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On Big Data: How should we make sense of them?

2020

The topic of Big Data is today extensively discussed, not only on the technical ground. This also depends on the fact that Big Data are frequently presented as allowing an epistemological paradigm shift in scientific research, which would be able to supersede the traditional hypothesis-driven method. In this piece, I critically scrutinize two key claims that are usually associated with this approach, namely, the fact that data speak for themselves, deflating the role of theories and models, and the primacy of correlation over causation. In so doing, I will also refer to a recent case history of data mining projects in the field of biomedicine, i.e. EXPOsOMICS. My intention is both to acknow…

Big DataValue (ethics)causalityMultidisciplinarydata-driven scienceComputer sciencebusiness.industryBig dataepistemologyopacity of algorithm.Data scienceend of theoryHistory and Philosophy of ScienceParadigm shiftKey (cryptography)CausationHeuristicsbusinessMètode Revista de difusió de la investigació
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