Semiotic Approaches to Big Data Visualization

With a few exceptions – focusing on journalism (Compagno 2017), on works of art (Chartier, Pulizzotto, Chartrand & Meunier 2019, Dondero 2020), on deep fake videos (Leone 2021, Dondero 2021), and on data epistemology (Bachimont 2018) – semiotics has been late to approach big data. In contrast to information and communication studies, which have been quick to recognize the big data revolution in medical, biological, political, urbanistic, and journalistic practices, and while digital humanities and digital art history continue to offer crucial insight with their analysis of large collections of artworks and heritage objects, semiotics has yet to live up to the big data challenge. In this Punctum issue we have attempted to (1) contribute to the global discussion of possible semiotic approaches to big data theory and methodology; (2) explore specifically an epistemological approach to visualizations of big data, i.e., to their manipulation, design, display, and interpretation; (3) study, from a critical vantage point, the ideologies and epistemic perspectives that underlie the acts of collecting and visualizing big data, prior to their analysis. Our overall objective has been to trace the path that leads from visualization, regarded as a unifying representation of disparate data, to its full elevation to an interpretative device.