Concepts for a Semantically Accessible Materials Data Space: Overview over Specific Implementations in Materials Science

This article describes advancements in the ongoing digital transformation in materials science and engineering. It is driven by domain‐specific successes and the development of specialized digital data spaces. There is an evident and increasing need for standardization across various subdomains to support science data exchange across entities. The MaterialDigital Initiative, funded by the German Federal Ministry of Education and Research, takes on a key role in this context, fostering collaborative efforts to establish a unified materials data space. The implementation of digital workflows and Semantic Web technologies, such as ontologies and knowledge graphs, facilitates the semantic integration of heterogeneous data and tools at multiple scales. Central to this effort is the prototyping of a knowledge graph that employs application ontologies tailored to specific data domains, thereby enhancing semantic interoperability. The collaborative approach of the Initiative's community provides significant support infrastructure for understanding and implementing standardized data structures, enhancing the efficiency of data‐driven processes in materials development and discovery. Insights and methodologies developed via the MaterialDigital Initiative emphasize the transformative potential of ontology‐based approaches in materials science, paving the way toward simplified integration into a unified, consolidated data space of high value.

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Publication Details

Journal
Advanced Engineering Materials
Published
2024-12-18
DOI
https://doi.org/10.1002/adem.202401092
Citations
5
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
0.59

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Concepts for a Semantically Accessible Materials Data Space: Overview over Specific Implementations in Materials Science

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Concepts for a Semantically Accessible Materials Data Space: Overview over Specific Implementations in Materials Science

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article en
5 citations

Abstract

This article describes advancements in the ongoing digital transformation in materials science and engineering. It is driven by domain‐specific successes and the development of specialized digital data spaces. There is an evident and increasing need for standardization across various subdomains to support science data exchange across entities. The MaterialDigital Initiative, funded by the German Federal Ministry of Education and Research, takes on a key role in this context, fostering collaborative efforts to establish a unified materials data space. The implementation of digital workflows and Semantic Web technologies, such as ontologies and knowledge graphs, facilitates the semantic integration of heterogeneous data and tools at multiple scales. Central to this effort is the prototyping of a knowledge graph that employs application ontologies tailored to specific data domains, thereby enhancing semantic interoperability. The collaborative approach of the Initiative's community provides significant support infrastructure for understanding and implementing standardized data structures, enhancing the efficiency of data‐driven processes in materials development and discovery. Insights and methodologies developed via the MaterialDigital Initiative emphasize the transformative potential of ontology‐based approaches in materials science, paving the way toward simplified integration into a unified, consolidated data space of high value.

Advanced Engineering MaterialsVol. 27(8)
Karlsruhe Institute of Technology (DE), Federal Institute For Materials Research and Testing (DE), FIZ Karlsruhe – Leibniz Institute for Information Infrastructure (DE), Universität Hamburg (DE), Schott (Germany) (DE), University of Bremen (DE), University of Oslo (NO), Bielefeld University (DE), Technische Informationsbibliothek (TIB) (DE), Leibniz-Institute for New Materials (DE), AWS-Institute for Digitized Products and Processes (DE), Max-Planck-Institut für Nachhaltige Materialien (DE), Leibniz-Institut für Werkstofforientierte Technologien - IWT (DE), Institut für Angewandte Trainingswissenschaft (DE), Fraunhofer Institute for Mechanics of Materials (DE), Fraunhofer Institute for Applied and Integrated Security (DE), Hochschule Aalen (DE), Fraunhofer Institute for Casting, Composite and Processing Technology IGCV (DE), Technische Universität Berlin (DE), Friedrich Schiller University Jena (DE), Deggendorf Institute of Technology (DE), Hamburg University of Technology (DE), Saarland University (DE), University of Lübeck (DE)
Bundesministerium für Bildung und Forschung, Max-Planck-Institut für Eisenforschung
Industry, innovation and infrastructure
Openalex Percentile: Top 32%
Machine Learning in Materials Science
0.59
DOIOpen Access PDFOpenAlex
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