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License: CC BY
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https://dx.doi.org/10.34657/79...
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License: CC BY
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Ontology Modelling for Materials Science Experiments

Authors: Mehwish Alam; Henk Birkholz; Danilo Dessi; Christoph Eberl; Heike Fliegl; Peter Gumbsch.; Philipp von Hartrott; +4 Authors

Ontology Modelling for Materials Science Experiments

Abstract

Materials are either enabler or bottleneck for the vast majority of technological innovations. The digitization of materials and processes is mandatory to create live production environments which represent physical entities and their aggregations and thus allow to represent, share, and understand materials changes. However, a common standard formalization for materials knowledge in the form of taxonomies, ontologies, or knowledge graphs has not been achieved yet. This paper sketches the e_orts in modelling an ontology prototype to describe Materials Science experiments. It describes what is expected from the ontology by introducing a use case where a process chain driven by the ontology enables the curation and understanding of experiments.

Countries
Germany, Germany, Italy
Keywords

Technology, ddc:600, Materials Science, 600, Data curation; Materials science; Ontology design, 004, 620, info:eu-repo/classification/ddc/600, Ontology Design, Data Curation, Konferenzschrift

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green