Abstract
To improve database system quality as well as runtime use of conceptual models, many logic-based reconstructions of conceptual data modelling languages have been proposed in a myriad of logics. They each cover their features to a greater or lesser extent and are typically motivated from a logic viewpoint. This raises questions such as what would be an evidence-based common core and what is the optimal language profile for a conceptual modelling language family. Based on a common metamodel of UML Class Diagrams (v2.4.1), ER/EER, and ORM/2’s static elements, a set of 101 conceptual models, and availing of computational complexity insights from Description Logics, we specify these profiles. There is no known DL language that matches exactly the features of those profiles and the common core is small (in the tractable \(\mathcal {ALNI}\)). Although hardly any inconsistencies can be derived with the profiles, it is promising for scalable runtime use of conceptual data models.
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Acknowledgments
This work is based upon research supported by the National Research Foundation of South Africa (Project UID90041) and the Argentinean Ministry of Science and Technology.
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Fillottrani, P.R., Keet, C.M. (2015). Evidence-Based Languages for Conceptual Data Modelling Profiles. In: Tadeusz, M., Valduriez, P., Bellatreche, L. (eds) Advances in Databases and Information Systems. ADBIS 2015. Lecture Notes in Computer Science(), vol 9282. Springer, Cham. https://doi.org/10.1007/978-3-319-23135-8_15
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