The Digitized Past: Challenges and Opportunities
The digital transformation is fundamentally changing how societies remember, interpret, and debate the past. Historical knowledge is increasingly created not only in archives, libraries, and museums, but also on social media platforms where millions of people encounter, discuss, and reinterpret history every day. At the same time, artificial intelligence, digital archives, and computational methods are opening entirely new possibilities for preserving, connecting, and analyzing historical sources. Our research investigates both sides of this transformation: how digital technologies reshape public understandings of history, and how they can be used to preserve and generate historical knowledge. A particular focus of our research is Holocaust remembrance, where we develop computational methods that support historical research, digital preservation, museum practice, and public engagement.
History is no longer communicated exclusively through books, museums, or classrooms. Platforms such as TikTok, YouTube, Instagram, Reddit, and emerging AI-powered systems have become major arenas where historical narratives are produced, debated, and shared with global audiences.
We study how platform algorithms, recommendation systems, generative AI, and online communities shape public understandings of the past. Our research examines how historical narratives are created and disseminated, how audiences engage with them, and how the affordances of digital platforms may encourage simplified or polarized interpretations of complex historical events. By combining computational methods with historical inquiry, we seek to understand how digital media influence collective memory, historical literacy, and democratic discourse.
Digitization has made vast historical collections accessible to researchers and the public. However, historical knowledge extends far beyond digital objects themselves. The context needed to interpret photographs, documents, testimonies, and other historical sources often resides in the expertise of historians, archivists, memorial institutions, and local communities.
Our research develops computational methods that transform digital collections into connected, searchable, and reusable historical knowledge. We investigate semantic annotation, knowledge graphs, AI-assisted transcription, multimodal analysis of historical collections, and interactive digital tools that support research, education, and remembrance. Our goal is to create technologies that preserve not only historical sources but also the contextual knowledge that gives them meaning.
An important component of this work is public engagement. We develop participatory digital infrastructures that enable volunteers, students, local initiatives, descendants, and memorial communities to contribute historical knowledge, annotations, and contextual information. By combining human expertise with computational methods, we seek to build collaborative knowledge ecosystems in which the public actively contributes to preserving and expanding our understanding of the past. Such approaches not only enrich historical collections but also strengthen civic participation in historical research and remembrance.
Our work combines Computational Social Science, Artificial Intelligence, Digital Humanities, and contemporary history to develop computational methods for historical research and communication. Rather than replacing historical expertise, AI and other computational approaches can support historians, archivists, museums, and memorial institutions by making large and heterogeneous collections more accessible, discoverable, and interconnected while preserving scholarly rigor and historical nuance.
Beyond archival research, we explore how digital technologies can support museum exhibitions, educational platforms, and new forms of public engagement with history. By critically integrating computational methods with historical scholarship, we aim to create digital tools that facilitate research, strengthen historical literacy, and foster critical engagement with the past.
Are you interested in digital history, AI, digital humanities, historical research, or the societal implications of digitization? The The Digitized Past project offers opportunities for motivated students to contribute through seminar projects, interdisciplinary student projects, Bachelor's theses, and Master's theses.
We welcome students from a wide range of disciplines, including history, political science, computer science, information systems, data science, digital humanities, and related fields. Depending on your interests and background, projects may involve empirical research, digital methods, AI applications, data analysis, visualization, or conceptual and policy-oriented work.
If you are interested in exploring a topic related to the project, we would be happy to discuss possible study and thesis opportunities. Please get in touch with us to learn more.