Overview of a suite of middle-ware services for implementing FAIR data principles

Principles of Findable, Accessible, Interoperable, and Reusable data for humans and computers (FAIR)1are widely endorsed by organizations such as the European Open Science Cloud, the life science data infrastructure ELIXIR, the NIH via its commons program, the biobanking infrastructure consortium BBMRI-ERIC, the G20 and the G7. Implementing a data ecosystem based on FAIR principles requires guidelines, tools, and training, and FAIR data stewards to help apply them. The principles as such do not recommend any particular implementation: user communities will have to decide the most appropriate implementation for their domain. Here, we demonstrate the use of a suite of Semantic Web-based middle-ware services that help communities implement FAIR data principles2. Aiming to facilitate adoption, the services are made to complement existing data infrastructures, including local and centralised data resources, and thus establish a robust, federated ecosystem of FAIR resources. The services are also particularly suited for training data stewards. We demonstrate the application of the services by rare disease and plant breeding communities where
the combination of Ontologies, Linked Data, and light-weight FAIR services are being explored as the means to implement FAIR data principles.