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Webinar page: https://www.fairsfair.eu/events/persistence-and-interoperability-fair-research-data-management The main principles of FAIR data (findable, accessible, interoperable and reusable) have received wide acceptance in scientific data management circles. The work of further defining these principles and applying them in day-to-day knowledge sharing is ongoing. The FAIRsFAIR working group "FAIR practices: semantics, interoperability and services" recently published the first iteration of three annual reports on the state of FAIR in European scientific data. Based on studies of public information, especially EOSC infrastructure efforts, and on limited surveying and interviews, the report reviews and documents commonalities between infrastructures and obstacles to semantic interoperability - that is the use of metadata and persistent identifiers to enhance dissemination across infrastructures.
| 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). | 0 | |
| 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. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
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