Katrin Glinka’s dissertation project investigates the effects of digitality on the cultural technique of collecting in museums. It integrates a cultural studies perspective with perspectives and approaches from computer science and Human-Computer Interaction. Based on a discussion of theoretical questions regarding the symbolic functions of collecting, the dissertation contributes practice-oriented recommendations. These are aimed at illustrating technic-inherent and epistemological potentials of digital technologies in the sense of a “digitally transformed” cultural technique of collecting.

Digital technologies are already extensively being used in museums, not only to document, index and publish collections, but also in research, interpretation, and mediation. In a post-digital society - or a post-digital museum practice -, it hardly seems productive to describe digitality exclusively and primarily as leading to upheaval or radical structural change per se. The dissertation project, therefore, follows the hypothesis that the use of digital technologies in museums has not automatically triggered a fundamental transformation of the cultural technique of collecting in itself. To explore this hypothesis, the object of investigation is narrowed down to concrete techniques, processes, procedures, and structures that are particularly associated with the recording, indexing, description, ordering, and finally publishing of museum collections. Based on resources such as technical documentation and reports, user manuals, and guidelines used in museums, it will be shown how and to what extent digital collection management systems were conceived in direct continuity to analogue systems. After acknowledging this continuity, the dissertation proceeds by identifying digital practices and technologies that actually transform the cultural technique of collecting in museums (or have the potential to do so as soon as they would be broadly applied).

This project specifically focusses on the central functions and conditions of "knowledge representation" as part of collecting in museums. Rather than solely treating "knowledge representation" as modelling and formal mapping of knowledge and data, the dissertation also draws on constructivist and feminist theories and conceptualizations of "situated knowledges”. This relates to the inherent potential of digital technologies to expand knowledge representations in such a way that they would allow the inclusion of a multitude of representations of objects as well as the creation of dynamic references to and between objects and collections. This, in turn, transgresses a hegemonic and monolithic concept of "knowledge" that has been a central part of the cultural technique of collecting in museums.

With this in mind, two exemplary lines of transformative potential (or fracture lines) are traced within the dissertation project: first, the epistemological expansion of knowledge representation in co-occurrence with anti-colonial museum practice and institutional critique and, second, the integration of methods for knowledge extraction and processing of digital collections based on Machine Learning - specifically Computer Vision (CV) and Natural Language Processing (NLP). In the context of this second line of transformation, the dissertation uses the term "similarity" as an example to exemplify epistemological differences and similarities between concepts and methods in computer science, art history, and museum practice. Following this comparison, the effects that are associated with the "dissimilarity of similarity" in the context of digital collection techniques in museums will be discussed and problematised.

Drawing on conceptualizations of human-centred computing perspectives on data, algorithms, and interfaces, the project finally explores how interfaces and visualisations can be conceived in such a way that they support the negotiation of underlying technological and epistemological conditions for referencing and representing objects in museum collections.