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--- wiki:1_fair-building-blocks:start [2025/12/15 14:35] – created - external edit 127.0.0.1
+++ wiki:1_fair-building-blocks:start [2026/03/19 11:09] (current) – dkottmeier
@@ Line 3: / Line 3: @@
 ==== Definition ====
-It is recommended that coordinated efforts across the Helmholtz Association be undertaken to achieve the goals, as defined in the HMC vision and mission. This is done by the **Road-toFAIR-Strategy**, which calls for 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:
+The [[..:0_vision-and-mission:start|Mission and vision]] of the HMC Hub Earth and Environment is realized by the **Road-to-FAIR-Strategy**. To do so, we suggest implementing 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.
-  * Common and agreed procedures to refer to shared entities and metadata values, particularly through the use of **metadata of persistent identifiers** (PID), to reduce redundancy and improve consistency in referencing key entities such as people, organizations, instruments, and datasets (**K**) //(AP: suggestion for key)//.
+In our experience, the aspects Findability and Accessibility are relatively well supported by existing technical solutions in Earth and Environment. Therefore, our building blocks focus particularly on interoperability and reusability.
-  * 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**). //[I would still recommend to merge semantics with mandatory and optional metadata elements, because these are closely related. Mingeling woth semantics only makes sense with very important information, which should be defined beforehand and applied accordingly.]//
-  * 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**?). //[I don't think this is possible. If the PIDs are managed well, these are the mandatory information. Everything else is domain specific, can not be mandatory, and but must be dealt on a disciplinary case by case basis.]//
-  * Common metadata or **exchange formats**, such as DataCite, DCAT, or ISO 19115, to ensure consistent structuring and exchange of metadata across systems (**E**) //[I still recommend to merge fromats witrh interfaces as the topic interface. This should indeed cover formats and protocols, that we need agreements about]//
-  * 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**).
-//[In general I dont want more than four building blocks, because otherwise it will be too many to easily remember. The blocks need to be very easy to grasp, so people have trhenm in their mind all the time. That's actually one of the strenghts of FAIR.]//
+Building blocks that mainly address **Interoperability** are:
+  * Common and agreed procedures to refer to systematically described entities through the use of **persistent identifiers** (PIDs), to reduce redundancy, enrich context and improve consistency in referencing instances such as people, organizations, instruments, and datasets.
+  * Common understanding across systems and disciplines through the use of **semantic resources** to standardize metadata element names and reduce ambiguity.
+  * Common methods to structure data through the application of **interfaces, protocols, exchange formats, and schemas**, to ensure consistent structuring and exchange of metadata across systems.
+  * Common handling of data dissimination through **exchange containers** such as FAIR Digital Objects or DataCrates, to enable machine-actionable reuse and portability.
-**Other important topics** where harmonization procedures are important are:
+The following building blocks mainly address **Reusability**:
-  * Inclusion of **provenance information**, capturing data origin, transformation steps, and responsible agents, to enable assessment of data reliability and reproducibility (**P**).
+  * Inclusion of **provenance information**, capturing data origin, transformation steps, and responsible agents, to disclose lineage, and enable assessment of data reliability and reproducibility.
-  * Clear **license information**, using standardized, machine-readable licenses, to define conditions of use and promote legal clarity (**L**).
+  * Standardized procedures for documenting and assessing **data quality**, including uncertainty, validation, completeness, and versioning, to establish a basis for data trust and ensure data are fit for purpose.
-  * 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 **access and use constraints** using standardized and machine-readable methods, e.g. common licenses, to promote legal clarity.
-  * 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**).
+/* Um weitere Themen erweitern, wie "AI", "Wo Daten veröffentlichen", "Visualisierung des Kontents von Metadaten - z.B. als Autor auch den Autoren zeigen/Anzeige der Zitationen", Empfehlungen zu Findability (Stichwort R3data, Schema.org) und Accesibility, AI readiness */
 These elements form the structural foundation for the detailed recommendations presented in this wiki.
-A key precondition for the implementation of these recommendations is the availability of skilled personnel, such as data stewards, data curators, and developers, who support data management and the technical and semantic infrastructure required to implement FAIR.
+A key precondition for the implementation of these recommendations is the availability of skilled personnel, such as data stewards, data curators, and developers, who support data management and the technical and semantic infrastructure required to implement FAIR. /* **Valuating research data management** (RDM) engagement, through citation of datasets with DOIs, inclusion of author contributions, and formal acknowledgment of data curation efforts.*/
+/*   ==== Suggested Disciplinary Metadata Fields: ====
+Instrument used for the measurement
+  * method of the measurement
+  * measured attribute
+  * measured parameter
+  * measured unit
+  * measured Object / Medium
+  * sampleID
+  * region where the sample was obtained
+*/