Page 185 - AC/E Digital Culture Annual Report

great European digital library, contains more than thirty million objects which are reckonedto represent 10% of the digital cultural heritage available in Europe. This explains the emergence of a few initiatives that are designed to foster the collaborative use of Europeana and focus on literacy, dissemination and optimisation of digital heritage.Mention should be made of the PREFORMA286 project (PREservation FORMAts for culture information/e-archives), which adopts a unique approach to address the challenge of imple- menting quality standards for the preservationof long-term digital archives by developing open-code tools for creating databases for digital content. Data is normally stored in le formats speci cally designed for documents, images, sound, video etc. which are usually produced by software from di erent providers unrelated to the institution. This means that memory insti- tutions are at the mercy of software providers’ uncertain future and in many cases makes it necessary for digital content to be transferredto newer formats in order to be preserved in the long term. The work of PREFORMA is to create open-code tools that enable cultural institutions to address the issue of quality and preservation of their digital archives.As for the analysis and interpretation of cultural heritage, we have seen how the use of com- putational methods is rapidly growing in pace with the huge increase in the amount of digital information and large-scale heritage digitisation techniques and programmes. It is here that so-called arti cial intelligence is also enjoying signi cant presence in relation to research into cultural heritage. Shared interests have increas- ingly been found in this eld, giving rise to a successful combination of these two disciplines, as proven by the existence of the Workshop on Arti cial Intelligence for Cultural Heritage,287 a biennial event currently in its tenth year which highlights the most important research and experiences in this eld.The new applications of arti cial intelligence have thus provided opportunities for producing innovative tools for managing the large amounts of existing data which is growing day by day;for interpreting this data leading to results that prioritise knowledge and enhancement; for promoting cultural heritage by o ering new paradigms for interaction that make use of the large amount of data; or for protecting heritage assets through fast, minimally invasive research.These applications explain why the use of arti - cial intelligence in the heritage eld has been the focus of various research projects that explore how it can help improve the enhancement, conservation and promotion of cultural assets.E eHDDT methodThe following example comes from China and is a study on creating a heritage monitoring system based on complex algorithms. Its salient feature is that it focuses on detecting deformations in the architectural structures of heritage buildings – one of the pathologies that a ect their long- term conservation.The research was carried out by two Chinese research institutions, the Department of Infor- mation Science and Engineering of the Univer- sity of Ningbo and the Zhejiang Fashion Institute of Technology (Ningbo), with the collaboration of two Australian institutions, the School of Information Technology of Deakin University (Melbourne) and the College of Engineeringand Science of Victoria University (Melbourne), which coordinated their e orts to design an e ective heritage detection and tracking method (E eHDDT) using wireless sensor networks (Xie et al., 2014).288The main concern sprang from the importance of monitoring and identifying early evidence of the deformation of the elements of heritage sites, especially in Asia. In contrast to most world heritage monuments, in countries like China much of the historic heritage is made ofAC/E DIGITAL CULTURE ANNUAL REPORT 2017185The use of digital technologies in the conservation, analysis and dissemination of cultural heritage