Dynamic Adaption of Metamodels Based on Knowledge Graphs
Abstract
In this work, we report on recent developments regarding the dynamic adaption of metamodels at runtime. This new approach is complemented by AdoPy, a Python-based wrapper for metamodel adaption procedures that also facilitates RDF-driven modifications and extensions. The conceptualization and implementation of the approach leverage knowledge graphs to extract relevant classes, relationships, and attributes, enabling the dynamic adaption of modeling method libraries. By integrating these capabilities into ADOxx, the proposed solution links metamodeling and knowledge graphs with systems engineering.
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- Amlashi, Danial M.
- Voelz, Alexander
- Song, Junsup
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Shortfacts
Category |
Paper in Conference Proceedings or in Workshop Proceedings (Paper) |
Event Title |
Advanced Information Systems Engineering Workshops |
Divisions |
Knowledge Engineering |
Subjects |
Kuenstliche Intelligenz Angewandte Informatik Anwendungssoftware |
Event Location |
Vienna |
Event Type |
Workshop |
Event Dates |
16-20 Jun 2025 |
Publisher |
Springer Nature Switzerland |
Page Range |
pp. 18-29 |
Date |
2025 |
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