Dual deep modeling: multi-level modeling with dual potencies and its formalization in F-Logic

Bernd Neumayr, Christoph Georg Schütz, Manfred Jeusfeld, Michael Schrefl

Research output: Contribution to journalArticlepeer-review

Abstract

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.
Original languageEnglish
Pages (from-to)233-268
Number of pages36
JournalSoftware and Systems Modeling
Volume17
Issue number1
DOIs
Publication statusPublished - 2018

Fields of science

  • 102 Computer Sciences
  • 102010 Database systems
  • 102015 Information systems
  • 102016 IT security
  • 102025 Distributed systems
  • 102027 Web engineering
  • 102028 Knowledge engineering
  • 102030 Semantic technologies
  • 102033 Data mining
  • 502050 Business informatics
  • 503008 E-learning

JKU Focus areas

  • Computation in Informatics and Mathematics
  • Management and Innovation

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