The Epistemology of Data Use: Conditions for Inferential Reasoning in the Age of Big Data Science
Sabina Leonelli (University of Exeter, UK)
Dec 1st, 2017
Center for Philosophy of Science, University of Pittsburgh (USA)
ABSTRACT: This talk examines the epistemology of data by addressing the challenges raised by ‘big data science’, and particularly the dissemination and re-use of large datasets via intricate and nested infrastructures such as digital databases. Empirically, my analysis is grounded on the in-depth qualitative study of “data journeys”, that is ways in which datasets are circulated and used for a variety of purposes across several different contexts. Conceptually, the talk brings my previous work on the relational nature of data to bear on existing philosophy of inductive reasoning and the triangulation of multiple lines of evidence (most prominently by John Norton, Alison Wylie and William Wimsatt), with the aim of outlining conditions under which big data can be used to reliably inform inferential reasoning. I conclude by highlighting five ways in which data science that fails to operate under such conditions could significantly damage scientific methods and the credibility of research outputs.
