What is a museum object according to a museum database?

Erin Canning

University of Oxford, UK

25 October 2023, 16.30-17.30 GMT

Image source: Erin Canning

Museum collection management systems (CMS), as the core data infrastructure for managing information about museum objects, have considerable power to shape understandings about what an object “is” through the fields made available for recording object information, and the relationships permitted between those fields. An interrogation of the fields of an art museum CMS demonstrates two primary ways through which an object can be known: through physical attributes, and through systems of classification intended to bring order to diverse objects from multiple and varied locations. This limits the way that an object can be known to, on one hand, vision-based empirical means, and, on the other, a system of organising the world that comes from only the museum’s point of view. In this talk, I will consider affect as an example of another way of coming to know museum objects that cannot be accommodated in museum databases at present. Through this example, I seek to show how databases can constrain ways of knowing, as well as demonstrate how it might be possible to accommodate radically different ways of knowing into such systems. Furthermore, by making space for additional ways of knowing, I aim to demonstrate how answering the question of “what is a museum object” is dependent upon the structure of the museum database and therefore can change when different system affordances are introduced. Finally, I discuss how changes to databases are never just that, but are tied to shifts in institutional power relations and long-held relations of power.

About the presenter

Erin Canning is a DPhil student in the Department of Engineering at the University of Oxford. Their project, “Novel applications of computational approaches in addressing problematic terminology within V&A museum catalogues”, is an AHRC-funded Collaborative Doctoral Partnership co-supervised by the University of Oxford and the Victoria & Albert Museum. Prior to beginning their studentship, Erin held the position of Ontology Systems Analyst at the Linked Infrastructure for Networked Cultural Scholarship project (LINCS). Erin holds Masters degrees in Information (MI) and Museum Studies (MMst) from the University of Toronto, where they conducted research examining how art museum information systems could be designed to accommodate affect as a fundamental way of knowing material culture. Erin is interested in the possibilities that semantic data modelling offers for structuring cultural heritage knowledge and data in more holistic and inclusive ways, as well as feminist and queer approaches to museum data practices.