1.b FDP reference implementation

Introduction

Running a FAIR Data Point to expose your metadata is an option if you have the necessary resources/capacity and knowledge. We also 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 (4B Exposing metadata ) within your FDP, the data can be harvested by the National Catalogue. For this step see: 5. Metadata harvesting .