Data abounds and our ability to process it algorithmically is unprecedented. This opens up to exciting prospects for scientific advance and socio-technological transfer which were unimaginable only two decades ago. New generation Artificial Intelligence (AI) plays a role in scientific discovery and is a key driver of socio-economic development.
Data-intensive and AI-driven methods are therefore likely to shape a significant proportion of science in the decades to come, leading to an unavoidable re-assessment of the very idea of scientific knowledge, its production, and its technological transfer to society. Against this background, the overarching aim of Reasoning with Data (ReDa) is to advance the state of the art in the methodology of reasoning with data by tackling two critical aspects of the use of data: the production of scientific evidence and the determination of causal relations. The results will contribute to the design of a medical decision-support system.