FAIR Implementation approach
We collaborate closely to create a FAIR implementation that fits your needs. We start by listening to your needs and requirements and then help you decide where to add the appropriate level of FAIR enabling capability.
The FAIR implementation starts with a requirements analysis. The main focus of this stage is determine which level of FAIRness is sufficient to achieve the desired outcomes.
A FAIR metadata model is created covering the relevant concepts, relationships, and meanings. This provides the basis for the machine readability of the solution.
The FAIR Data Point is installed that handles machine interactions and contains the FAIR metadata model. It also provides core functions like interfacing and access control.
The FAIR Data Point is integrated into the existing data architecture. It depends on the scope of the project which interactions and interfaces will need to be implemented.
Requirements analysis
During the requirements analysis we will identify your FAIR needs in terms of functionality, performance and security. During this stage we:
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Gather your needs through interviews and workshops.
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Agree priorities of taking into account feasibility.
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Translate requirements in key user stories.
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Finalise and agree requirements and user stories.
Installation
Once the FAIR metadata model has been created it can be applied to create the metadata to be stored in the FAIR Data Point. During this stage we:
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Create metadata templates based on the semantic model.
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Create metadata based on the metadata templates.
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Install FAIR Data Point and publish metadata.
Solution Integration
At the solution integration stage, with the FAIR Data Point in place, it will be integrated in the existing data infrastructure. It involves:
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Developing and testing interfaces to the existing infrastructure.
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Integrating the interfaces to the FAIR Data Point.
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Test the end-to-end solution, especially the user stories.
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Go-live once testing is concluded.