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--- wiki:s1.0 [2025/08/27 12:27] – dkottmeier
+++ wiki:s1.0 [2025/09/01 11:47] (current) – [Motivation for this Recommendation:] dkottmeier
@@ Line 1: / Line 1: @@
-**Recommendation S1.0 **
+**Recommendation **
-======Recommendation to enrich data with rich metadata======
+======Recommendation to decompose metadata according to community-recognized frameworks======
 =====Description=====
-Status: Under development, Date: 2025/07/08 10:18, Version: 001
+Status: Under development, Date: 2025/07/07 10:18, Version: 001
 =====Motivation for this Recommendation: =====
-As data can only be embedded in semantic frameworks when it is described with rich metadata, the first step toward a standardized approach for implementing semantic resources is for data producers to enrich data with metadata, and as part of this for data producers or given communities to agree on which metadata should be provided by data producers and required by data infrastructures. Only the standardized use of metadata enable annotation with identifiable terms from recognized controlled vocabularies, which allows machines to interpret and connect data across disciplinary and institutional boundaries. Since the needs for these metadata can vary greatly between research communities, data infrastructures, and use cases, we recommend using existing metadata schemas commonly used in the respective communities, data infrastructures, and use cases as a guide. Below, we will list just a few of the many possible ones. In addition, there are generally applicable schemas that can be recommended.
+Many metadata elements, e.g., a measured quantities or methods, are complex, meaning they combine terms from different categories into a single compound concept. In other words, they consist of multiple metadata components drawn from different categories.
-=====Recommendation summary====
+For example, the variable air temperature (°C) does not only specify the measured quantity (temperature) but also includes additional components: the measurement context (air) and the unit (°C).
-All data producers in Helmholtz Earth & Environment should enrich their datasets with rich, standardized metadata at the time of dataset creation, submission to repositories or publication. This should be done following metadata categories specified in established general or discipline-specific metadata schemas or workflows (see also I2.0 Define exchange format).
+Because most metadata elements leave room for interpretation regarding which information they should capture, it is crucial to establish binding standards. Such standards must clearly define which components belong to a given metadata element.
+The individual components of a metadata element can either be stored in separate fields or, alternatively, combined into a single text string within one field, following a community-agreed syntax.
+=====Recommendation ====
+[shortened from below]
+[Format: Wer! macht was! wo! wann! unter welchen Voraussetzungen!]
 =====Binding Convention: =====
@@ Line 18: / Line 25: @@
 ^                         ^ mandatory  ^ conditional	          ^ optional ^
-^ Helmholtz FAIR Principle|     x       |      |          |
+^ Helmholtz FAIR Principle|            |      |          |
 =====Precondition for Implementation: =====
@@ Line 24: / Line 31: @@
 =====Related Recommendations =====
-Parent: S0
+Parent:
-Dependent: S3.0
+Dependent:
-Other: related to I2.0
+Other: none
 =====Contributors=====
+Names of contributors to this recommendation
 =====Content=====
@@ Line 39: / Line 47: @@
 __About__
-A metadata schema defines the structure, content, and semantics of metadata elements used to describe a dataset. It specifies what metadata should be captured, how it should be named, and in which format it should be stored. Schemas often include controlled vocabularies and formal structures, allowing metadata to be understood both by humans and machines. Widely used schemas include ISO 19115 for geospatial data, DataCite Metadata Schema for citation metadata, and Dublin Core for general resource description.
+__History and structure__
-__History__
+__Current Use of ...__
-__Current Use of Metadata Standards in Earth & Environmental Sciences__
-Across Helmholtz Earth and Environmental sciences, metadata standards are applied in diverse repositories and infrastructures, to name just a few of them:
-  * PANGAEA (AWI/MARUM) applies metadata workflows combining descriptive (e.g. dataset titles, abstracts, parameters, methods), structural (e.g. campaign and event hierarchies), and administrative (e.g. file formats, DOIs, licenses) elements. PANGAEA uses ISO 19115, DIF, Dublin Core, and its own metadata schema ensuring interoperability across geosciences and marine research (https://wiki.pangaea.de/wiki/Metadata).
-  * GFZ Data Services (GFZ Potsdam) supports metadata based on ISO 19115, NASA GCMD DIF, and DataCite, with its own metadata entry system providing templates and controlled vocabularies for FAIR compliance.
-  * Helmholtz Coastal Data Center (HCDC) relies on ISO 19115 and NetCDF CF Conventions, and in some cases OGC SensorML, to capture observational and sensor-based data.
-  * DataCite Metadata Schema provides the global backbone for dataset citation and retrieval (DataCite Schema
 __Motivation__
-Providing sufficient enrichment of data with metadata forms the basis for the implementation of standardized semantic concepts.
 ====2. Possible alternative solutions====
@@ Line 63: / Line 61: @@
 ====4. The Recommendation====
-**Bibliographic Metadata**
-It is recommended that for the accurate and consistent identification of a resource for citation and retrieval purposes, each published dataset should be provided with the core metadata elements defined in the most up-to-date DataCite Metadata Schema (see https://schema.datacite.org/).
+**Instruments/Devices**
+**Manufacturers’ names** should always be reported as they were //valid at the time of production//. In practice, this means using the name that appears on the instrument label or in the official manual.
-**Types of Metadata**
+  * If an instrument is marketed under a brand name, the brand (e.g., Thermo Scientific) not the parent company name (Thermo Fisher Scientific) should be used. If no brand is indicated, the official company name should be given.
+  * If the instrument was produced by a subsidiary company, use the subsidiary’s name at the time of production (e.g., Spectra GmbH), not the later acquirer (X Corp.). Subsequent changes, such as company sales, mergers, or renamings, should //not// be reflected in the metadata.
+  * In general, the most granular level available (e.g., the concrete brand or subsidiary rather than only the corporate group) should be recorded to ensure precision and avoid ambiguity.
-We recommend distinguishing between the main categories of metadata as defined in ISO standards and adopted by infrastructures such as DataCite:
+**Instrument model names** and numbers should be reproduced exactly as they are written on the instrument label or in the accompanying manual, including spaces, special characters, and capitalization. This ensures consistency and guarantees that identical instruments are always represented in the same way across datasets.
-__Descriptive Metadata__: describe the intellectual content of the data.
-Example: titles, abstracts, keywords, parameters, methods, temporal and geographic coverage.
-__Structural Metadata__: describe the internal structure and organization of data.
-Example: data tables, file formats (CSV, NetCDF), relations between files.
-__Administrative Metadata__: describe management, rights, and provenance.
-Example: license information, DOI assignment, versioning, funding project identifiers.
-__Provenance/Technical Metadata__ (sometimes included under administrative or treated separately in ISO frameworks): document how the data were created, transformed, and curated.
-Example: instruments, laboratory methods, data processing workflows.
-**Community and Repository Alignment**
-When selecting metadata schemas, data producers should always consider the intended purpose of the metadata:
-  - If datasets are to be published in repositories such as PANGAEA or GFZ Data Services, metadata must follow repository-specific workflows and schemas.
-  - If datasets need to be interoperable within a scientific community (e.g., oceanography, climate science), community standards like CF Conventions, NetCDF Climate & Forecast metadata, or GCMD keywords should be adopted.
-  - If datasets must be integrated into international portals and infrastructures, metadata must be aligned with globally recognized schemas such as ISO 19115 or DataCite.
 ====5. Naming of communities that have already implemented the recommendation====
@@ Line 101: / Line 79: @@
 ====7. Examples of Instances====
+Comment: HIER ERLÄUTERN, WIE in XML oder JSON dokumentiert werden; Beispiel.. V´Wie verpackt, um im Protokoll zu packen. unterschiedlich je nach Metadatenschemata; z.B. PANGAEA "kommaseparariert in einem Feld" vs SMS or Registry"
 ====8. Further Information====