Using Knowledge Graphs to Detect Enterprise Architecture Smells - The Practice of Enterprise Modeling
Conference Papers Year : 2021

Using Knowledge Graphs to Detect Enterprise Architecture Smells

Abstract

Hitherto, the concept of Enterprise Architecture (EA) Smells has been proposed to assess quality flaws in EAs and their models. Together with this new concept, a catalog of different EA Smells has been published and a first prototype was developed. However, this prototype is limited to ArchiMate and is not able to assess models adhering to other EA modeling languages. Moreover, the prototype is not integrate-able with other EA tools. Therefore, we propose to enhance the extensible Graph-based Enterprise Architecture Analysis (eGEAA) platform that relies on Knowledge Graphs with EA Smell detection capabilities. To align these two approaches, we show in this paper, how ArchiMate models can be transformed into Knowledge Graphs and provide a set of queries on the Knowledge Graph representation that are able to detect EA Smells. This enables enterprise architects to assess EA Smells on all types of EA models as long as there is a Knowledge Graph representation of the model. Finally, we evaluate the Knowledge Graph based EA Smell detection by analyzing a set of 347 EA models.
Fichier principal
Vignette du fichier
514409_1_En_4_Chapter.pdf (2.67 Mo) Télécharger le fichier
Origin Files produced by the author(s)

Dates and versions

hal-04323868 , version 1 (05-12-2023)

Licence

Identifiers

Cite

Muhamed Smajevic, Simon Hacks, Dominik Bork. Using Knowledge Graphs to Detect Enterprise Architecture Smells. 14th IFIP Working Conference on The Practice of Enterprise Modeling (PoEM), Nov 2021, Riga, Latvia. pp.48-63, ⟨10.1007/978-3-030-91279-6_4⟩. ⟨hal-04323868⟩
40 View
108 Download

Altmetric

Share

More