The term DataArt usually refers vaguely to any kind of artistic work that involves the use of data for its creation in some way. The type of DataArt that is presented on these works involves a broader conception of the common terms visualization/sonification; data transduction.
This is a term I proposed several years ago (https://www.untref.edu.ar/mundountref/problematicas-y-desafios-en-arte-electronico-y-educacion) and one that I keep using both for academic research and for art production.
Data Transduction stands as a theoretical framework that organizes the practical workflow and aesthetic conception of the use, analysis and mapping of data for aesthetic purposes. It stands as a generalization of the traditional terms “sonification/visualization” as they are traditionally understood within the artistic community. In this sense, data transduction involves data management in any part of the creative process and disrupts the idea of linear and basic mapping of data onto sonic/visual parameters. This disruption comes by supporting the use of data also as a raw material for both metaphor construction and parametric control and by stating also that data can come and be extracted from any source.
That is the kind of works that are presented here. Data as a compositional raw material. Data as a flow for parametric control. Data as a computational aesthetic experience.