Vers les analyses algorithmiques de l'espace et des territoires

• Main Authors: Claire Bailly, Jean Magerand
• Format: Article
• Language: fra
• Published: Ministère de la culture 2018-12-01
• Series: Les Cahiers de la Recherche Architecturale, Urbaine et Paysagère
• Subjects: Big data; data mining; deep learning; design process; architecture
• Online Access: http://journals.openedition.org/craup/1082

Big data, data mining and machine learning are undergoing unprecedented development. The methods they claim and / or convey invade the modes of analysis of most domains in charge of the territory and of the city such as sociology or geography. They cause deep epistemological questioning. This article aims to evaluate the changes that affect and redefine, in this context, the reading of our environments. To this end, we will highlight some of the salient points of automated data processing. Starting from the observation that the ways we read the world co-evolve with the ways we act on it, the challenge is ultimately to better understand how big data, data mining and machine learning are likely to affect our design processes.