Automatic conceptual database design based on heterogeneous source artifacts

Abstract

The article presents an approach to the automatic derivation of conceptual database models from heterogeneous source artifacts. The approach is based on the integration of conceptual database models that are derived from source artifacts of one single type by already existing tools, whereby those models possess limited certainty given their limited completeness and correctness. The uncertainty of the automatically derived models from specific source artifacts is expressed and managed through the effectiveness measure of the generation of specific concepts of the input conceptual database models. The approach is implemented by the DBomnia tool - the first online web-based tool enabling automatic derivation of conceptual database models from heterogeneous source artifacts (business process models and textual specifications). DBomnia employs other pre-existing tools to derive conceptual models from sources of the same type and then integrates those models. The case study-based evaluation proves that the implemented approach enables effective automatic derivation of the conceptual database model from a set of heterogeneous source artifacts. Moreover, the automatic derivation of the conceptual database model from a set of heterogeneous source artifacts is more effective than each independent automatic derivation of the conceptual database model from sources of one single type only.