Abstract
Data architecture is composed of models, policies, rules or standards that govern which data is collected, and how it is stored, arranged, integrated, and put to use in data systems and organizations [1]. Organizations often use models to describe this data architecture for a domain. But what type of models are needed?
This vertical data architecture approach describes what different models are needed, how these models are interlinked, what the concerns are of certain representation and how an organization can deal with the challenges of keeping these models aligned. This involves the analysis of a Universe of Discourse (UoD), creating conceptual information models (in FBM), transforming these into logical data models and transform these logical models into one or more implementation models. Issues like traceability back to the UoD and impact directly from the UoD to the implementation are main issues which often are hard to tackle.
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Bulles, J., Arntz, R., Evers, M. (2020). Fully Traceable Vertical Data Architecture. In: Debruyne, C., et al. On the Move to Meaningful Internet Systems: OTM 2019 Workshops. OTM 2019. Lecture Notes in Computer Science(), vol 11878. Springer, Cham. https://doi.org/10.1007/978-3-030-40907-4_10
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DOI: https://doi.org/10.1007/978-3-030-40907-4_10
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