Abstract
This article deals with a practical and synthetic view of conceptual modelling. It suggests four graph database normal forms organised into two levels of conceptual modelling: data and metadata, with room for yet one conceivable graph normal form based on old approaches, such as object-oriented class normalisation and the idea of conceptual symmetry. Attention is also paid to bridging the semantic gap between a database on the server side and a programming language on the client side, which argues for using graph databases as better data sources for business intelligence systems and working with machine learning language models. The authors applied their practical experience in teaching database modelling at a university and many years of experience in software development in Smalltalk, Python, Java, and C#.
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Merunka, V., Wijekoon, H., Beránek, P. (2024). Conceptual Data Normalisation from the Practical View of Using Graph Databases. In: Almeida, J.P.A., Di Ciccio, C., Kalloniatis, C. (eds) Advanced Information Systems Engineering Workshops. CAiSE 2024. Lecture Notes in Business Information Processing, vol 521. Springer, Cham. https://doi.org/10.1007/978-3-031-61003-5_21
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