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Concept into Architecture: A Pragmatic Modeling Method for the Acquisition and Representation of Information

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Advances in Data Science and Information Engineering

Abstract

Process models are very important in a wide range of application areas, for example, software development or operational management. The first step in modeling a process is gaining information and knowledge engineering. This information documented as process models are a very important part of Enterprise Architectures (EAs). All forces in the NATO use the NATO Architecture Framework (NAF). Process models in the NAF are represented as part of the operational view, the sub-view NOV-5. Process models are often the starting point for modeling or creating an EA. According to the principles of proper modeling, not only the correct use of the syntax is necessary but also the relevance of a model. This is inseparable from the underlying information from which the model is created.

This chapter deals with the creation of a modeling method that allows subject matter experts (SME) in the area to be modeled to get started with EA. The aim of presentation is to use the method to obtain the necessary information for the creation of the process model and represent the information in a human- and machine-readable form. Also, the goal of this contribution is to transform the information syntactically correctly as a NOV-5 process model, using a software developed as part of this contribution. The transformed NOV-5 model is similar to the original representation of the gained information, so this enables the SME to check the created NAF-compliant model for correctness of content and to use the model without knowledge of the NAF.

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Jahnen, S., Pickl, S., Bein, W. (2021). Concept into Architecture: A Pragmatic Modeling Method for the Acquisition and Representation of Information. In: Stahlbock, R., Weiss, G.M., Abou-Nasr, M., Yang, CY., Arabnia, H.R., Deligiannidis, L. (eds) Advances in Data Science and Information Engineering. Transactions on Computational Science and Computational Intelligence. Springer, Cham. https://doi.org/10.1007/978-3-030-71704-9_47

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