Semantic orchestration and exploitation of material data: A dataspace solution demonstrated on steel and copper applications

TL;DR

This paper presents a semantic data management system called DSMS designed for materials science, enabling efficient integration, exploration, and sharing of heterogeneous data to support engineering decision-making and innovation.

Contribution

It introduces a novel semantic methodology and a comprehensive technology stack tailored for materials engineering data management, adhering to FAIR principles.

Findings

Demonstrated DSMS's applicability to steel and copper data processing tasks

Enabled improved data integration and knowledge extraction in materials science

Supported decision-making and design optimization through data sharing

Abstract

In materials science and manufacturing, vast amounts of heterogeneous data (e.g., measurement and simulation logs, process data, publications) serve as the bedrock of valuable knowledge for various engineering applications. However, efficiently storing and managing this diverse data poses challenges due to limited standardization and integration across different organizational units. Addressing these challenges is essential to fully unlock the potential of data-driven approaches. This paper introduces novel, comprehensive semantic methodology tailored to materials engineering and realized as a technology stack named Dataspace Management System (DSMS), which powers dataspace solutions that leverage the knowledge encoded in heterogeneous data sources to support data-driven insights and to derive new knowledge. At its core, DSMS offers a distinctive knowledge management approach tuned to meet the specific requirements of the materials science and manufacturing domain, all while adhering to the FAIR principles. DSMS provides functionalities for data integration, linkage, exploration, visualization, processing, data sharing, and services (e.g., consulting) to support engineers in decision-making, design and optimization. We present an architectural overview of DSMS, outlining its core concepts and their technological implementation, as well as demonstrate its applicability to common data-processing tasks through use cases from the StahlDigital and KupferDigital research projects within Germany's MaterialDigital initiative.