Conceptual Universal Database Language: Moving Up the Database Design Levels

Database Design Revisited

“…It is obvious from the plethora of models (presented in the previous section) that there is a need for a DBMS able to provide more powerful data types, as those of the real world complex data. In the first four discussed models, handling of such types by the programmer by SQL-like languages and extensions requires knowledge of the internal organization of both metadata and data [12]. Thus, the ultimate goal should be to provide a data manipulation language able to manipulate directly the composite data types (without bothering the programmer with internal organization details), while permitting the direct expression of restrictions over subfields.…”

“…Apart from being a data manipulation language able to manipulate directly composite data types, while permitting the direct expression of restrictions over subfields, CUDL allows the application programmer/designer to model the structures of its application with composite data types that are closer to the ER diagrams and sometimes without any decomposition of the ER entities into simpler ones (an example is depicted in [12]).…”

“…We demonstrate that a database modelled by Entity-Relationship (ER) diagrams can be directly expressed to the CUDL Abstraction Level (CAL,) the data model corresponding to CUDL, by a set of rules for direct transformation of ER diagrams to CAL. This set consists of a basic set of five rules (first presented in [12]), that is extended with an extra rule (first presented in [13]) that deals with specific situations appearing in practical applications. Consequently, the resulting more powerful and composite data can be directly maintained with the CUDL language.…”

“…In this way, the development process consisting in conceptual design (ER), transformation to Logical Relational Schema, usage of SQL for data manipulation/retrieval and the reverse steps to present the results in the conceptual level is simplified by conceptual design (ER), transformation to CAL and the usage of CUDL for direct manipulation/retrieval of real world (conceptual) structures. In this paper, we present an enhanced revisiting of the whole database design process, based on the rules presented in [12,13], using examples that demonstrate the benefits for the database designer of using realworld data types.…”

“…The transformation from CAL to FDB (meta-model, [21,23]) has been studied in [9,11]. In Section 4, we present the 5 Rule Set for Transformation from ER to CAL [12] (dealing with the most common cases that appear in real life applications, for the transformation from ER diagrams to CAL), while in Section 5, we present the addition of an extra rule that is needed for the transformation of a relation between a weak and a strong (not identifying) entity that also has attributes. Section 6 concludes the paper and presents future research possibilities.…”