Christiane Sibille: Transform – Evaluate – (Re-)Use: Collections as Data in Practice

Since 2021, the Digital Scholarship Services office of the collections and archives at the ETH Library has been developing projects and services at the intersection of digitized collections, infrastructure, and research. The idea of “collections as data” and the use of machine learning technologies have been central to this work from the very beginning. These projects currently focus on workflows for transforming and enriching digitized collections, ranging from handwritten transcripts to richly illustrated journals. In this context, we have developed a four-stage conceptual framework that helps us identify different levels of application for machine learning in archives. In my presentation, I will introduce this framework and discuss the learnings from our projects, focusing on the role of interdisciplinary methods in establishing sustainable workflows and services.

Archives and museums are placing great hopes in Artificial Intelligence. Time-consuming, labor-intensive tasks — such as the description and analysis of objects — can already be, or may soon be, taken over by machines. Artificial Intelligence (AI) promises not only access to previously unexplored holdings but also new, powerful analytical tools for research, enabling the extraction of new information about cultural objects and the visualization of previously unseen connections. Finally, the hope is that automation will free valuable resources for research and creative work with cultural heritage.
The conference »Archival Intelligence: AI × Archives × Museums« asks where we currently stand with regard to these promises. It seeks to show where and how AI can be used in practice and to open a discussion on the new possibilities and consequences arising from the availability of these technologies — implications that we may not yet have anticipated. The focus lies on concrete applications of AI — from automated text, speech, and handwriting recognition, and the analysis of images and videos, to the cataloguing of archival holdings and scholarly data analysis, the curation of collections, AI-supported provenance research, and restoration.
Experts from museums, archives, and universities offer practice-oriented insights into the use of AI as an analytical tool and as valuable support for semantic indexing and targeted information retrieval. Particular emphasis is placed on learning from applications outside the fields of art and culture, such as research data management, in order to develop pragmatic approaches for museums and cultural archives.
Organized by the ZKM | Center for Art and Media, one of the leading institutions in the field of media art and recognized for its expertise in the preservation of electronic and digital artworks, this conference offers an opportunity to discover innovative approaches and to engage with experts who are actively shaping the future of work with cultural and scholarly objects.  

With

Dominik Bönisch Alpári (Düsseldorf University of Applied Sciences), Giovanni Colavizza (University of Copenhagen), Robert G. Erdmann (University of Amsterdam), Ralph Ewerth (TIB Hannover), Jasmijn Van Gorp (Utrecht University), Adelheid Heftberger (Federal Archives), Andreas Kohlbecker (ZKM | Karlsruhe), Bárbara Romero Ferrón (Leuphana University Lüneburg), Heiko Schuldt (University of Basel), Christiane Sibille (ETH, Zurich), and Kim Voss (DRA | German Broadcasting Archive).

The conference is part of the »Artificial Intelligence & Art« funding project of the City of Karlsruhe.

Imprint:

Margit Rosen: Concept
Idis Hartmann: Concept
Andreas Kohlbecker: Research Associate
Felix Mittelberger: Research Associate