FAIRsFAIR is working actively to produce recommendations on technologies that support semantic interoperability in a sustainable way, and practices that support FAIRness.
Specifically, we aim to:
On this page you can find summary information about our key outputs in each of these areas. Click on the links to access comprehensive newspieces, the associated reports, and further reading material.
Based on studies of public information, especially EOSC infrastructure efforts, and on limited surveying and interviews, documented in D2.1 Report on FAIR requirements for persistence and interoperability 2019, FAIRsFAIR published a second D2.4 Report on FAIR requirements for persistence and interoperability was written specifically for researchers, data stewards, and service providers, as a guide the use of PIDs, metadata, and semantic interoperability. The third report, D2.10 3rd Report on FAIR requirements for persistence and interoperability, zoomed in on six specific aspect of FAIR implementation, that should be paid attention to.
The Recommendations for FAIR Semantics proposes 17 recommendations related to one or more of the FAIR principles and 10 best practice recommendations to improve the global FAIRness of semantic artefacts.
The report 2.3 Set of FAIR data repositories features provides guidelines to enable repositories not only to host FAIR digital objects, but also to be FAIR themselves. The recommendations were collected in the workshop “Building the data landscape of the future: FAIR Semantics and FAIR Repositories” which took place in Espoo Finland in October 2019.
The non-technical requirements tabled in the report relate to service level and other agreements between users and repositories or communities and data providers. They include amongst others:
The report provides a comprehensive list of technical features aimed at improving interoperability and grouped by category. Categories dealt with include:
Additional technical requirements are that repositories should acquire a machine-readable license and provide a search interface that enables findability.
A FAIRsFAIR reference implementation of a FAIR Data Point was presented in D2.6 1st reference implementation of the data repositories features and further testing and development were discussed in D2.9 2nd reference implementation of the data repositories features and client application.
The Assessment report on FAIRness of services (D2.7) proposes an assessment framework for the FAIRness of services. Aimed at a target audience of data service owners, the model contains concrete recommendations to improve different aspects of services. The report presented 50 recommendations on how services can be made optimally improve the FAIRness of the data that they are used for. The recommendations are divided into seven different aspects:
Technical & service provisioning aspects
Associated report M2.10 Report on basic framework on FAIRness of services
Associated webinar: FAIRification of Services: Two Examples
Associated workshop: FAIR Certification of Repositories and other Data Services
The FAIRsFAIR extra milestone dedicated to software as a research output, M2.15 Assessment report on 'FAIRness of software' (October 16, 2020) presents the state-of-the-art of software in the scholarly ecosystem alongside 10 high-level recommendations for organisations seeking to define FAIR principles or other requirements for research software in the scholarly domain.
Associated webinar: FAIR + Software: decoding the principles
Associated blog post: Decoding the FAIR principles: are they relevant to software?
The emergence of an ecosystem where FAIR data reuse becomes the norm depends upon researchers’ ability to search for and find suitable data held across multiple repositories. For this to happen, repository and aggregator service providers must reach agreement on common metadata catalogue standards to support interoperability. Through a series of workshops, metadata catalogue integration challenges were explored with representatives of domain specific repositories which led to the D3.6 Proposal on integration of metadata catalogues to support cross-disciplinary FAIR uptake. During the subsequent pilot, the feasibility of Data Catalogue Vocabulary (DCAT) v2 was assessed from both the domain specific and aggregator perspectives. The results of the pilot are presented in D3.7 Report on integration of metadata catalogues. Key findings include: