Model-Based Construction of Enterprise Architecture Knowledge Graphs

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Abstract

Enterprise Architecture offers guidelines for the coherent, model-based design and management of enterprises. EA models provide a layered, integrated, and cohesive representation of the enterprise, enabling communication, analysis, and decision making. With the increasing size of EA models, automated analysis becomes essential. However, advanced model analysis is neither incorporated in current EA methods like ArchiMate nor supported by existing EA tools like Archi. Knowledge Graphs (KGs) can effectively organize and represent knowledge and enable reasoning to utilize this knowledge, e.g., for decision support. This paper introduces a model-based Enterprise Architecture Knowledge Graph (EAKG) construction method and shows how starting from ArchiMate models, an initially derived EAKG can be further enriched by EA-specific and graph characteristics-based knowledge. The introduced EAKG entails new representation and reasoning methods applicable to EA knowledge. As a proof of concept, we present the results of a first Design Science Research Cycle aiming to realize an Archi plugin for the EAKG that enables analysis of EA Smells within ArchiMate models.

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Glaser, P. L., Ali, S. J., Sallinger, E., & Bork, D. (2022). Model-Based Construction of Enterprise Architecture Knowledge Graphs. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13585 LNCS, pp. 57–73). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-17604-3_4

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