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--- wiki:m2.2 [2025/05/26 09:26] – [Motivation for this Recommendation:] esoeding
+++ wiki:m2.2 [2025/05/26 09:28] (current) – [1. Explanation of the Background and Benefits of the Recommendation] esoeding
@@ Line 8: / Line 8: @@
 =====Motivation for this Recommendation: =====
+Implementing ROR in metadata workflows helps data stewards, repository maintainers, and developers ensure cleaner, more consistent, and machine-actionable organizational references. It eliminates ambiguity caused by name variants, manual entry errors, and institutional restructuring, reducing the curation burden and improving data quality at scale. For maintainers and developers, integrating ROR enables easier linking and interoperability with external systems (e.g., ORCID, DataCite, Crossref), supports automated harvesting and reporting, and simplifies downstream integration with analytics and discovery services. Using ROR as the authoritative source ensures that organizational metadata stays up to date without requiring manual oversight. Moreover, contributing to the accuracy of ROR records fosters a more reliable global research infrastructure ecosystem—benefiting the entire community and reducing duplicated efforts across systems.
 =====Recommendation ====
 It is recommended that data infrastructures (data repositories, data bases) should:
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 __Motivation__
-Using ROR identifiers in data infrastructures ensures that references to research organizations are unambiguous, persistent, and globally interoperable. By recording RORs alongside organizational metadata for datasets, publications, instruments, and related entities, infrastructures enhance metadata quality, enable reliable cross-linking across systems, and support automated discovery and aggregation. Treating ROR metadata as the authoritative source helps maintain consistency and reduces manual errors or duplication in institutional references. Additionally, engaging with the ROR ecosystem—by notifying it of suspected inaccuracies—contributes to improving the global research information landscape. Adopting ROR strengthens the visibility and traceability of research outputs, aligns infrastructures with FAIR and open science principles, and facilitates seamless integration with external services such as ORCID, DataCite, and Crossref.
+Implementing ROR in metadata workflows helps data stewards, repository maintainers, and developers ensure cleaner, more consistent, and machine-actionable organizational references. It eliminates ambiguity caused by name variants, manual entry errors, and institutional restructuring, reducing the curation burden and improving data quality at scale. For maintainers and developers, integrating ROR enables easier linking and interoperability with external systems (e.g., ORCID, DataCite, Crossref), supports automated harvesting and reporting, and simplifies downstream integration with analytics and discovery services. Using ROR as the authoritative source ensures that organizational metadata stays up to date without requiring manual oversight. Moreover, contributing to the accuracy of ROR records fosters a more reliable global research infrastructure ecosystem—benefiting the entire community and reducing duplicated efforts across systems.
 ====2. Possible alternative solutions====