Simone Cuconato

In an increasingly data-driven world, the question of data – or metadata – veracity is now a central issue not only in the world of information but also in the legal one. Data veracity describes a closeness to truth on a higher level than a measure such as accuracy does. High veracity data is data that can be relied upon when making decisions, thus reducing the risk of basing choices on untrue information. The article uses epistemic logic to model structured metadata automatically extracted from legal papers, and the tools of metaontology to propose a definition of veracity as truthmaker.

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’. 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.

In this article we develop a logical model for automatic extraction of structured metadata. We introduce a new predicate???? – reads ‘extract’ – and a structure???? to syntactically and semantically define metadata extracted with any automatic metadata extraction system. These systems will be considered, in the logical model created, as knowledge extraction agents. In this case KEA taken into consideration is CERMINE, a comprehensive open-source system for extracting structured metadata from scientific articles in a born-digital form.