Abstract
Forward engineering relational schemas based on conceptual models is an established practice, with a number of commercial tools available and widely used in production settings. These tools employ automated transformation strategies to address the gap between the primitives offered by conceptual modeling languages (such as ER and UML) and the relational model. Despite the various benefits of automated transformation, once a database schema is obtained, data access is usually undertaken by relying on the resulting schema, at a level of abstraction lower than that of the source conceptual model. Data access then requires both domain knowledge and comprehension of the (non-trivial) technical choices embodied in the resulting schema. We address this problem by forward engineering not only a relational schema, but also creating an ontology-based data access mapping for the resulting schema. This mapping is used to expose data in terms of the original conceptual model, and hence queries can be written at a high level of abstraction, independently of the transformation strategy selected.
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Acknowledgments
This research is partly funded by Brazilian funding agencies CNPq (grants numbers 313687/2020-0, 407235/2017-5) and CAPES (grant number 23038.028816/2016-41).
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Guidoni, G.L., Almeida, J.P.A., Guizzardi, G. (2021). Forward Engineering Relational Schemas and High-Level Data Access from Conceptual Models. In: Ghose, A., Horkoff, J., Silva Souza, V.E., Parsons, J., Evermann, J. (eds) Conceptual Modeling. ER 2021. Lecture Notes in Computer Science(), vol 13011. Springer, Cham. https://doi.org/10.1007/978-3-030-89022-3_12
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