Reprogramming heritage: an approach for the automatization in the adaptative reuse of buildings

Abstract

This article introduces a methodology for a novel data-driven computational model aimed at aiding public administrations in managing and evaluating the adaptative reuse of buildings while tackling ecological and digital challenges. Drawing from the 2030 Agenda for Sustainable Development, the study underscores the significance of innovative approaches in harnessing the economic potential of data. Focusing on Barcelona’s Ciutat Vella district, the research selects five historic public buildings for analysis, strategically positioned to spur local entrepreneurship and counteract tourism dominance. Through an extensive literature review, the article identifies a gap in computational models for building adaptative reuse and proposes a methodological framework that integrates data collection, processing, and computational modelling, underscored by GIS technology and open data sources. The proposed methodology for a computational algorithm aims to systematise spatial characteristics, assess programmatic needs, and optimise building usage, while addressing challenges such as data integration and quality assurance. Ultimately, the research presents a pioneering approach to building adaptative reuse, aimed at fostering sustainable urban development and offering replicable insights applicable to similar challenges in other cities.