Toronto, October 9, 2025
An international and multilingual digital humanities initiative has officially launched: the pilot project “Semantic AI for Networked Saints” (SANS).
This collaboration brings together three leading research projects across two countries: the Documents of Early English Data Sets (DEEDS) and the Baptisteria Sacra Index (BSI), both based at the University of Toronto, and Mapping Saints (MS) at Linnaeus University in Sweden. The collective strength of these three projects provides a robust and diverse source base for this groundbreaking work.
Advancing Hagiographical Research Through AI
The SANS pilot project is designed to address a long-standing challenge in hagiographical and cultural heritage studies: connecting fragmented data about saints across various textual and visual contexts.
The project team is developing a sophisticated framework utilizing Generative AI to efficiently and accurately identify and extract saint references from a wide range of cultural heritage works, dated from the 2nd to the 18th centuries. The AI’s objective is not merely to find names, but to extract the rich context surrounding each reference, including:
- Associated placenames and geographical data
- Institutional names and community affiliations
- Dedications, dating, and liturgical feasts
This process will create a deep, layered dataset that allows scholars to map and analyze the complex historical and cultural networks of saint veneration across time, regions and communities.
The Commitment to Linked Open Data (LOD)
A core commitment of the SANS pilot is to ensure maximum accessibility, scholarly reuse, and open access. The finalized, enriched dataset will be published as Linked Open Data (LOD).
This transformation is essential. It allows the project’s data to move beyond traditional database structures and connect to the broader web of open “holistic knowledge.” The new data will be made discoverable via an open access ontology-based semantic portal, offering unprecedented opportunities for new research questions and digital analysis by the global community.
This pilot phase, which focuses on developing and validating the complex data models, is supported by the technical consulting expertise of Sigtica, a team of data engineers specializing in AI for cultural heritage preservation, whose assistance is integral to the successful deployment of the advanced generative models required for this multilingual data extraction work.
The project team looks forward to sharing further updates as the SANS pilot progresses and begins to reveal new connections within our shared cultural heritage.