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Short description
This step focuses on the processes required to transform existing metadata, already mapped to a metadata schema (see previous step). It provides detailed guidance on how to expose metadata to meet these standards, ensuring that data can be easily discovered and utilized by others. By exposing metadata in a FAIR manner, the research resource (e.g. Dataset) is made findable and accessible to a wider audience through appropriate channels and platforms such as the Health-RI Catalog.
This step also emphasizes the impact of adhering to the FAIR principles and the standards that compile them. It offers practical advice and tools to help users achieve compliance, thereby enhancing the reusability and interoperability of their data. This step is essential for those looking to improve the visibility and accessibility of their metadata, ensuring that it can be effectively matched and reused within the scientific community and beyond.
Transform data:
FAIR in a box - csv -> rdf part (add link)
open refine - transformation part
Castor EDC - swag template
Store and expose data:
Triple store in a FAIR data point
Transform, store and expose metadata:
FAIR data point reference implementation
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The next step in the process is to make your data and metadata linkable, i.e. transform them to a machine readable knowledge graph representation [Generic]. Currently, this is done using Semantic Web and Linked Data technologies [GOFAIR_process]. An example of a linkable machine-readable global framework is the Resource Description Framework (RDF). It provides a common and straightforward underlying model and creates a powerful global virtual knowledge graph [Generic]. To transform the metadata and data into this linkable representation requires the semantic models defined in step X and step Y respectively. See the How to section for practical information.
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