Making Sense Of Data In The Sciences. Philosophical Perspectives on the Methodology, Epistemology and Practices of Data-Intensive Science

Discussions on the role of data in the sciences have acquired a central position in current philosophy of science. As part of a wider critical debate on the rhetoric of ‘big data’, philosophical discussions are now focused on the practices involved in the use of data in specific scientific disciplines, documenting challenges and benefits of working with data and studying the ethical dimensions of what is known as “data-intensive science”.

This workshop is aimed at promoting and further expanding this line of research, by focusing on a number of particularly important questions for the debate:

• What is the role played by ‘traditional’ aspects of scientific research (e.g. experiments, causal discovery, etc.) in data-intensive science?
• Which kind of practical and methodological issues are part of scientific practices involved in the use of (big) data?
• Which modes of integration are made necessary by the need of using different kinds of data regarding significantly different phenomena?
• Which role should we conceive for values in data-intensive science?
• Does data-intensive science entail new aspects of responsibility? If so, which notion of responsibility do we need and which aspects should we highlight?

Discussions on these issues will follow a practice-based approach to philosophy of science, aiming at studying actual contexts of practice in the sciences and advancing scientific practice itself by highlighting its potentially problematic aspects.