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 …
science and engineering. It is driven by domain‐specific successes and the development of …
[HTML][HTML] Toward a digital materials mechanical testing lab
To accelerate the growth of Industry 4.0 technologies, the digitalization of mechanical testing
laboratories as one of the main data-driven units of materials processing industries is …
laboratories as one of the main data-driven units of materials processing industries is …
Metadata stewardship in nanosafety research: learning from the past, preparing for an “on-the-fly” FAIR future
Introduction: Significant progress has been made in terms of best practice in research data
management for nanosafety. Some of the underlying approaches to date are, however …
management for nanosafety. Some of the underlying approaches to date are, however …
Materials characterisation and software tools as key enablers in Industry 5.0 and wider acceptance of new methods and products
Abstract Recently, the NMBP-35 Horizon 2020 projects-NanoMECommons, CHARISMA,
and Easi-stress-organised a collaborative workshop to increase awareness of their …
and Easi-stress-organised a collaborative workshop to increase awareness of their …
The landscape of ontologies in materials science and engineering: A survey and evaluation
Ontologies are widely used in materials science to describe experiments, processes,
material properties, and experimental and computational workflows. Numerous online …
material properties, and experimental and computational workflows. Numerous online …
Review and Alignment of Domain-Level Ontologies for Materials Science
The growing complexity and interdisciplinary nature of Materials Science research demand
efficient data management and exchange through structured knowledge representation …
efficient data management and exchange through structured knowledge representation …
European standardization efforts from FAIR toward explainable-AI-ready data documentation in materials modelling
Security critical AI applications require a standardized and interoperable data and metadata
documentation that makes the source data explainable-AI ready (XAIR). Within the domain …
documentation that makes the source data explainable-AI ready (XAIR). Within the domain …
[HTML][HTML] Battery testing ontology: An EMMO-based semantic framework for representing knowledge in battery testing and battery quality control
The demand for advanced battery management systems (BMSs) and battery test procedures
is growing due to the rising importance of electric vehicles (EVs) and energy storage …
is growing due to the rising importance of electric vehicles (EVs) and energy storage …
Modeling experts, knowledge providers and expertise in Materials Modeling: MAEO as an application ontology of EMMO's ecosystem
This work presents the MarketPlace Agent and Expert Ontology (MAEO), an ontology for
modeling experts, expertise, and more broadly, knowledge providers and knowledge …
modeling experts, expertise, and more broadly, knowledge providers and knowledge …
Scope of physics-based simulation artefacts
Data and metadata documentation requirements for explainable-AI-ready (XAIR) models
and data in physics-based simulation technology are discussed by analysing different …
and data in physics-based simulation technology are discussed by analysing different …