The project CUHE aims to develop and demonstrate a web-based application based on AI recommendations that will allow cultural heritage professionals (e.g. museum curators, archivists) as well as (humanities) researchers to explore existing media and cultural heritage digital collections in a more holistic way and allow them to curate new galleries or create digital stories and exhibitions which can showcase and share the new insights gained.
The project will target a key infrastructure for researchers and heritage professionals: European users can not only find over 50 million records but also explore over 60 curated digital exhibitions, countless galleries and blog posts.
CUHE plans to improve and make more scalable the process of curating digital exhibitions and galleries by providing a facility for related content exploration based on an AI recommendation system that exploits the metadata available for the content. Resulting recommendations would be at the level of records related to a given record, records related to a given curated collection (e.g. gallery, exhibition,etc), and collections related to a given collection. The work in the project will not only focus on the recommendation algorithm themselves but most importantly, will aim through co-creation to come up with a user interface that allows the users (who are often not ICT specialists) to understand what data dimensionalities resulted in the relation between the records or collections presented and give the option to adjust these parameters with several options. The recommendations could be used for both curating new collections (to help find interesting, diverse, and related content that will enable holistic documentation) and for contextualising and exploring connections between existing collections, allowing the audience to examine the presented topic from multiple perspectives.see website