Introduction

Scholarship on library catalogues and cataloguing practices provides numerous examples of how catalogue metadata reflect social biases regarding gender, racialised ethnicity, religion and sexuality, among others. This chapter takes a higher level view of library catalogues’ metadata, examining the numerous actors and practices that influence the creation and interpretation of catalogue metadata. Drawing on the work of critical heritage studies and feminism scholars in Europe, North America and Australia, I discuss the power exerted in the creation of catalogue metadata and the implications of such power relationships for research using these metadata. Acknowledging the inevitability of bias in data, I describe opportunities to manage catalogue metadata biases using natural language processing (NLP). Though bias cannot be eliminated, when critically applied, NLP methods can make the perspectives included and excluded in a catalogue explicit, informing research that aims to understand, use and improve library catalogues’ metadata and, in turn, the information discovery process. Due to overlaps in the cataloguing practices of GLAM institutions (galleries, libraries, archives and museums), this chapter refers to work relevant to the GLAM sector as a whole in addition to libraries specifically.

Digital and online technologies are enabling broader access to heritage in long-established libraries, such as the National Library of Scotland, through its Data Foundry platform (https://data.nls.uk).