Science & Philosophy (Dec 2021)
Epistemic logic for metadata modelling from scientific papers on Covid-19
Abstract
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 we propose an epistemic logic model for metadata extracted from scientific papers on COVID-19. More in details, we introduce a new predicate ξ – reads ‘extract’ – and a structure S to syntactically and semantically analyse 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 ‘knowledge extraction agents’ (henceforth KEA). In this case KEA 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.
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