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Erschienen in: Business & Information Systems Engineering 1/2024

17.07.2023 | Research Paper

Model-to-Model Transformation

From UML Class Diagrams to Labeled Property Graphs

verfasst von: Ana León, Maribel Yasmina Santos, Alberto García, Juan Carlos Casamayor, Oscar Pastor

Erschienen in: Business & Information Systems Engineering | Ausgabe 1/2024

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Abstract

Conceptual schemas are the basis to build well-grounded Information Systems, by representing the main concepts of a domain of knowledge, as well as the relationships among them. Since conceptual schemas focus on the concepts, they are independent of the specific technological platform used to implement them. This allows a single conceptual schema to be transformed into different platform-specific models according to the implementation requirements. This is a non-trivial process that is crucial for the performance and maintainability of the system, as well as for the accomplishment of the domain data requirements. Much research has been done on transforming conceptual schemas into relational data models. Nevertheless, less work has been done on transforming conceptual schemas into property graphs, a data structure indispensable to building appropriate and efficient systems based on graph databases. The work proposes a systematic approach to transform conceptual schemas, represented as UML class diagrams, into property graphs by using a set of transformation rules and patterns applied in a systematic way. Besides a practical example used to help the presentation of the proposed approach, the evaluation has been done by measuring different quality dimensions such as semantic equivalence, readability, maintainability, complexity, size, and performance.

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Metadaten
Titel
Model-to-Model Transformation
From UML Class Diagrams to Labeled Property Graphs
verfasst von
Ana León
Maribel Yasmina Santos
Alberto García
Juan Carlos Casamayor
Oscar Pastor
Publikationsdatum
17.07.2023
Verlag
Springer Fachmedien Wiesbaden
Erschienen in
Business & Information Systems Engineering / Ausgabe 1/2024
Print ISSN: 2363-7005
Elektronische ISSN: 1867-0202
DOI
https://doi.org/10.1007/s12599-023-00824-9

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