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Artificial Intelligence and Pattern Recognition Technologies for Cultural Heritage: Involvement of Optical Character Recognition Software for Citizen Science in the processes for Crowdsourcing of Ancient Italian Texts.
Linnaeus University, Faculty of Arts and Humanities, Department of Cultural Sciences. Linnaeus University, Faculty of Technology, Department of computer science and media technology (CM). (Digital Humanities)
2022 (English)Independent thesis Advanced level (degree of Master (Two Years)), 80 credits / 120 HE creditsStudent thesis
Sustainable development
Not refering to any SDG
Abstract [en]

Cultural heritage makes reference to an extremely diverse set of sources. More specifically, historical artifacts as well as intangible elements of a community’s history, pertain to cultural heritage. However, when looking at the conservation, the enrichment, and the divulgation of these elements, the question becomes more complex. Even more so, when a context of nebulous regulation, unequal distribution of resources and funding of cultural heritage institutions, as well as a bureaucratically complex division of competencies between territories, are present. This is the case in Italy, and more specifically, Southern and Central Italy, where all these issues are present, and further hinder the exploration of undiscovered historical material, as well as the organization and divulgation of discovered material. 

Following this discrepancy along the lines of legal and practical restrictions, this thesis aims to explore and evaluate how technology can obviate to said issues. For instance, a methodological exercise was endeavored by scanning some ancient texts, in Latin and in Old Italian, and by running an optical character recognition software on the latter. 

More specifically, this thesis applies the paradigm of citizen science for crowdsourcing to explore how well optical character recognition software works in terms of accessibility and efficiency. As such, this methodological exercise does not consist primarily of a technological evaluation but aims at opening up new ways for the public to interact with cultural heritage institutions, for exchanging historical information while respecting the legal and practical considerations that were mentioned. In conclusion, by highlighting this issue, it would be possible to further research and enrich the publicly available data on Italian educational history between the 18th and the 19th Century.  

 

Place, publisher, year, edition, pages
2022. , p. 247
Keywords [en]
Artificial Intelligence, Pattern Recognition, Web-Technologies, Cultural Heritage, Crowdsourcing, Citizen Science, Optical Character Recognition, Accessibility.
National Category
Humanities and the Arts
Identifiers
URN: urn:nbn:se:lnu:diva-114820OAI: oai:DiVA.org:lnu-114820DiVA, id: diva2:1676488
Subject / course
Digital humanities
Educational program
Digital humanities, master programme, 120 credits
Supervisors
Examiners
Available from: 2022-07-01 Created: 2022-06-26 Last updated: 2022-07-01Bibliographically approved

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Ballerino, Julie
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Department of Cultural SciencesDepartment of computer science and media technology (CM)
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CiteExportLink to record
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Citation style
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