Meta-Acervos: AI, Metadata, and the Politics of Visibility in Brazilian Museum Collections

Authors

Thiago G. Hersan (The New School), Giselle Beiguelman (University of São Paulo), Ana Gonçalves Magalhães (University of São Paulo)

Presentation

Session

VISAP Paper 2

Time

Wednesday, Nov 11, 10:36 – 10:48 (US/Eastern) · session 10:00 – 11:30

Location

Hall Essex south

Keywords

Art, archiving, embedding, clustering, machine learning

Abstract

This research presents a visualization methodology for creating alternative archival connections within incomplete, fragmented, and historically uneven collections. Meta-Acervos is an interactive meta-archive system that integrates information from dispersed art collections held by public museums in Brazil, using computational analysis and interactive visualization to foreground relationships between objects across institutional boundaries. Rather than functioning solely as an interface for accessing museum artworks, the system explores how visualization and interface design can support alternative discursive, curatorial, and museological approaches to cultural heritage. By challenging archival structures organized around established schools, artistic movements, techniques, and historical periods, Meta-Acervos investigates how computational systems can produce different ways of encountering and interpreting collections. Situated within the context of the Global South, the project also examines the contradictions of archival digitization in Brazil, where preservation, classification, and access are shaped by histories of inequality, institutional priorities, and colonial knowledge structures. The research argues that visualization can function not only as a means of representing archival information, but also as a critical method for interrogating and reconfiguring the structures through which cultural heritage is organized, while making visible the assumptions and biases embedded in archival data and computational technologies.