Digital heritage enrichment through artificial intelligence and semanticweb technologies

Abstract

Art and culture represent substantial ways to transfer the history of humans across civilizations and epochs. Preserving artwork and cultural objects is thus important and the focus of multiple institutions and governments around the world. Digital preservation in cultural heritage represents a cost-effective and reliable long-term preservation and several challenges related to its effectiveness and its reliability have arisen such as metadata enrichment, digital curation, link discoveries, etc. Through this paper, we discuss these challenges and present innovative ways that leverage recent endeavors in artificial intelligence and semantic web technologies to enrich cultural data. Our contributions mitigate these issues either by recovering metadata of mislabeled assets or curating their damaged visual capture through new and advanced deep learning and semantic web technologies. The presented approaches are being studied in Qatar in the course of the CEPROQHA project. 2019 IEEE.