Contributions to Proceedings:

M. Smajevic, S. Hacks, D. Bork:
"Using Knowledge Graphs to Detect Enterprise Architecture Smells";
in: "Proceedings of the 14th IFIP Working Conference, PoEM 2021, Riga, Latvia, November 24-26, 2021", Springer International Publishing, 2021, ISBN: 978-3-030-91278-9, 48 - 63.

English 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.

Enterprise Architecture, Model transformation, ArchiMate, Knowledge Graph, Analysis

Electronic version of the publication:

Created from the Publication Database of the Vienna University of Technology.