The GraphBRAIN Framework for Knowledge Graph Management and Its Applications to Cultural Heritage

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Abstract

The traditional record-based approach to the description of Cultural Heritage is nowadays obsolete. It is unable to properly handle complex descriptions and it cannot support advanced functions provided by Artificial Intelligence techniques for helping practitioners, scholars, researchers and end-users in carrying out their tasks. A graph-based, semantic approach is needed, such as that provided by Semantic Web solutions. Also, a ‘holistic’ description approach is needed, that includes and inter-connects all branches and types of Cultural Heritage, and that is not limited to describing just the formal metadata of cultural objects, but can deal with their content, physicality, context and lifecycle, as well. The GraphBRAIN framework and technology for Knowledge Graph management enforces all these ideas and enjoys improved efficiency, expressiveness, and flexibility thanks to the use of the LPG model for knowledge representation. This paper describes GraphBRAIN and its application to several Cultural Heritage-related fields, including digital libraries, archives and museums, history of computing, and tourism as a way to boost fruition of these items.

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APA

Ferilli, S., Bernasconi, E., Di Pierro, D., & Redavid, D. (2025). The GraphBRAIN Framework for Knowledge Graph Management and Its Applications to Cultural Heritage. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 14129 LNCS, pp. 144–161). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-73741-1_10

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