Largely inspired by Erik’s index. I’m trying to hypothesize how we might sync the three different dimensions of FAIR that I see as important: cultural adoption, technical feasibility/capability, and the theory so they all contribute to a fuller science.


  • The Semantic Web - ontologies as exclusive to new discoveries, or inclusive?
  • The role of humans and machines in the semantic web
  • Who sees the semantic web?
    • Machines - Humans
  • Centralization and Decentralization in the semantic web - managing expanding content, sustainability, and discovery


  • Ways to create a norm: Moral norm, Incentivized norm, Institutional norms, default norms and their place in science
  • A scientific ecosystem of metadata
  • Treating Humans.

Technical Implementation

  • Rich metadata automation
  • Nanopublications, CEDAR, and the differences between them.
  • Machine Readability, Machine Usability, Machine Actionability
  • Federated Model Learning - what might it take to ensure we don’t overload individual servers
  • Machine Generated for 80%, Semantic Web Annotations for the 20%
  • Actual monitoring - monitoring scientific change
  • Ways to get rich machine actionable data that don’t use RDF - (Knowledge Graph, etc)

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