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To be sustainable and useful, scientific data should be FAIR. These goals can only be achieved by definition and adoption of metadata standards and implementation of tools and services that support these standards. Unfortunately, the diversity of needs with respect to scientific (meta)data leads to a large gap between the scope and pace of large-scale standardization efforts and the day-to-day work of domain researchers. This poster gives an overview of Metador - a metadata-centered framework emphasizing the I and R in FAIR. With Metador we try to address these issues using an incremental, bottom-up approach. It is based on a lightweight technical meta-standard for packaging JSON-serialized metadata objects alongside the research data in archives, a simple API implementing this standard, and a plugin-based metadata schema system. On top of this, it provides automatic generation of dashboards for compatible data archives that can be embedded in different settings. To showcase the versatility of the framework, we recently implemented the dashboard functionality of Metador as a general-purpose InvenioRDM extension. In future work, we plan to extend this integration to enable improved metadata-driven search capabilities, powered by the dynamic Metador metadata schema system, as well as integrating use cases demonstrating how the framework can be applied to satisfy concrete metadata needs for research data handling.
{"references": ["https://github.com/Materials-Data-Science-and-Informatics/metador-core"]}
framework, metadata, FAIR, Python
framework, metadata, FAIR, Python
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| 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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