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A central mission of HMC is to support the data producers of the Helmholtz community in making their data FAIR. Developing a sustainable strategy for doing so requires a detailed understanding of community-specific practices, strengths, and limitations related to the application of each FAIR data guideline. We have applied the FAIR Data Maturity Model, developed by the respective RDA working group, to a prototypical data pipeline in the research field Matter. In our poster presentation, we would like to provide an overview of our approach and discuss the lessons learned that helped us identify key activities for meeting community needs.
FAIR Data Maturity Model, FAIR Assessment, Helmholtz Metadata Collaboration
FAIR Data Maturity Model, FAIR Assessment, Helmholtz Metadata Collaboration
| 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 |
| views | 9 | |
| downloads | 7 |

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