Year: 2025
Type: article
Abstract: Modern scientific knowledge management systems increasingly demand methods capable of flexible modeling and dynamic analytics. This paper presents an approach to modeling for the needs of research knowledge base systems. The presented method integrates extensible XML-based data modeling with advanced analytical tools. The approach enables the structured definition of domain models characterized by hierarchical nesting, historical tracking, and semantic versioning. The presented analytical engine, based on this approach, uses XPath navigation to support dynamic pivot-table aggregations over complex, nested data. The underlying modeling is particularly useful for handling temporal data. It is suitable for broader contexts, resulting in flexible data structures, multi-version record management, interoperability with Linked Open Data (LOD) standards, and FAIR-compliant workflows. The results demonstrate that combining model-centric extensibility, semantic interoperability, and user-driven analytics provides a scalable and adaptable foundation for building information management systems across diverse institutional and organizational settings. A use case for a university knowledge database is presented, and acceptance of the system by users is discussed.
Source: Electronics
Language: English
Topic: Optics and Image Analysis
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $2,896
Funder: Politechnika Warszawska
OpenAlex ID: W4413816656