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Dual deep modeling: multi-level modeling with dual potencies and its formalization in F-Logic
Johannes Kepler University Linz, Linz, Austria.
Johannes Kepler University Linz, Linz, Austria.
University of Skövde, School of Informatics. University of Skövde, The Informatics Research Centre. (Information Systems)ORCID iD: 0000-0002-9421-8566
Johannes Kepler University Linz, Linz, Austria.
2016 (English)In: Journal of Software and Systems Modeling (online), ISSN 1619-1366, E-ISSN 1619-1374, 1-36 p.Article in journal (Refereed) Epub ahead of print
Abstract [en]

An enterprise database contains a global, integrated, and consistent representation of a company’s data. Multi-level modeling facilitates the definition and maintenance of such an integrated conceptual data model in a dynamic environment of changing data requirements of diverse applications. Multi-level models transcend the traditional separation of class and object with clabjects as the central modeling primitive, which allows for a more flexible and natural representation of many real-world use cases. In deep instantiation, the number of instantiation levels of a clabject or property is indicated by a single potency. Dual deep modeling (DDM) differentiates between source potency and target potency of a property or association and supports the flexible instantiation and refinement of the property by statements connecting clabjects at different modeling levels. DDM comes with multiple generalization of clabjects, subsetting/specialization of properties, and multi-level cardinality constraints. Examples are presented using a UML-style notation for DDM together with UML class and object diagrams for the representation of two-level user views derived from the multi-level model. Syntax and semantics of DDM are formalized and implemented in F-Logic, supporting the modeler with integrity checks and rich query facilities.

Place, publisher, year, edition, pages
Berlin, Germany: Springer Berlin/Heidelberg, 2016. 1-36 p.
Keyword [en]
data modeling, multi-level modeling, f-logic
National Category
Information Systems
Research subject
Natural sciences; Technology
URN: urn:nbn:se:his:diva-12138DOI: 10.1007/s10270-016-0519-zOAI: diva2:919649

The paper was published online on 2016-04-07 by Springer. The article is open-access with license "Creative Commons Attribution 4.0 International License"

Available from: 2016-04-14 Created: 2016-04-14 Last updated: 2016-08-18

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