Innovative evaluations of conceptual database models

Two approaches of meta-modeling are described and exploited for innovative evaluations of conceptual database models. The former approach starts from the abstract machine model and through a vertical mapping designs a model, called structured database schema. The latter meta-model starts from a graph of conceptual classes and through a horizontal mapping reaches a resulting model coincident with the structured database schema. "Goodness" of the two meta-models allows proving the correct definition of the resulting model, the achievement of quality desiderata and the possibility to introduce formulas for the computation of consistency costs. "Quantitative measures" express the costs of what has been specified/proved in terms of variable cardinality; "qualitative measures" express the saving of what has been implicitly specified/proved in terms of classes.