databases: Data and concepts redundancy

Recently, ontologies have been widely adopted by small, medium and large companies in various domains. These ontologies may contain redundant concepts (computed from primitive concepts). At the beginning of the development of ontologies, the relationship between them and the database was weakly coupled. With the explosion of semantic data, persistent solutions to ensure a high performance of applications were proposed. As a consequence, a new type of database, called semantic database (SDB) is born. Several types of SDB have been proposed and supported by different DBMS, where each one has its architecture and its storage layouts for ontologies and its instances. At this stage, relationship between databases and ontologies becomes strongly coupled. As a consequence, several research studies were proposed on the physical design phase of SDB. To guarantee the similar success that relational databases got, SDB has to be supported by complete design methodologies and tools including the different steps of the database life cycle. Such methodology should identify the redundancy embedded into ontology. In this paper, we propose a design methodology dedicated to SDB including the main phases of the lifecycle of the database development: conceptual, logical, deployment and physical. The conceptual design of SDB can be easily performed by exploiting the similarities between ontologies and conceptual models. The logical design phase is performed thanks to the incorporation of dependencies between concepts and properties in the ontologies. These dependencies are quite similar to the principle of functional dependencies defined in the traditional databases. Due to the diversity of the SDB architectures and the variety of the used storage layouts (horizontal, vertical, binary) to store and manage ontological data, we propose a SDB deployment à la carte. Finally, a prototype implementing our design approach on Oracle 11g is outlined