| Summary: | This paper discusses how data mining produces multiscale spatial representations in the contemporaneity: from private scale of individual physiological data to the global dimension of predictive models of big data. In order to understand the arrangements among these scales, we characterize data mining as an epistemic action from digital materiality; therefore, it is generator of algorithmic modes of knowledge. Based on this, we revisited the concept of hybrid spaces (SOUZA E SILVA, 2006) and analyzed how several practices of collect, analysis and reappropriation of data constitute topologies grounded on practices of data annotation, data visualization (creation of data doubles) and predictive models.
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