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Ontology Summit Theme Suggestions     (1)

  • Formal Ontology (FO) as a computer-based artifact Alex Shkotin     (1A)
    • Track A: forms, requirements, QA…     (1A1)
    • Track B: Definitions (Def)     (1A2)
    • Track C. Theoretical knowledge in XXI century. All theoretical texts are digital, so let's keep them structured semantically.     (1A3)
      • The system of sciences = sessions on the degree of formalization of different sciences.     (1A3A)
      • The system of technologies. = sessions on the degree of formalization of theoretical knowledge of different technologies.     (1A3B)
      • The theories of laws. = sessions on the degree of formalization of different law systems.     (1A3C)
  • Ontology use in computational brain and neuroscience of information models Ravi Sharma     (1B)
  • AI Solutions using ontology: (Tracks) Ravi Sharma     (1C)
  • Meta-ontology – beyond things and relationships: use of Uncertainties in entity and strengths in relationships Ravi Sharma     (1D)
  • Can ontologies filter and detect complex events? Ravi Sharma     (1E)
  • Ontologies - value demonstration - during Covid-19 and variants? Ravi Sharma     (1F)
  • Ontology for monitoring democracies, civil societies, ethics and environment. Ravi Sharma     (1G)
  • Disasters and Risks Gary Berg-Cross     (1H)
    • The information needed for the complex events of predicting, monitoring, mitigating and managing disasters and risks is complex and spans many organizations (both governmental and non-governmental), countries, languages and cultures.     (1H1)
    • Communication in real time is important for emergency response by many groups with severe time constraints.     (1H2)
    • Some potential tracks and sessions vary by where in the lifecycle of risks and disasters we are or by type of disaster situation we have:     (1H3)
    • Related material:     (1H4)
      • The COVID-19 Ontology     (1H4A)
        • The Pandemic  has prompted an impressive, worldwide response by the academic community. In order to support text mining approaches as well as data description, linking and harmonization in the context of COVID-19, we have developed an ontology representing major novel coronavirus (SARS-CoV-2) entities. The ontology has a strong scope on chemical entities suited for drug repurposing, as this is a major target of ongoing COVID-19 therapeutic development.     (1H4A1)
        • A disease model is framed by 3 high level concepts - The Agent addresses “what causes a disease like an infectious disease?”. It can be a microorganism, a pathogen, a virus, a bacterium, a parasite, or other microbes. SARS-CoV and SARS-CoV-2 are examples of such agents. The 2nd concept is that of the host - the organism which answers the question “who can be infected by a disease agent?”. It can be a human or an animal. The last concept is the environment.     (1H4A2)