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Knowledge graphs in BERD and in NFDI

descriptionPublicationkeyboard_double_arrow_right Presentation , Other literature type , Conference object 01 Jan 2022 Germany Publisher:Zenodo
Authors: Shigapov, Renat;

doi: 10.5281/zenodo.7373258 , 10.5281/zenodo.7373257

Knowledge graphs in BERD and in NFDI

Abstract

Knowledge graphs are able to capture, enrich and disseminate research data objects so that the FAIR and Linked Data principles are fulfilled. How knowledge graphs can improve the domain-specific (BERD) and cross-domain (NFDI) research data infrastructures? The answer is based on the use cases in BERD@NFDI and on activities of the NFDI working group “Knowledge graphs”. First, we describe the architecture, knowledge graphs and use cases in BERD@NFDI. Then, we present the NFDI working group “Knowledge Graphs”, its work plan and potential base services.

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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!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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