Evolve with Your Research -- Stepwise System Evolution from Document-driven to Fact-centric Research Data Management in Materials Science

TL;DR

This paper presents a stepwise approach for evolving research data management systems in materials science, integrating document and fact-centric paradigms to enhance FAIR compliance, reproducibility, and collaboration.

Contribution

It introduces a novel framework combining the STAR paradigm and SET methodology for systematic development of adaptable, FAIR-compliant research data infrastructures.

Findings

Demonstrates gradual consolidation of research data into unified datasets.

Highlights improved reproducibility and data re-use in materials science.

Supports accelerated scientific discovery through adaptive system design.

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.