AI for Cultural Heritage Hub Conference
AI for Cultural Heritage Hub (ArCH) to centrum utworzone na Uniwersytecie w Cambridge, które zapewnia kuratorom kolekcji bibliotecznych i muzealnych oraz pracownikom naukowym dostęp do narzędzi AI umożliwiających bezpieczną analizę danych związanych z dziedzictwem kulturowym. Jest to także miejsce, w którym prowadzone są prace nad prototypowymi rozwiązaniami opartymi na sztucznej inteligencji, które pozwolą lepiej poznać zbiory i zidentyfikować, które narzędzia sztucznej inteligencji umożliwiają ich opracowanie i zbadanie.
16 marca w godzinach 10.00-17.30 GMT (11.00-18.30 UTC) odbędzie się AI for Cultural Heritage Hub Conference (w formie stacjonarnej oraz na platformie Zoom). Udział w konferencji jest bezpłatny, jednak wymaga rejestracji.
Program:
Addressing cultural heritage challenges
ArCH’s six case studies will test the ability of AI methodologies to address three cultural heritage challenges.
Solving these challenges will serve researchers and wider society by benefitting cultural heritage practitioners, expert users and all those engaging with cultural heritage.
Challenge 1: Unlocking inaccessible data
Three of the case studies will address the challenge of unlocking inaccessible data by applying AI transcription and computer vision (CV) tools to digitised documents.
Case Study 1: AI tools will be used to convert analogue Cambridge University Library catalogue cards into online records. This has the potential to make thousands of rare books and maps discoverable, a project that would otherwise take years.
Case Studies 2 and 3: Historical handwritten biodiversity records from the University Museum of Zoology registers and specimen labels from the University Herbarium will be turned into machine-readable datasets. As well as deepening our understanding of these collections, this has enormous potential for biological research and the nature-human interface.
Challenge 2: Reconstructing fragmentary or dispersed cultural objects
Two further case studies will investigate how AI can assist with the reconstruction of fragmentary or dispersed cultural objects, to transform our understanding of them and their context.
Case study 4: This case study will test the ability of AI tools to reconstruct the position of unplaced papyrus fragments from the Book of the Dead of Ramose, an ancient document held at the Fitzwilliam Museum, by analysing fibre patterns.
Case Study 5: This case study investigates the potential of machine learning (ML) and computer vision tools to fill in missing text and analyse Mesoamerican symbols found in a sixteenth-century Nahuatl-Latin lectionary held in the Bible Society Collection at Cambridge University Library.
Challenge 3: Integrating expert cultural knowledge into AI algorithms
Case study 6 will investigate the use of LVM tools trained on small, bespoke datasets of specific types of cultural heritage artefacts, integrating expert, practitioner and community knowledge.