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--- wiki:2_fair-building-blocks:1_semantic:start [2026/09/18 12:08] – [1. Explanation of the Background and Benefits of the Recommendation] dkottmeier
+++ wiki:2_fair-building-blocks:1_semantic:start [2026/09/18 12:10] (current) – [4. The Recommendation] dkottmeier
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 ====4. The Recommendation====
-Data stewards, archivists, and tool developers—including those responsible for systems used at various stages of the data lifecycle, such as data acquisition, processing, documentation, and storage—should ensure that metadata is captured in a structured and standardized manner, using harmonized metadata schemas aligned with community standards. This includes platforms such as electronic lab notebooks, archiving tools, sensor registries, and other software environments that support data generation, transformation, or submission. Metadata must be consistently annotated with well-governed controlled vocabularies to guarantee semantic clarity, interoperability, and long-term reusability across diverse data infrastructures. Providing clear documentation of the vocabularies and semantic resources in use, alongside transparent, user-friendly annotation workflows, supports consistent metadata quality and facilitates semantic integration.
+Data stewards, archivists, and tool developers — including those responsible for systems used at various stages of the data lifecycle, such as data acquisition, processing, documentation, and storage — should ensure that metadata is captured in a structured and standardized manner. Metadata must be consistently annotated with well-governed controlled vocabularies to guarantee semantic clarity, interoperability, and long-term reusability across diverse data infrastructures. Providing clear documentation of the vocabularies and semantic resources in use, alongside transparent, user-friendly annotation workflows, supports consistent metadata quality and facilitates semantic integration.
 Developers of data portals, knowledge graphs, and discovery tools should incorporate these controlled vocabularies and ontologies into their software environments. This enhances machine-readability, promotes semantic consistency across systems, and enables users to efficiently search, filter, and combine data from multiple sources.