Record link: 
http://hdl.handle.net/20.500.12708/150287
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Title: 
Historization of Enterprise Architecture Models via Enterprise Architecture Knowledge Graphs
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Citation: 
Bråtfors, R., Hacks, S., & Bork, D. (2022). Historization of Enterprise Architecture Models via Enterprise Architecture Knowledge Graphs. In The Practice of Enterprise Modeling (pp. 51–65). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-031-21488-2_4
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Publisher DOI: 
10.1007/978-3-031-21488-2_4
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Publication Type: 
Inproceedings - Full-Paper Contribution
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Language: 
English
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Authors: 
Bråtfors, Robin 
Hacks, Simon 
Bork, Dominik 
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Organisational Unit: 
E194-03 - Forschungsbereich Business Informatics 
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Published in: 
The Practice of Enterprise Modeling 
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ISBN: 
978-3-031-21487-5
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Volume: 
456
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DOI of the book: 
10.1007/978-3-031-21488-2
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Date (published): 
17-Nov-2022
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Event name: 
PoEM 2022 
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Event date: 
23-Nov-2022 - 25-Nov-2022
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Event place: 
London, United Kingdom of Great Britain and Northern Ireland (the)
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Number of Pages: 
15
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Publisher: 
Springer Nature Switzerland AG, Cham, Switzerland
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Peer reviewed: 
Yes
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Keywords: 
Enterprise architecture; Historical analysis; Knowledge graph
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Abstract: 
Enterprise Architecture (EA) is the discipline that aims to provide a holistic view of the enterprise by explicating business and IT alignment from the perspectives of high-level corporate strategy down to daily operations and network infrastructures. EAs are consequently complex as they compose and integrate many aspects on different architecture layers. A recent proposal to cope with this complexity and to make EAs amenable to automated and intuitive visual analysis is the transformation of EA models into EA Knowledge Graphs. A remaining limitation of these approaches is that they perceive the EA to be static, i.e., they represent and analyze EAs at a single point in time. In the paper at hand, we introduce a historization concept, a prototypical implementation, and a performance analysis for how EAs can be represented and processed to enable the analysis of their evolution.
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Research facilities: 
Pilotfabrik 
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Project title: 
MFP 4.2 Advanced Analytics for Smart Manufacturing: 854187 (Center for Digital Production GmbH) 
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Research Areas: 
Information Systems Engineering: 100%
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Science Branch: 
1020 - Informatik: 90%
5020 - Wirtschaftswissenschaften: 10%
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Appears in Collections:
Conference Paper

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