ArtiFact: A Large-Scale Multi-Modal Cultural Heritage Dataset
Multi-modal data management has emerged as a central research topic in the database community, spanning data integration, semantic query processing, and data quality assessment. Despite this growing interest, the community lacks large-scale, real-world datasets combining tables, text, and images. We present ArtiFact, a multi-modal cultural heritage dataset of 651045 museum records collected from the Metropolitan Museum of Art, the Art Institute of Chicago, and the Rijksmuseum. We demonstrate the utility of ArtiFact through two downstream tasks. For cross-modal error detection, we introduce a curated taxonomy of seven error categories injected into 130209 records and show that reliably det...
| Authors | Luciano Duarte, Olga Ovcharenko, Sebastian Schelter |
|---|---|
| Primary category | cs.DB |
| Published | 8 June 2026 |
| Last updated at source | 12 August 2026 |
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