Legacy scientific applications remain valuable research assets but are often tightly coupled to project-specific execution environments, limiting their reuse, reproducibility, and deployment within modern scientific workflow systems and cloud-native Virtual Research Environments (VREs). Existing migration approaches pr...
N. Soveizi, S. Tesselaar, Hero Robinson Brouwer et al.· 0 citations
Digital Twin (DT) ecosystems integrate heterogeneous computational models to represent complex systems under evolving, purpose-specific objectives. Systematic reuse of existing high-quality models and datasets is essential for scalable DT development, yet is constrained by heterogeneity in semantic intent, data structu...
N. Soveizi, Milan Kopp, Parinaz Rashidi et al.· 0 citations
LLMCrater is a lifecycle-aware metadata generation framework that combines Large Language Models (LLMs) with stage-specific RO-Crate metadata profiles that progressively enriches metadata across four research lifecycle stages while remaining compatible with RO-Crate~1.1 and EOSC metadata recommendations.
Dani Termaat, N. Soveizi, Zhi-Ming Zhao et al.· 0 citations
A lifecycle-aware framework that integrates quantitative software quality assessment with Large Language Model (LLM)-based code refinement is proposed and the potential of metric-driven LLM feedback for research software quality improvement is demonstrated while highlighting its inherently multi-objective nature.
Nafis Tanveer Islam, N. Soveizi, Yutong Li et al.· 0 citations
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