AI Use Cases for the Digital Documentation and Preservation of Cultural and Scientific Heritage

Alexander I. Iliev; Aman Malik; Gagan Anil Gowda; Satyajit Samal

doi:10.55630/dipp.2026.16.19

Authors

Alexander I. Iliev SRH University, Campus Berlin, Ernst-Reuter-Platz 10, 10587 Berlin, Germany , Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, 8 Acad. Georgi Bonchev Street, 1113 Sofia, Bulgaria
Aman Malik SRH University, Campus Berlin, Ernst-Reuter-Platz 10, 10587 Berlin, Germany
Gagan Anil Gowda SRH University, Campus Berlin, Ernst-Reuter-Platz 10, 10587 Berlin, Germany
Satyajit Samal SRH University, Campus Berlin, Ernst-Reuter-Platz 10, 10587 Berlin, Germany

DOI:

https://doi.org/10.55630/dipp.2026.16.19

Keywords:

Multimodal AI, Digital Cultural Heritage, Metadata Enrichment, Semantic Linking, Multimedia Retrieval

Abstract

This paper presents a multimodal approach to the artificial intelligence of the digital presentation and preservation of cultural and scientific heritage. Integrating the multiple modalities of indexing, automated metadata enrichment and semantic linking, the framework provides better archival discoverability. The main contribution is a non-destructive architecture that utilizes a shared semantic space to fuse text, visual, and audio modalities while employing a Semantic Anchor strategy to prevent the erasure of "thin" legacy metadata. Experimental findings demonstrate a Mean Precision @ 5 of 0.92 and a 100% Data Retention rate, proving that the framework successfully reclaims "dark data" while maintaining high retrieval consistency across heterogeneous multimedia collections.

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