FAIR Convergence Matrix: Optimizing the Reuse of Existing FAIR-Related Resources

  • Hana Pergl Sustkova (Contributor)
  • Kristina Maria Hettne (Contributor)
  • Mark Musen (Contributor)
  • Peter McQuilton (Contributor)
  • Erik Schultes (Contributor)
  • Larry Lannom (Contributor)
  • Peter Wittenburg (Contributor)
  • Jan Slifka (Contributor)
  • Annika Jacobsen (Contributor)
  • Melanie Imming (Contributor)
  • Markus Stocker (Contributor)
  • Robert Pergl (Contributor)
  • Barbara Magagna (Contributor)
  • Tobias Kuhn (Contributor)
  • Susanna-Assunta Sansone (Contributor)



Figure 1 shows convergence Matrix Process Overview. The questionnaire is composed and maintained by FAIR Experts, an effort was made to ensure broad coverage of technologies and other Resources and how they relate to each of the FAIR principles. The questionnaire is encoded in a machine-readable Wizard Knowledge Model, which then exposes the questions in a user-friendly interface (screenshot). The community spokesperson registers in the Wizard, completes a few questions profiling the community, then begins to answer the 61 questions in the questionnaire. Default answers, drop-downs and autocomplete make the completion of the form easier and help achieve the machine readability. At some point in the future, Communities and trusted third-parties (e.g., funding agencies, publishers, data stewards, etc.) could publish customized Knowledge Models that will offer recommendations on, or even require the use of, certain Resources. This function could be a powerful driver of convergence. The drop-down and autocorrect is provided by FAIRsharing. The data input by the Community Spokesperson is captured as stand-alone nanopublications (capturing an assertion about the “Implementation Choice Made” and documenting the decision with a collection provenance metadata). The nanopublications
will be made available on the distributed nanopublication server network, and will be available to any other organizations for hosting and serving. The resulting open knowledge graph is generated from the stored data and can be viewed as a public good, advising a myriad of decisions needed to launch and sustain the Internet
of FAIR Data and Services.
Date made available2020

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