Developing a creative model for Wikidata analysis in the GLAM sector

Enrique Tabone

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Authors Biographies: Enrique Tabone is a multi-disciplinary artist who has recently completed a postgraduate research degree at the University of Salford, where she works as a data scientist with the Digital Curation Lab at MediaCityUK. Her most recent publications about creative uses of Wikidata appear in the International Journal of Performance Arts and Digital Media (Vol.19 No. 3, 2023), and Mimesis Journal (Vol.13 No. 2, forthcoming, 2024/25).

Keywords: Wikidata, digital curation data sonification, data visualisation, GLAM

TL;DR: A series of explorations with datasets from art collections and museums is discussed in the context of potential applications to present the data structured through Wikidata in creative ways.

Abstract: In 2019, the author started developing a research project exploring the visualization of specific datasets from Wikidata for artistic practice at the University of Salford’s Digital Curation Lab. Initially, the research involved an analysis of gender representation in the University of Salford’s Art Collection through Wikidata. This led to the development of an inquiring model for application on other art or museum collections. Subsequently, this model was applied to datasets that include about 99 university art collections across the UK. During the period 2021 – 2023, a similar approach was adopted on Heritage Malta’s collection of prehistoric female figurines, held at two museums in Malta and Gozo. The project brought together the research work conducted over the previous years, towards a coherent conclusion. Structured on Wikidata, these datasets have been demonstrated through data visualizations, and a data sound art installation (data sonification) accompanied by physical art objects, created through the author’s artistic practice. In the process, reflections on data representations in art collections and/or museums – regardless of whether it is data visualization or data sonification – have provided opportunities to explore concrete ways to look into a collection (through data about it) rather than at a collection as a set of artefacts. This data science point of view aims to enable the discovery of relationships between items within the dataset while stitching them together through shared properties, including in creative ways.

Format: Paper (20 minutes presentation)

Submission Number: 21