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--- wiki:basic_recommendations [2025/06/19 11:40] – [Basic FAIR Implementation Recommendations] dkottmeier
+++ wiki:basic_recommendations [2025/06/20 07:57] (current) – [Description] dkottmeier
@@ Line 6: / Line 6: @@
-[Status: Under development, Date: 2023-08-25, Version: 001]
+[Status: Under development, Date: 2025-06-19, Version: 001]
 ==== Motivation for this Recommendation: ====
@@ Line 61: / Line 61: @@
 It is recommended that coordinated efforts across the Helmholtz Association be undertaken to achieve the above-mentioned goals, with the implementation of a common set of **FAIR building blocks**. These building blocks are operational measures required to support the findability, accessibility, interoperability, and reusability of research data. They include:
-  * Common and agreed procedures to refer to shared entities and metadata values, particularly through the use of **metadata of persistent identifiers** (**PID**s), to reduce redundancy and improve consistency in referencing key entities such as people, organizations, instruments, and datasets (PID?).
+  * Common and agreed procedures to refer to shared entities and metadata values, particularly through the use of **metadata of persistent identifiers** (**PID**s), to reduce redundancy and improve consistency in referencing key entities such as people, organizations, instruments, and datasets (**rename to PID**?).
-  * Harmonized use of **Semantic Resources**, including controlled vocabularies and mapping tables, to standardize metadata element names and their meanings, reduce ambiguity, and ensure consistent interpretation across disciplines and systems (S).
+  * Harmonized use of **semantic resources**, including controlled vocabularies and mapping tables, to standardize metadata element names and their meanings, reduce ambiguity, and ensure consistent interpretation across disciplines and systems (**S**).
-  * Agreements on **Mandatory and Optional Metadata elements**, covering both domain-independent and domain-specific needs, to support accurate description, discovery, exchange, and reuse of data across infrastructures, user communities, and tools (M?).
+  * Agreements on **mandatory and optional metadata elements**, covering both domain-independent and domain-specific needs, to support accurate description, discovery, exchange, and reuse of data across infrastructures, user communities, and tools (**M**?).
-  * Common metadata or **Exchange Formats**, such as DataCite, DCAT, or ISO 19115, to ensure consistent structuring and exchange of metadata across systems (E)
+  * Common metadata or **exchange formats**, such as DataCite, DCAT, or ISO 19115, to ensure consistent structuring and exchange of metadata across systems (**E**)
-  * Common data **Exchange Containers**, such as FAIR Digital Objects or DataCrates, to enable machine-actionable reuse and portability (C).
+  * Common data **exchange containers**, such as FAIR Digital Objects or DataCrates, to enable machine-actionable reuse and portability (**C**).
-  * Common **Interfaces**, to provide standardized, open mechanisms for data and metadata access and harvesting (I).
+  * Common **interfaces**, to provide standardized, open mechanisms for data and metadata access and harvesting (**I**).
-  * Inclusion of **Provenance information**, capturing data origin, transformation steps, and responsible agents, to enable assessment of data reliability and reproducibility (P).
-  * Clear **License information**, using standardized, machine-readable licenses, to define conditions of use and promote legal clarity (L).
+**Other important topics** where harmonization procedures are important are:
-  * Documented procedures for assessing and communicating **Data Quality**, including uncertainty, validation, completeness, and versioning, to ensure data are fit for purpose (Q).
+  * Inclusion of **provenance information**, capturing data origin, transformation steps, and responsible agents, to enable assessment of data reliability and reproducibility (**P**).
-  * Clear definition of **Stakeholder Roles** and responsibilities, including who is accountable for metadata provision, data stewardship, infrastructure maintenance, and policy implementation (R).
+  * Clear **license information**, using standardized, machine-readable licenses, to define conditions of use and promote legal clarity (**L**).
-  * **Recognition** and credit for **research data management** (RDM) engagement, through citation of datasets with DOIs, inclusion of author contributions, and formal acknowledgment of data curation efforts (RDM).
+  * Documented procedures for assessing and communicating **data quality**, including uncertainty, validation, completeness, and versioning, to ensure data are fit for purpose (**Q**).
+  * Clear definition of **stakeholder roles** and responsibilities, including who is accountable for metadata provision, data stewardship, infrastructure maintenance, and policy implementation (**R**).
+  * **Valuating research data management** (RDM) engagement, through citation of datasets with DOIs, inclusion of author contributions, and formal acknowledgment of data curation efforts (**V**).
 These elements form the structural foundation for the detailed recommendations presented in this wiki.