Epistemic logic for metadata modelling from scientific papers on Covid-19

Simone Cuconato


The field of epistemic logic developed into an interdisciplinary area focused on explicating epistemic issues in, for example, artificial intelligence, computer security, game theory, economics, multiagent systems and the social sciences. Inspired, in part, by issues in these different ‘application’ areas, in this paper I propose an epistemic logic T for metadata extracted from scientific papers on COVID-19. More in details, I introduce a structure S to syntactically and semantically modelling metadata extracted with systems for extracting structured metadata from scientific articles in a born-digital form. These systems will be considered, in the logical model created, as ‘Metadata extraction agents’ (MEA). In this case MEA taken into consideration are CERMINE and TeamBeam. In an increasingly data-driven world, modelling data or metadata means to help systematise existing information and support the research community in building solutions to the COVID-19 pandemic.


epistemic logic; applied non-classical logics; metadata modelling; COVID-19 pandemic

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DOI: http://dx.doi.org/10.23756/sp.v9i2.652


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Science & Philosophy - Journal of Epistemology, Science and Philosophy. ISSN 2282-7757; eISSN  2282-7765.