~/talk

Metrics in Context: A Data Specification For Scholarly Metrics

Talkat FOSDEM 2021 · on Saturday, 2021-02-06· at 17:30· D.research· [data-engineering, open-source]

speaker

name:Asura Enkhbayar
links:none on file

resources

video:https://video.fosdem.org/2021/D.research/open_research_scholarly_metrics.mp4
slides:https://fosdem.org/2021/schedule/event/open_research_scholarly_metrics/attachments/slides/4530/export/events/attachments/open_research_scholarly_metrics/slides/4530/metrics_in_context_slides

summary

Describes the need for a standard way to record provenance and processing for scholarly metrics produced by providers like Google Scholar, Web of Science, Scopus, Dimensions, Crossref and Scite.ai, covering citations and altmetrics such as Tweets and Facebook shares. Presents an early prototype called Metrics in Context implemented as a Frictionless Data specification, arguing for attention to the tracing and patterning processes that create metrics used in hiring, promotion and funding decisions.

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