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 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. 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].+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 Road-to-FAIR Strategy provides the framework through which these technical, organizational, and procedural aspects can be coordinated and translated into actionable recommendations. 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 Road-to-FAIR Strategy provides the framework through which these technical, organizational, and procedural aspects can be coordinated and translated into actionable recommendations.
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 Within this wiki, the HMC Hub Earth and Environment and its partners from the Helmholtz DataHub Earth and Environment formulate recommendations aligning research data management practices across the Earth and Environment community. The wiki translates general objectives into concrete implementation guidance and documents the recommendations developed through the Road-to-FAIR Strategy. Within this wiki, the HMC Hub Earth and Environment and its partners from the Helmholtz DataHub Earth and Environment formulate recommendations aligning research data management practices across the Earth and Environment community. The wiki translates general objectives into concrete implementation guidance and documents the recommendations developed through the Road-to-FAIR Strategy.
  
-The Road-to-FAIR Strategy provides the overarching framework for identifying shared requirements, developing implementation measures, and coordinating their adoption across heterogeneous infrastructures. Its structure and individual components are described in the dedicated Road-to-FAIR Strategy chapter.+The [[wiki:1_road-to-fair-strategy:|Road-to-FAIR Strategy]] provides the overarching framework for identifying shared requirements, developing implementation measures, and coordinating their adoption across heterogeneous infrastructures. Its structure and individual components are described in the dedicated Road-to-FAIR Strategy chapter.
  
 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. 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.
start.1787143165.txt.gz · Last modified: by dkottmeier