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wiki:s0 [2025/07/07 10:08] – [3. Consideration of the advantages and disadvantages of implementing the recommendation] dkottmeierwiki:s0 [2025/08/01 12:57] (current) – [Contributors] esoeding
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 =====Description===== =====Description=====
  
-Status: Under development, Date: 2025/05/07 10:18, Version: 001+Status: Under development, Date: 2025/07/07 10:18, Version: 001
  
 =====Motivation for this Recommendation ===== =====Motivation for this Recommendation =====
 The use of shared, community-endorsed vocabularies for metadata annotation is key to ensuring unambiguous and standardized descriptions of data. This not only supports the alignment and integration of heterogeneous datasets but also enhances data discovery and reuse. Crucially, such practices form the foundation for machine-readability of metadata, which is essential for achieving semantic interoperability. The use of shared, community-endorsed vocabularies for metadata annotation is key to ensuring unambiguous and standardized descriptions of data. This not only supports the alignment and integration of heterogeneous datasets but also enhances data discovery and reuse. Crucially, such practices form the foundation for machine-readability of metadata, which is essential for achieving semantic interoperability.
- 
-The basis for a comprehensive metadata annotation is the is that data is provided with sufficient and structured metadata and that there is agreement about which metadata is considered essential in communities. Standardized metadata categories and structures enable machines to interpret and connect data across disciplinary and institutional boundaries. 
  
 Within the Helmholtz research field Earth and Environment, there is a growing need for consistent approaches to metadata annotation that ensure semantic interoperability. This recommendation aims to address that need by guiding the selection and prioritization of controlled vocabularies and by supporting the optimization of metadata annotation workflows.  Within the Helmholtz research field Earth and Environment, there is a growing need for consistent approaches to metadata annotation that ensure semantic interoperability. This recommendation aims to address that need by guiding the selection and prioritization of controlled vocabularies and by supporting the optimization of metadata annotation workflows. 
  
-=====Recommendation ====+=====Recommendation summary ====
 Data infrastructures and data hosts—such as data repositories, sensor registries, electronic lab notebooks, or other platforms that store and make data available—should ensure the annotation of the vast majority of metadata using standardized terms from established and, where appropriate, FAIR-compliant controlled vocabularies (e.g., lists, thesauruses, taxonomies, standardized terminologies, or, ideally, ontologies) to promote semantic consistency, clarity, and interoperability. Data platforms such as data portals or knowledge graphs should incorporate these terms into their tools and reuse them for standardized representation and improved search. Data infrastructures and data hosts—such as data repositories, sensor registries, electronic lab notebooks, or other platforms that store and make data available—should ensure the annotation of the vast majority of metadata using standardized terms from established and, where appropriate, FAIR-compliant controlled vocabularies (e.g., lists, thesauruses, taxonomies, standardized terminologies, or, ideally, ontologies) to promote semantic consistency, clarity, and interoperability. Data platforms such as data portals or knowledge graphs should incorporate these terms into their tools and reuse them for standardized representation and improved search.
 +
 +/*Kommentar Doro: eigentlich sprechen wir auch die Entwickler oder "Ausfüller" von PIDs an*/
 =====Binding Convention ===== =====Binding Convention =====
  
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 =====Precondition for Implementation ===== =====Precondition for Implementation =====
-The basis for a comprehensive metadata annotation is the is that data is provided with sufficient and structured metadata and that there is agreement about which metadata is considered essential in communities. Metadata annotation with semantic ressources is only effective if there is consensus within a research community about which controlled vocabularies or other semantic resources best meet the community's needs, and if these resources have clear governance, provenance, and documentation. Furthermore, they should be available and maintained over the long term (at least 5 years) and cover the vast majority of requirements.+The basis for a comprehensive metadata annotation is that the data is provided with sufficient and structured metadata and that there is agreement about which metadata is considered essential in communities. Standardized metadata categories and structures enable the annotation with identifiable terms from recognized controlled vocabularies, which allows machines to interpret and connect data across disciplinary and institutional boundaries.
  
 +Metadata annotation with semantic ressources is only effective if there is consensus within a research community about which controlled vocabularies or other semantic resources best meet the community's needs, and if these resources have clear governance, provenance, and documentation. Furthermore, they should be available and maintained over the long term (at least 5 years) and cover the vast majority of requirements.
 =====Contributors===== =====Contributors=====
  
 +Dorothee Kottmeier (Lead)
  
 =====Content===== =====Content=====
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 ====4. The Recommendation==== ====4. The Recommendation====
  
-Data infrastructures should ensure the annotation of the large majority of metadata using standardized terms within metadata systems — such as data repositories, sensor registries, electronic lab notebooks, or other platforms that manage or reference data, including descriptions of files stored outside formal repositories — at the time of metadata creation or management, by applying terms from established and, where applicable, FAIR-compliant controlled vocabularies (e.g., ontologies, taxonomies, or standardized terminologies) to promote semantic consistency, clarity, and interoperability.+Data stewards, archivists, and tool developers—including those responsible for systems used at various stages of the data lifecycle, such as data acquisition, processing, documentation, and storage—should ensure that metadata is captured in a structured and standardized manner, using harmonized metadata schemas aligned with community standards. This includes platforms such as electronic lab notebooks, archiving tools, sensor registries, and other software environments that support data generation, transformation, or submission. Metadata must be consistently annotated with well-governed controlled vocabularies to guarantee semantic clarity, interoperability, and long-term reusability across diverse data infrastructures. Providing clear documentation of the vocabularies and semantic resources in use, alongside transparent, user-friendly annotation workflows, supports consistent metadata quality and facilitates semantic integration. 
 + 
 +Developers of data portals, knowledge graphs, and discovery tools should incorporate these controlled vocabularies and ontologies into their software environments. This enhances machine-readability, promotes semantic consistency across systems, and enables users to efficiently search, filter, and combine data from multiple sources. 
 + 
 +To enable seamless semantic annotation from the start, data producers need to be supported through targeted training and awareness initiatives that emphasize the use of community-endorsed vocabularies, structured metadata practices, and annotation best practices. Transparent user guidance and easily accessible documentation of recommended semantic resources are essential to ensure metadata quality and simplify the semantic linkage of data throughout its lifecycle.
  
 ====5. Naming of communities that have already implemented the recommendation==== ====5. Naming of communities that have already implemented the recommendation====
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 ===References=== ===References===
 +
 +- Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., ... & Mons, B. (2016). [The FAIR Guiding Principles for scientific data management and stewardship](https://doi.org/10.1038/sdata.2016.18). *Scientific Data*, 3, 160018. https://doi.org/10.1038/sdata.2016.18
 +
 +- Le Franc, Y., Hettne, K., & Ó Carragáin, E. (2019). *D2.5 FAIR Semantics Recommendations Second Iteration*. Zenodo. https://doi.org/10.5281/zenodo.4314321
 +
  
 ===Relevant Community Recommendations=== ===Relevant Community Recommendations===
wiki/s0.1751882887.txt.gz · Last modified: by dkottmeier