📌 Introduction
Running a FAIR Data Point to expose your metadata is an option if you have the necessary resources/capacity and knowledge. However, we recommend setting up an automatic export as the preferred method for exposing your metadata.
Requirements:
a (virtual) machine,
installed Docker
🧠 Explanation / Approach
The FAIR Data Point (FDP) reference implementation is available as a Docker Compose distribution. You can find detailed instructions in the official documentation at About FAIR Data Point — FAIR Data Point 1.16 documentation.
There are two options to deploy the FDP reference implementation:
Local deployment: For a simple setup, the Local Deployment is a good place to start.
Production deployment: If you plan to use the FDP in a real production environment, there’s also a Production Deployment option available.
Other implementations of Fair Data Point
There are several FAIR Data Point implementations in existence:
The reference implementation as described above.
The MOLGENIS software supports the FAIR Data Point protocol.
Castor currently supports a previous version.
The Netherlands eScience Center have their own implementation.
The SURF Data Repository implements the protocol.
RD-Nexus implements the protocol.
LOVD implements the protocol.
X-omics initiative develope a FAIR Data Infrastructure, FAIR Data Cube, which contains a enhanced FAIR Data Point as a main component in terms of its search and ranking capability.
⚖️ Pros / Cons
Pros
All components (FDP client, FDP server, blazegraph) deployed in one go.
Cons
Requires knowledge on deploying docker containers,maintenance of the server and application
Next steps
If you have an FDP and compliant metadata (2. Metadata mapping)within your FDP, the data can be harvested by the National Catalogue. For this step, please contact servicedesk@health-ri.nl .