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https://repository.ifla.org/handle/123456789/2196
Title: | AI and Data to Improve Preservation Management |
Authors: | Cabane, Célia Zreik, Alaa |
Keywords: | Subject::Artificial intelligence Subject::Preservation and conservation Subject::Cultural heritage Subject::National libraries Subject::Research |
Issue Date: | 24-Oct-2022 |
Publisher: | International Federation of Library Associations and Institutions (IFLA) |
Series/Report no.: | 87th IFLA World Library and Information Congress (WLIC);Poster Sessions |
Abstract: | Heritage collections are increasing and aging as time passes. To analyze all the hazards which occurred to almost 40 million documents, among which centuries old manuscripts, the National Library of France (BnF – Bibliothèque nationale de France) has decided to build a research program combining data describing collections and artificial intelligence. The aim of this program is to create a choice assistant tool. It is held by the BnF and the Versailles-Saint-Quentin University and funded by the Fondation des Sciences du Patrimoine. To analyze the hazards which occurred to the documents, all the events that occurred to a given document has been placed onto a trajectory. An ontology was constructed to tackle the heterogeneity of all the databases used. This work on the data relies on the use of two algorithms, which could calculate the similarity between different trajectories, create groups and compare communicability of the documents and event trajectories. The software, based on these algorithms and a database, requires as input a document and its related data and calculate its communicability status as output. In 2022, a global review has been done to improve software, algorithms and data and to consider other AI methods concerning preservation management. |
URI: | https://2022.ifla.org/ https://repository.ifla.org/handle/123456789/2196 |
Appears in Collections: | World Library and Information Congress (WLIC) Materials |
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150-cabane-poster-en.pdf | 321.91 kB | Adobe PDF | View/Open |
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