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 language | English |
|---|---|
| Pages (from-to) | 233-268 |
| Number of pages | 36 |
| Journal | Software and Systems Modeling |
| Volume | 17 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 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