Results 231 to 240 of about 1,551,832 (303)

Semantic Orchestration and Exploitation of Material Data: A Dataspace Solution Demonstrated on Steel and Copper Applications

open access: yesAdvanced Engineering Materials, EarlyView.
This article introduces the Dataspace Management System (DSMS), a methodological framework realized in software, designed as a technology stack to power dataspaces with a focus on advanced knowledge management in materials science and manufacturing. DSMS leverages heterogeneous data through semantic integration, linkage, and visualization, aligned with
Yoav Nahshon   +7 more
wiley   +1 more source

Seamless Science: Lifting Experimental Mechanical Testing Lab Data to an Interoperable Semantic Representation

open access: yesAdvanced Engineering Materials, EarlyView.
In pursuit of modern data management techniques, this study presents an in‐lab pipeline combining electronic laboratory notebooks (eLabFTW) and Python scripts for creating semantically enriched, interoperable, machine‐actionable data. Automating data mapping enhances usability, collaboration, and unified knowledge representation.
Markus Schilling   +7 more
wiley   +1 more source

Ontologies for FAIR Data in Additive Manufacturing: A Use Case‐Based Evaluation

open access: yesAdvanced Engineering Materials, EarlyView.
An ontology‐based approach for generating findable, accessible, interoperable, reusable data in additive manufacturing is explored, focusing on powder bed fusion. The article highlights the benefits of enhanced data findability and digital twin enablement, while addressing challenges like data integration complexity and the need for specialized ...
Thomas Bjarsch   +2 more
wiley   +1 more source

Performance Evaluation of Upper‐Level Ontologies in Developing Materials Science Ontologies and Knowledge Graphs

open access: yesAdvanced Engineering Materials, EarlyView.
This article provides examples of ontology development in the materials science domain (use‐case of Brinell hardness testing) and gives ontology developers an overview for selecting their desired top‐level ontologies (e.g., BFO, EMMO, PROVO) by considering different evaluation parameters like semantic richness, domain coverage, extensibility ...
Hossein Beygi Nasrabadi   +3 more
wiley   +1 more source

Editorial: The diagnoses of glaucoma in the era of artificial intelligence. [PDF]

open access: yesFront Ophthalmol (Lausanne)
AlRyalat SA, Al Bdour M, Jammal HM.
europepmc   +1 more source

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