Enabling FAIR Discovery of Rare Disease Digital Resources

Rajaram Kaliyaperumal*, Núria Queralt Rosinach, Kees Burger, Luiz Olavo Bonino Da Silva Santos, Marc Hanauer, Marco Roos

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)
80 Downloads (Pure)


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.

Original languageEnglish
Title of host publicationNavigating Healthcare Through Challenging Times - Proceedings of dHealth 2021 - Health Informatics Meets Digital Health
EditorsDieter Hayn, Gunter Schreier, Martin Baumgartner
Number of pages3
ISBN (Electronic)9781643681801
Publication statusPublished - 7 May 2021
Event15th Annual Conference on Health Informatics meets Digital Health, dHealth 2021 - Virtual, Online, Austria
Duration: 11 May 202112 May 2021

Publication series

NameStudies in Health Technology and Informatics
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365


Conference15th Annual Conference on Health Informatics meets Digital Health, dHealth 2021
CityVirtual, Online


  • data management
  • FAIR
  • information storage and retrieval
  • metadata
  • rare disease
  • semantic web


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