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-====== Preface ======
-About the FAIR Principles
-When "The FAIR Guiding Principles for Scientific Data Management and Stewardship" were initially published they addressed a very important aspect for the data management community: even though everyone in the RDM community knew, that the management of research data was important, it was very hard to communicate the goals and benefits to anyone outside the RDM teams. Data Managers faced a lot of backlash, because they had difficulties to properly explain why documantration of data was useful, how it was supposed to be organized, and what the additional value would be. At his point the FAIR guiding principles offered a relatively simpe narrative, describing the high level goals of RDM through four terms. The data should become Findable, Accessible, Interoperable and Reusable. The RDM community could very well identify themselves with these goals. In addition, four more concrete level principles (F1-4, A1-4, I1-4, R1-4) were listed, which outline particular practices aimed to achieve the higher level goals.
-What happened was, that the data mangers tailored their data infrastructuires and ecosystems to conform with the lower level goals.
-The FAIR Guiding Principles describe how research data and other digital objects should become Findable, Accessible, Interoperable, and Reusable. However, Wilkinson et al. make clear that FAIR is not a technical standard or an implementation specification. The principles define desired outcomes but do not prescribe particular metadata schemas, identifiers, formats, vocabularies, protocols, or software solutions.
-This flexibility allows FAIR to be applied across different disciplines, but it also creates limitations. Research communities must independently agree on suitable standards and apply them consistently. Without such coordination, two datasets may both be described as FAIR while still being technically or semantically incompatible. FAIRness is also gradual rather than binary: a resource may be highly findable but only weakly interoperable or reusable.
-Another limitation is that machine actionability exists on a continuum. Machines may locate and access data without being able to interpret their meaning, licence, provenance, or possible uses. Rich metadata alone therefore do not guarantee meaningful interoperability, particularly when communities use different terminologies.
-Finally, FAIR does not necessarily mean open. Restricted or sensitive data can still be FAIR when their metadata and access conditions are clearly described. The principles also do not directly assess scientific quality, ethical acceptability, long-term preservation, governance, or trustworthiness. Their practical success ultimately depends on shared community standards and coordinated implementation.
-The central limitation can therefore be summarized as follows: FAIR defines the properties that a well-managed digital research object should exhibit, but it does not provide the common standards or coordinated implementation required to produce those properties. Its practical success depends on research communities agreeing upon and consistently applying persistent identifiers, metadata schemas, semantic vocabularies, protocols, provenance practices, and licences.
 ====== Introduction ======
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 ===== The Character of This Wiki =====
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 /*Alternative: Metadata Management Recommendations and Best Practices*/
+/*
 In this Wiki, the HMC Hub Earth and Environment and its partners will **formulate recommendations** for such aligned practices for the community. We are making concrete suggestions for the implementation and support with practical suggestions for such procedures.
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 The resulting recommendations are consistently documented using the same guiding questions and a harmonized structure. Two perspectives must therefore be considered: on the one hand, the discussion and agreement on content; on the other, the administrative and technical implementation. Each individual step required for implementation must be examined. The perspectives and roles of the various stakeholders are taken into account to ensure that all influencing factors are considered in detail. In addition, the decision-making processes that lead to established procedures are outlined—both from the bottom up and from the top down.
-This provides a foundation for optimizing the procedures concerning the individuals involved, their responsibilities, and the necessary actions. In order for the FAIR approach to be successful, it is essential that identified stakeholders take on specific responsibilities.
+This provides a foundation for optimizing the procedures concerning the individuals involved, their responsibilities, and the necessary actions. In order for the FAIR approach to be successful, it is essential that identified stakeholders take on specific responsibilities. */
+=====  The Character of This Wiki =====
+This wiki serves as the collaborative working platform of the Helmholtz Metadata Collaboration (HMC) Hub Earth and Environment. It is conceived as a living resource that reflects the current perspectives, discussions, and activities of the Hub and its wider community. Its content is continuously refined as new requirements emerge, implementation experience is gained, and community agreements evolve.
+The wiki primarily supports the development, discussion, and documentation of concepts and recommendations. More formalized outcomes derived from this work are published through the central HMC website, the website of the HMC Hub Earth and Environment, or other appropriate publications and resources.
+=====  The Helmholtz Metadata Collaboration =====
+The Helmholtz Metadata Collaboration promotes the qualitative enrichment of research data through high-quality metadata and supports the implementation of this approach throughout the Helmholtz Association.
+HMC develops and implements concepts, services, and technologies for the sustainable management of research data. Its principal objective is to ensure that the breadth and depth of research data produced by the Helmholtz Centres can be discovered, accessed, interpreted, and reused by the wider scientific community in accordance with the **FAIR Guiding Principles**.[1] The objective of enabling FAIR research data across the Helmholtz Association is also reflected in the **Recommendations for Policies of the Helmholtz Centres on Research Data Management**.[2]
+Research data, metadata, information, and knowledge systems are created and maintained by a wide range of individuals, institutions, and stakeholder groups. The establishment of a harmonized, interoperable, and ultimately FAIR research data space therefore requires the alignment of practices, responsibilities, and technical processes across heterogeneous data infrastructures. Such alignment must be implemented not only within technical systems but also through the coordinated activities of the people and organizations responsible for producing, managing, curating, and providing access to research data.
+=====  The Content of This Wiki =====
+Within this wiki, the HMC Hub Earth and Environment and its partners formulate recommendations for the alignment of research data management practices across the Earth and Environment community. The wiki translates general objectives into concrete implementation guidance and provides practical support for the adoption of coordinated procedures.
+To advance FAIR research data across the diverse data infrastructures of the Helmholtz Research Field Earth and Environment, the Hub has developed the **Road-to-FAIR Strategy**. This strategy comprises a series of coordinated activities through which shared requirements are identified, discussed, and translated into implementable recommendations.
+As an initial step, existing data infrastructures and their interfaces are examined in order to identify established practices, recurring challenges, and approaches that may serve as transferable models. On this basis, relevant committees and stakeholder groups collaborate to define implementation measures for specific objectives. For each agreed Road-to-FAIR building block, concrete recommendations are developed and documented. These recommendations are presented in this wiki as part of a living handbook and are revised as technical environments, community practices, and institutional requirements evolve.
+To support consistency and transparency, all recommendations are documented according to a common structure and a shared set of guiding questions. Their development must take account of two complementary perspectives: first, the substantive discussion and community agreement concerning the intended outcome; and second, the administrative, organizational, and technical measures required for implementation.
+Each step necessary for implementation must therefore be examined individually. The perspectives, responsibilities, and requirements of the relevant stakeholder groups are considered in order to identify dependencies and influencing factors. The processes through which procedures are discussed, agreed upon, and established are also documented, including both bottom-up processes originating within communities and infrastructures and top-down processes arising from institutional strategies and policies.
+This approach provides a basis for clarifying and improving procedures, responsibilities, and required actions. The successful implementation of FAIR practices ultimately depends on the active participation of the identified stakeholders and on their willingness and ability to assume clearly defined responsibilities.
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 For questions, comments and suggestions, please write to [[hmc-hub-ee@geomar.de|hmc-hub_ee@geomar.de]].
+====== References ======
+[1] Wilkinson, M. D. et al. The FAIR Guiding Principles for scientific data management and stewardship. Sci. Data 3:160018 doi: 10.1038/sdata.2016.18 (2016)
+[2] Empfehlungen für Richtlinien der Helmholtz-Zentren zum Umgang mit Forschungsdaten, 2019, Helmholtz Open Science, https://os.helmholtz.de/open-research-data/forschungsdaten-policies/ doi: doi.org/10.2312/os.helmholtz.002