The digital transformation of society is advancing rapidly, reshaping our everyday lives. This evolution is not only changing how we engage with images, texts, and objects from the past and present, but is also significantly impacting art historical research. Computational methods – particularly those powered by Artificial Intelligence (AI) and Large Language Models (LLMs) – are driving a disruptive shift, the full implications of which are still unfolding.
The Art History research unit seeks to engage with this transformation in a reflective and responsible manner, exploring both the new methodological opportunities it presents and the accompanying legal and ethical challenges.
Our work focuses on three central challenges:
1) Translating analogue objects into digital data: This includes scanning, creating 3D models, digital reconstructions, and transcriptions. In the process of converting material forms into machine-readable form, some information is inevitably lost. However, this also opens up new possibilities for analysis and presentation. Our aim is to develop solutions that are sensitive to the specific materiality and research questions of each object.
2) Computational analysis: The growing availability of digital data relating to art-historically significant objects offers vast new avenues for analysis. Through the use of algorithms, as well as relational and graph databases, we can search and organise objects more effectively, revealing their similarities, differences, and interconnections. We are committed to investigating and expanding these analytical capabilities.
3) Presenting research findings: From websites and databases to blogs, vlogs, podcasts, and interactive formats, the digital sphere offers countless ways to communicate research. AI is also transforming how we write and present our results. We aim to develop legally and ethically responsible publication practices that inform both the academic community and the wider public, while remaining practical and accessible.
All research projects within our unit address these challenges. We are especially interested in harnessing the potential of machine learning and AI to forge new directions in research. One example is the project Ottoman Nature in Travelogues (ONiT) in which the team extracted approximately 20,000 images from travelogues about the Ottoman Empire held by the Austrian National Library. These images were made searchable and publicly accessible via the ONiT-Explorer. The team continues to critically reflect on its findings, regarding methodology, representation and accuracy. We are also actively involved in the Austrian Academy of Sciences’ thematic platform Machine Learning at the Austrian Academy of Sciences (MLA2S).
Ongoing Research Projects
Ottoman Nature in Travelogues (ONiT)
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