Co-curation in the Museum: Opening-up Collections with a Sense of Serendipity and Purpose

Abstract

Opening up collections and fostering inclusive curatorial practices is a crucial part of reshaping power dynamics between museums and their public. Yet, when it comes to hands-on collection work inside museums—such as researching catalogues, arranging displays, and developing interpretive stories—these processes largely remain behind the scenes, outside the influence of visitors. A core challenge in supporting more people to search, find, and share their meaningful connections with museum collections is that these collections are vast, complex, and contain significant archival gaps. This makes grasping the structure and contents of a museum’s holdings a daunting task, even for dedicated experts. This paper presents research on how collection work can be put into action on the museum floor by designing co-curational interfaces that utilise the networked potential of digital collections. Drawing insights from Searcher, a project that experiments with the entire collection data of three European museums, we share novel methods for aiding users in navigating large collections and sharing discoveries in public displays. Centered on the concept of serendipity, these methods pair computational techniques that uncover dense interconnections between collection objects with people’s intuitive and interpretive power to identify what is personally meaningful. In doing so, more people are invited to exert their creative energy with collections, bringing in new and diverse perspectives into the museum. Given that the museum’s frontend grants access to only a fraction of its holdings through fixed displays and long-serving narratives, we argue for more open circulation of search, stories, and sharing within museums.

Presenters

Jon Stam
Student, PhD in the Arts Student, LUCA School of Arts, Limburg (nl), Belgium

Details

Presentation Type

Paper Presentation in a Themed Session

Theme

Collections

KEYWORDS

Co-Curation; Participation; Digital Collections; Machine-Learning; Interaction Design