Background: Integration of heterogenous resources is key for Rare Disease research. Within the EJP RD, common Application Programming Interface specifications are proposed for discovery of resources and data records. This is not sufficient for automated processing between RD resources and meeting the FAIR principles.
Objective: To design a solution to improve FAIR for machines for the EJP RD API specification.
Methods: A FAIR Data Point is used to expose machine-actionable metadata of digital resources and it is configured to store its content to a semantic database to be FAIR at the source.
Results: A solution was designed based on grlc server as middleware to implement the EJP RD API specification on top of the FDP.
Conclusion: grlc reduces potential API implementation overhead faced by maintainers who use FAIR at the source.
Keywords: FAIR; data management; information storage and retrieval; metadata; rare disease; semantic web.