Requirements and Technical Solutions for a Scientific Data Management System Architecture
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Abstract
This paper addresses the problem of defining requirements for the architecture of a scientific data management system and selecting technical solutions for implementing its components. Scientific data are divided into three categories – research datasets, scientific and technical information (STI), and scientometric information (SMI) – which differ in structure, volume, update patterns, access profile, and metadata requirements, complicating their effective management within a single general-purpose store. Based on a data typology and use cases for the key roles (researcher, analyst, data engineer, administrator), requirements for the components are formulated. A comparative analysis of alternative solutions is performed for each component, and a modular architecture is proposed that separates sources of truth from derived representations. A consistent technology stack compatible with on-premises deployment is determined, along with cross-cutting mechanisms of identification, authorization, and resource management.
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References
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