Evolve with your research: stepwise system evolution from document-driven to fact-centric research data management in materials science

The digitalisation of research requires data management systems capable of supporting a broad spectrum of usage scenarios, ranging from document-oriented repositories to fully factographic environments. This paper introduces a methodological approach for the stepwise development of such systems, illustrated by the MatInf Research Data Management System (RDMS). The proposed framework combines a graph-based STAR paradigm-emphasising Statefulness, Traceability, Aim, and Result-with the SET methodology, which enables systematic Standardisation, Extraction, and Testing of research data. Together, these principles provide a pathway towards FAIR-compliant data infrastructures, facilitating reproducibility, re-use, and integration of heterogeneous materials science data. By demonstrating the gradual consolidation of research outputs into unified datasets, this study highlights how adaptive RDMS design can support accelerated scientific discovery and enhance collaborative research in large-scale projects.Scientific Contribution: This work develops a methodological framework for the progressive evolution of research data management systems in materials science, moving from document-oriented to graph-based and ultimately factographic approaches.

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Publication Details

Journal
Journal of Cheminformatics
Published
2026-03-17
DOI
https://doi.org/10.1186/s13321-026-01180-y
Primary Topic
Research Data Management Practices
Type
article
Field-Weighted Citation Impact
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article

Evolve with your research: stepwise system evolution from document-driven to fact-centric research data management in materials science

Alfred Ludwig, Victor Dudarev
Journal of Cheminformatics
Research Data Management Practices
article

Evolve with your research: stepwise system evolution from document-driven to fact-centric research data management in materials science

Alfred Ludwig, Victor Dudarev
article en

Abstract

The digitalisation of research requires data management systems capable of supporting a broad spectrum of usage scenarios, ranging from document-oriented repositories to fully factographic environments. This paper introduces a methodological approach for the stepwise development of such systems, illustrated by the MatInf Research Data Management System (RDMS). The proposed framework combines a graph-based STAR paradigm-emphasising Statefulness, Traceability, Aim, and Result-with the SET methodology, which enables systematic Standardisation, Extraction, and Testing of research data. Together, these principles provide a pathway towards FAIR-compliant data infrastructures, facilitating reproducibility, re-use, and integration of heterogeneous materials science data. By demonstrating the gradual consolidation of research outputs into unified datasets, this study highlights how adaptive RDMS design can support accelerated scientific discovery and enhance collaborative research in large-scale projects.Scientific Contribution: This work develops a methodological framework for the progressive evolution of research data management systems in materials science, moving from document-oriented to graph-based and ultimately factographic approaches.

Journal of Cheminformatics
University Hospitals of the Ruhr-University of Bochum (DE), Ruhr University Bochum (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 20%
Research Data Management Practices
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